id	sid	tid	token	lemma	pos
ejpam-5015	1	1	european	european	PROPN
ejpam-5015	1	2	journal	journal	PROPN
ejpam-5015	1	3	of	of	ADP
ejpam-5015	1	4	pure	pure	ADJ
ejpam-5015	1	5	and	and	CCONJ
ejpam-5015	1	6	applied	apply	VERB
ejpam-5015	1	7	mathematics	mathematic	NOUN
ejpam-5015	1	8	vol	vol	NOUN
ejpam-5015	1	9	.	.	PROPN
ejpam-5015	2	1	17	17	NUM
ejpam-5015	2	2	,	,	PUNCT
ejpam-5015	2	3	no	no	INTJ
ejpam-5015	2	4	.	.	NOUN
ejpam-5015	2	5	1	1	NUM
ejpam-5015	2	6	,	,	PUNCT
ejpam-5015	2	7	2024	2024	NUM
ejpam-5015	2	8	,	,	PUNCT
ejpam-5015	2	9	180	180	NUM
ejpam-5015	2	10	-	-	SYM
ejpam-5015	2	11	200	200	NUM
ejpam-5015	2	12	issn	issn	PROPN
ejpam-5015	2	13	1307	1307	NUM
ejpam-5015	2	14	-	-	SYM
ejpam-5015	2	15	5543	5543	NUM
ejpam-5015	2	16	–	–	PUNCT
ejpam-5015	2	17	ejpam.com	ejpam.com	X
ejpam-5015	2	18	published	publish	VERB
ejpam-5015	2	19	by	by	ADP
ejpam-5015	2	20	new	new	PROPN
ejpam-5015	2	21	york	york	PROPN
ejpam-5015	2	22	business	business	PROPN
ejpam-5015	2	23	global	global	ADJ
ejpam-5015	2	24	bayesian	bayesian	NOUN
ejpam-5015	2	25	regression	regression	NOUN
ejpam-5015	2	26	analysis	analysis	NOUN
ejpam-5015	2	27	using	use	VERB
ejpam-5015	2	28	median	median	ADJ
ejpam-5015	2	29	rank	rank	NOUN
ejpam-5015	2	30	set	set	NOUN
ejpam-5015	2	31	sampling	sample	VERB
ejpam-5015	2	32	inad	inad	PROPN
ejpam-5015	2	33	nawajah1,∗	nawajah1,∗	PROPN
ejpam-5015	2	34	,	,	PUNCT
ejpam-5015	2	35	hassan	hassan	PROPN
ejpam-5015	2	36	kanj2	kanj2	PROPN
ejpam-5015	2	37	,	,	PUNCT
ejpam-5015	2	38	,	,	PUNCT
ejpam-5015	2	39	yehia	yehia	PROPN
ejpam-5015	2	40	kotb2	kotb2	PROPN
ejpam-5015	2	41	,	,	PUNCT
ejpam-5015	2	42	,	,	PUNCT
ejpam-5015	2	43	julian	julian	PROPN
ejpam-5015	2	44	hoxha2	hoxha2	PROPN
ejpam-5015	2	45	,	,	PUNCT
ejpam-5015	2	46	,	,	PUNCT
ejpam-5015	2	47	mouhammad	mouhammad	NOUN
ejpam-5015	2	48	alakkoumi2	alakkoumi2	PROPN
ejpam-5015	2	49	,	,	PUNCT
ejpam-5015	2	50	,	,	PUNCT
ejpam-5015	2	51	kamel	kamel	PROPN
ejpam-5015	2	52	jebreen3,4,5	jebreen3,4,5	PROPN
ejpam-5015	2	53	,	,	PUNCT
ejpam-5015	2	54	1	1	NUM
ejpam-5015	2	55	department	department	NOUN
ejpam-5015	2	56	of	of	ADP
ejpam-5015	2	57	mathematics	mathematic	NOUN
ejpam-5015	2	58	,	,	PUNCT
ejpam-5015	2	59	college	college	NOUN
ejpam-5015	2	60	of	of	ADP
ejpam-5015	2	61	science	science	NOUN
ejpam-5015	2	62	and	and	CCONJ
ejpam-5015	2	63	technology	technology	NOUN
ejpam-5015	2	64	,	,	PUNCT
ejpam-5015	2	65	hebron	hebron	PROPN
ejpam-5015	2	66	university	university	PROPN
ejpam-5015	2	67	,	,	PUNCT
ejpam-5015	2	68	palestine	palestine	PROPN
ejpam-5015	2	69	2	2	NUM
ejpam-5015	2	70	college	college	NOUN
ejpam-5015	2	71	of	of	ADP
ejpam-5015	2	72	engineering	engineering	NOUN
ejpam-5015	2	73	and	and	CCONJ
ejpam-5015	2	74	technology	technology	NOUN
ejpam-5015	2	75	,	,	PUNCT
ejpam-5015	2	76	american	american	PROPN
ejpam-5015	2	77	university	university	PROPN
ejpam-5015	2	78	of	of	ADP
ejpam-5015	2	79	the	the	DET
ejpam-5015	2	80	middle	middle	PROPN
ejpam-5015	2	81	east	east	PROPN
ejpam-5015	2	82	,	,	PUNCT
ejpam-5015	2	83	egaila	egaila	PROPN
ejpam-5015	2	84	54200	54200	NUM
ejpam-5015	2	85	,	,	PUNCT
ejpam-5015	2	86	kuwait	kuwait	PROPN
ejpam-5015	2	87	3	3	NUM
ejpam-5015	2	88	department	department	NOUN
ejpam-5015	2	89	of	of	ADP
ejpam-5015	2	90	mathematics	mathematics	PROPN
ejpam-5015	2	91	,	,	PUNCT
ejpam-5015	2	92	palestine	palestine	PROPN
ejpam-5015	2	93	technical	technical	PROPN
ejpam-5015	2	94	university	university	PROPN
ejpam-5015	2	95	kadoorie	kadoorie	NOUN
ejpam-5015	2	96	,	,	PUNCT
ejpam-5015	2	97	hebron	hebron	PROPN
ejpam-5015	2	98	,	,	PUNCT
ejpam-5015	2	99	palestine	palestine	PROPN
ejpam-5015	2	100	4	4	NUM
ejpam-5015	2	101	department	department	NOUN
ejpam-5015	2	102	of	of	ADP
ejpam-5015	2	103	mathematics	mathematic	NOUN
ejpam-5015	2	104	,	,	PUNCT
ejpam-5015	2	105	an	an	DET
ejpam-5015	2	106	-	-	PUNCT
ejpam-5015	2	107	najah	najah	ADJ
ejpam-5015	2	108	national	national	ADJ
ejpam-5015	2	109	university	university	NOUN
ejpam-5015	2	110	,	,	PUNCT
ejpam-5015	2	111	nablus	nablus	PROPN
ejpam-5015	2	112	,	,	PUNCT
ejpam-5015	2	113	palestine	palestine	PROPN
ejpam-5015	2	114	5	5	NUM
ejpam-5015	2	115	unité	unité	NOUN
ejpam-5015	2	116	de	de	X
ejpam-5015	2	117	recherche	recherche	X
ejpam-5015	2	118	clinique	clinique	PROPN
ejpam-5015	2	119	saint	saint	PROPN
ejpam-5015	2	120	-	-	PUNCT
ejpam-5015	2	121	louis	louis	NOUN
ejpam-5015	2	122	fernand	fernand	NOUN
ejpam-5015	2	123	-	-	PUNCT
ejpam-5015	2	124	widal	widal	ADJ
ejpam-5015	2	125	lariboisière	lariboisière	NOUN
ejpam-5015	2	126	,	,	PUNCT
ejpam-5015	2	127	aphp	aphp	ADJ
ejpam-5015	2	128	,	,	PUNCT
ejpam-5015	2	129	paris	paris	PROPN
ejpam-5015	2	130	,	,	PUNCT
ejpam-5015	2	131	france	france	PROPN
ejpam-5015	2	132	abstract	abstract	NOUN
ejpam-5015	2	133	.	.	PUNCT
ejpam-5015	3	1	bayesian	bayesian	NOUN
ejpam-5015	3	2	estimation	estimation	NOUN
ejpam-5015	3	3	of	of	ADP
ejpam-5015	3	4	the	the	DET
ejpam-5015	3	5	linear	linear	ADJ
ejpam-5015	3	6	regression	regression	NOUN
ejpam-5015	3	7	parameter	parameter	NOUN
ejpam-5015	3	8	system	system	NOUN
ejpam-5015	3	9	is	be	AUX
ejpam-5015	3	10	considered	consider	VERB
ejpam-5015	3	11	by	by	ADP
ejpam-5015	3	12	deploying	deploy	VERB
ejpam-5015	3	13	median	median	ADJ
ejpam-5015	3	14	rank	rank	NOUN
ejpam-5015	3	15	set	set	NOUN
ejpam-5015	3	16	sampling	sample	VERB
ejpam-5015	3	17	(	(	PUNCT
ejpam-5015	3	18	mrss	mrss	NOUN
ejpam-5015	3	19	)	)	PUNCT
ejpam-5015	3	20	.	.	PUNCT
ejpam-5015	4	1	the	the	DET
ejpam-5015	4	2	full	full	ADJ
ejpam-5015	4	3	conditional	conditional	ADJ
ejpam-5015	4	4	distributions	distribution	NOUN
ejpam-5015	4	5	and	and	CCONJ
ejpam-5015	4	6	the	the	DET
ejpam-5015	4	7	associated	associated	ADJ
ejpam-5015	4	8	posterior	posterior	ADJ
ejpam-5015	4	9	distribution	distribution	NOUN
ejpam-5015	4	10	are	be	AUX
ejpam-5015	4	11	obtained	obtain	VERB
ejpam-5015	4	12	.	.	PUNCT
ejpam-5015	5	1	therefore	therefore	ADV
ejpam-5015	5	2	,	,	PUNCT
ejpam-5015	5	3	based	base	VERB
ejpam-5015	5	4	on	on	ADP
ejpam-5015	5	5	markov	markov	NOUN
ejpam-5015	5	6	chain	chain	NOUN
ejpam-5015	5	7	monte	monte	PROPN
ejpam-5015	5	8	carlo	carlo	PROPN
ejpam-5015	5	9	simulation	simulation	PROPN
ejpam-5015	5	10	,	,	PUNCT
ejpam-5015	5	11	the	the	DET
ejpam-5015	5	12	bayesian	bayesian	NOUN
ejpam-5015	5	13	point	point	NOUN
ejpam-5015	5	14	estimates	estimate	NOUN
ejpam-5015	5	15	and	and	CCONJ
ejpam-5015	5	16	credible	credible	ADJ
ejpam-5015	5	17	intervals	interval	NOUN
ejpam-5015	5	18	for	for	ADP
ejpam-5015	5	19	the	the	DET
ejpam-5015	5	20	regression	regression	NOUN
ejpam-5015	5	21	parameters	parameter	NOUN
ejpam-5015	5	22	are	be	AUX
ejpam-5015	5	23	determined	determine	VERB
ejpam-5015	5	24	.	.	PUNCT
ejpam-5015	6	1	to	to	PART
ejpam-5015	6	2	measure	measure	VERB
ejpam-5015	6	3	the	the	DET
ejpam-5015	6	4	efficiency	efficiency	NOUN
ejpam-5015	6	5	of	of	ADP
ejpam-5015	6	6	the	the	DET
ejpam-5015	6	7	obtained	obtain	VERB
ejpam-5015	6	8	bayesian	bayesian	NOUN
ejpam-5015	6	9	estimates	estimate	NOUN
ejpam-5015	6	10	concerning	concern	VERB
ejpam-5015	6	11	the	the	DET
ejpam-5015	6	12	frequentist	frequentist	NOUN
ejpam-5015	6	13	estimates	estimate	VERB
ejpam-5015	6	14	we	we	PRON
ejpam-5015	6	15	compute	compute	VERB
ejpam-5015	6	16	the	the	DET
ejpam-5015	6	17	asymptotic	asymptotic	ADJ
ejpam-5015	6	18	relative	relative	ADJ
ejpam-5015	6	19	efficiency	efficiency	NOUN
ejpam-5015	6	20	of	of	ADP
ejpam-5015	6	21	the	the	DET
ejpam-5015	6	22	obtained	obtain	VERB
ejpam-5015	6	23	bayesian	bayesian	NOUN
ejpam-5015	6	24	estimates	estimate	NOUN
ejpam-5015	6	25	using	use	VERB
ejpam-5015	6	26	markov	markov	NOUN
ejpam-5015	6	27	chain	chain	NOUN
ejpam-5015	6	28	monte	monte	PROPN
ejpam-5015	6	29	carlo	carlo	PROPN
ejpam-5015	6	30	simulation	simulation	PROPN
ejpam-5015	6	31	.	.	PUNCT
ejpam-5015	7	1	this	this	DET
ejpam-5015	7	2	study	study	NOUN
ejpam-5015	7	3	shows	show	VERB
ejpam-5015	7	4	that	that	SCONJ
ejpam-5015	7	5	the	the	DET
ejpam-5015	7	6	bayesian	bayesian	NOUN
ejpam-5015	7	7	estimation	estimation	NOUN
ejpam-5015	7	8	of	of	ADP
ejpam-5015	7	9	the	the	DET
ejpam-5015	7	10	simple	simple	ADJ
ejpam-5015	7	11	linear	linear	ADJ
ejpam-5015	7	12	regression	regression	NOUN
ejpam-5015	7	13	parameters	parameter	NOUN
ejpam-5015	7	14	under	under	ADP
ejpam-5015	7	15	frequentist	frequentist	NOUN
ejpam-5015	7	16	mrss	mrss	NOUN
ejpam-5015	7	17	is	be	AUX
ejpam-5015	7	18	highly	highly	ADV
ejpam-5015	7	19	beneficial	beneficial	ADJ
ejpam-5015	7	20	and	and	CCONJ
ejpam-5015	7	21	much	much	ADV
ejpam-5015	7	22	superior	superior	ADJ
ejpam-5015	7	23	to	to	ADP
ejpam-5015	7	24	the	the	DET
ejpam-5015	7	25	rss	rss	NOUN
ejpam-5015	7	26	scheme	scheme	NOUN
ejpam-5015	7	27	.	.	PUNCT
ejpam-5015	8	1	2020	2020	NUM
ejpam-5015	8	2	mathematics	mathematic	NOUN
ejpam-5015	8	3	subject	subject	NOUN
ejpam-5015	8	4	classifications	classification	NOUN
ejpam-5015	8	5	:	:	PUNCT
ejpam-5015	8	6	62c10	62c10	NUM
ejpam-5015	8	7	,	,	PUNCT
ejpam-5015	8	8	62j20	62j20	NUM
ejpam-5015	8	9	,	,	PUNCT
ejpam-5015	8	10	62d05	62d05	NUM
ejpam-5015	8	11	key	key	ADJ
ejpam-5015	8	12	words	word	NOUN
ejpam-5015	8	13	and	and	CCONJ
ejpam-5015	8	14	phrases	phrase	NOUN
ejpam-5015	8	15	:	:	PUNCT
ejpam-5015	8	16	median	median	NOUN
ejpam-5015	8	17	ranked	rank	VERB
ejpam-5015	8	18	set	set	ADJ
ejpam-5015	8	19	sampling	sampling	NOUN
ejpam-5015	8	20	;	;	PUNCT
ejpam-5015	8	21	bayes	bayes	NOUN
ejpam-5015	8	22	factor	factor	NOUN
ejpam-5015	8	23	;	;	PUNCT
ejpam-5015	8	24	regression	regression	NOUN
ejpam-5015	8	25	;	;	PUNCT
ejpam-5015	8	26	bayesian	bayesian	NOUN
ejpam-5015	8	27	approach	approach	NOUN
ejpam-5015	8	28	1	1	NUM
ejpam-5015	8	29	.	.	PUNCT
ejpam-5015	9	1	introduction	introduction	NOUN
ejpam-5015	9	2	regression	regression	NOUN
ejpam-5015	9	3	is	be	AUX
ejpam-5015	9	4	the	the	DET
ejpam-5015	9	5	process	process	NOUN
ejpam-5015	9	6	of	of	ADP
ejpam-5015	9	7	investigating	investigate	VERB
ejpam-5015	9	8	the	the	DET
ejpam-5015	9	9	relationship	relationship	NOUN
ejpam-5015	9	10	between	between	ADP
ejpam-5015	9	11	a	a	DET
ejpam-5015	9	12	dependent	dependent	ADJ
ejpam-5015	9	13	variable	variable	NOUN
ejpam-5015	9	14	and	and	CCONJ
ejpam-5015	9	15	some	some	DET
ejpam-5015	9	16	independent	independent	ADJ
ejpam-5015	9	17	variables	variable	NOUN
ejpam-5015	9	18	given	give	VERB
ejpam-5015	9	19	a	a	DET
ejpam-5015	9	20	set	set	NOUN
ejpam-5015	9	21	of	of	ADP
ejpam-5015	9	22	historical	historical	ADJ
ejpam-5015	9	23	data	datum	NOUN
ejpam-5015	9	24	.	.	PUNCT
ejpam-5015	10	1	the	the	DET
ejpam-5015	10	2	objective	objective	NOUN
ejpam-5015	10	3	of	of	ADP
ejpam-5015	10	4	regression	regression	NOUN
ejpam-5015	10	5	is	be	AUX
ejpam-5015	10	6	to	to	PART
ejpam-5015	10	7	discover	discover	VERB
ejpam-5015	10	8	a	a	DET
ejpam-5015	10	9	model	model	NOUN
ejpam-5015	10	10	that	that	PRON
ejpam-5015	10	11	accurately	accurately	ADV
ejpam-5015	10	12	captures	capture	VERB
ejpam-5015	10	13	this	this	DET
ejpam-5015	10	14	relationship	relationship	NOUN
ejpam-5015	10	15	and	and	CCONJ
ejpam-5015	10	16	minimizes	minimize	VERB
ejpam-5015	10	17	the	the	DET
ejpam-5015	10	18	discrepancy	discrepancy	NOUN
ejpam-5015	10	19	between	between	ADP
ejpam-5015	10	20	predicted	predict	VERB
ejpam-5015	10	21	values	value	NOUN
ejpam-5015	10	22	from	from	ADP
ejpam-5015	10	23	the	the	DET
ejpam-5015	10	24	model	model	NOUN
ejpam-5015	10	25	and	and	CCONJ
ejpam-5015	10	26	the	the	DET
ejpam-5015	10	27	actual	actual	ADJ
ejpam-5015	10	28	values	value	NOUN
ejpam-5015	10	29	observed	observe	VERB
ejpam-5015	10	30	in	in	ADP
ejpam-5015	10	31	the	the	DET
ejpam-5015	10	32	data	datum	NOUN
ejpam-5015	10	33	.	.	PUNCT
ejpam-5015	11	1	∗corresponding	∗corresponde	VERB
ejpam-5015	11	2	author	author	NOUN
ejpam-5015	11	3	.	.	PUNCT
ejpam-5015	12	1	doi	doi	NOUN
ejpam-5015	12	2	:	:	PUNCT
ejpam-5015	12	3	https://doi.org/10.29020/nybg.ejpam.v17i1.5015	https://doi.org/10.29020/nybg.ejpam.v17i1.5015	NOUN
ejpam-5015	12	4	email	email	NOUN
ejpam-5015	12	5	addresses	address	VERB
ejpam-5015	12	6	:	:	PUNCT
ejpam-5015	13	1	inadn@hebron.edu	inadn@hebron.edu	PROPN
ejpam-5015	13	2	(	(	PUNCT
ejpam-5015	13	3	i.	i.	PROPN
ejpam-5015	13	4	nawaja	nawaja	PROPN
ejpam-5015	13	5	)	)	PUNCT
ejpam-5015	13	6	,	,	PUNCT
ejpam-5015	13	7	hassan.kanj@aum.edu.kw	hassan.kanj@aum.edu.kw	PROPN
ejpam-5015	13	8	(	(	PUNCT
ejpam-5015	13	9	h.	h.	PROPN
ejpam-5015	13	10	kanj	kanj	PROPN
ejpam-5015	13	11	)	)	PUNCT
ejpam-5015	13	12	,	,	PUNCT
ejpam-5015	13	13	yehia.kotb@aum.edu.kw	yehia.kotb@aum.edu.kw	PROPN
ejpam-5015	13	14	(	(	PUNCT
ejpam-5015	13	15	y.	y.	PROPN
ejpam-5015	13	16	kotb	kotb	PROPN
ejpam-5015	13	17	)	)	PUNCT
ejpam-5015	13	18	,	,	PUNCT
ejpam-5015	13	19	julian.hoxha@aum.edu.kw	julian.hoxha@aum.edu.kw	INTJ
ejpam-5015	13	20	(	(	PUNCT
ejpam-5015	13	21	j.	j.	PROPN
ejpam-5015	13	22	hoxha	hoxha	PROPN
ejpam-5015	13	23	)	)	PUNCT
ejpam-5015	13	24	,	,	PUNCT
ejpam-5015	13	25	mouhammad.a@aum.edu.kw	mouhammad.a@aum.edu.kw	NOUN
ejpam-5015	13	26	(	(	PUNCT
ejpam-5015	13	27	m.	m.	NOUN
ejpam-5015	13	28	alakkoumi	alakkoumi	PROPN
ejpam-5015	13	29	)	)	PUNCT
ejpam-5015	13	30	k.jebreen@yahoo.com	k.jebreen@yahoo.com	PROPN
ejpam-5015	13	31	(	(	PUNCT
ejpam-5015	13	32	k.	k.	PROPN
ejpam-5015	13	33	jebreen	jebreen	PROPN
ejpam-5015	13	34	)	)	PUNCT
ejpam-5015	13	35	https://www.ejpam.com	https://www.ejpam.com	NOUN
ejpam-5015	14	1	180	180	NUM
ejpam-5015	14	2	©	©	PROPN
ejpam-5015	14	3	2024	2024	NUM
ejpam-5015	14	4	ejpam	ejpam	NOUN
ejpam-5015	14	5	all	all	DET
ejpam-5015	14	6	rights	right	NOUN
ejpam-5015	14	7	reserved	reserve	VERB
ejpam-5015	14	8	.	.	PUNCT
ejpam-5015	15	1	i.	i.	PROPN
ejpam-5015	15	2	nawajah	nawajah	PROPN
ejpam-5015	15	3	,	,	PUNCT
ejpam-5015	15	4	h.	h.	PROPN
ejpam-5015	15	5	kanj	kanj	PROPN
ejpam-5015	15	6	,	,	PUNCT
ejpam-5015	15	7	y.	y.	PROPN
ejpam-5015	15	8	kotb	kotb	PROPN
ejpam-5015	15	9	,	,	PUNCT
ejpam-5015	15	10	j.	j.	PROPN
ejpam-5015	15	11	hoxha	hoxha	PROPN
ejpam-5015	15	12	,	,	PUNCT
ejpam-5015	15	13	m.	m.	PROPN
ejpam-5015	15	14	alakkoumi	alakkoumi	PROPN
ejpam-5015	15	15	,	,	PUNCT
ejpam-5015	15	16	k.	k.	PROPN
ejpam-5015	15	17	jebreen	jebreen	PROPN
ejpam-5015	15	18	/	/	SYM
ejpam-5015	15	19	eur	eur	PROPN
ejpam-5015	15	20	.	.	PUNCT
ejpam-5015	16	1	j.	j.	PROPN
ejpam-5015	16	2	pure	pure	PROPN
ejpam-5015	16	3	appl	appl	PROPN
ejpam-5015	16	4	.	.	PROPN
ejpam-5015	16	5	math	math	PROPN
ejpam-5015	16	6	,	,	PUNCT
ejpam-5015	16	7	17	17	NUM
ejpam-5015	16	8	(	(	PUNCT
ejpam-5015	16	9	1	1	NUM
ejpam-5015	16	10	)	)	PUNCT
ejpam-5015	16	11	(	(	PUNCT
ejpam-5015	16	12	2024	2024	NUM
ejpam-5015	16	13	)	)	PUNCT
ejpam-5015	16	14	,	,	PUNCT
ejpam-5015	16	15	180	180	NUM
ejpam-5015	16	16	-	-	SYM
ejpam-5015	16	17	200	200	NUM
ejpam-5015	16	18	181	181	NUM
ejpam-5015	16	19	regression	regression	NOUN
ejpam-5015	16	20	encompasses	encompass	VERB
ejpam-5015	16	21	various	various	ADJ
ejpam-5015	16	22	techniques	technique	NOUN
ejpam-5015	16	23	,	,	PUNCT
ejpam-5015	16	24	and	and	CCONJ
ejpam-5015	16	25	one	one	NUM
ejpam-5015	16	26	common	common	ADJ
ejpam-5015	16	27	approach	approach	NOUN
ejpam-5015	16	28	is	be	AUX
ejpam-5015	16	29	linear	linear	PROPN
ejpam-5015	16	30	regression	regression	NOUN
ejpam-5015	16	31	,	,	PUNCT
ejpam-5015	16	32	which	which	PRON
ejpam-5015	16	33	takes	take	VERB
ejpam-5015	16	34	the	the	DET
ejpam-5015	16	35	form	form	NOUN
ejpam-5015	16	36	of	of	ADP
ejpam-5015	16	37	:	:	PUNCT
ejpam-5015	17	1	y	y	PROPN
ejpam-5015	17	2	=	=	SYM
ejpam-5015	17	3	β0	β0	PROPN
ejpam-5015	18	1	+	+	CCONJ
ejpam-5015	18	2	β1x1	β1x1	PUNCT
ejpam-5015	19	1	+	+	NUM
ejpam-5015	19	2	β2x2	β2x2	PUNCT
ejpam-5015	19	3	+	+	CCONJ
ejpam-5015	19	4	.	.	PUNCT
ejpam-5015	19	5	.	.	PUNCT
ejpam-5015	19	6	.	.	PUNCT
ejpam-5015	20	1	+	+	CCONJ
ejpam-5015	20	2	βnxn	βnxn	NOUN
ejpam-5015	20	3	+	+	CCONJ
ejpam-5015	20	4	ϵ	ϵ	X
ejpam-5015	20	5	(	(	PUNCT
ejpam-5015	20	6	1	1	NUM
ejpam-5015	20	7	)	)	PUNCT
ejpam-5015	20	8	in	in	ADP
ejpam-5015	20	9	the	the	DET
ejpam-5015	20	10	equation	equation	NOUN
ejpam-5015	20	11	1	1	NUM
ejpam-5015	20	12	,	,	PUNCT
ejpam-5015	20	13	the	the	DET
ejpam-5015	20	14	dependent	dependent	ADJ
ejpam-5015	20	15	variable	variable	NOUN
ejpam-5015	20	16	y	y	PROPN
ejpam-5015	20	17	is	be	AUX
ejpam-5015	20	18	related	relate	VERB
ejpam-5015	20	19	to	to	ADP
ejpam-5015	20	20	the	the	DET
ejpam-5015	20	21	independent	independent	ADJ
ejpam-5015	20	22	variables	variable	NOUN
ejpam-5015	20	23	xi	xi	PROPN
ejpam-5015	20	24	,	,	PUNCT
ejpam-5015	20	25	where	where	SCONJ
ejpam-5015	20	26	1	1	NUM
ejpam-5015	20	27	≤	≤	NUM
ejpam-5015	20	28	i	i	PRON
ejpam-5015	20	29	≤	≤	PROPN
ejpam-5015	20	30	n.	n.	VERB
ejpam-5015	20	31	the	the	DET
ejpam-5015	20	32	coefficients	coefficient	NOUN
ejpam-5015	20	33	βi	βi	PRON
ejpam-5015	20	34	represent	represent	VERB
ejpam-5015	20	35	the	the	DET
ejpam-5015	20	36	respective	respective	ADJ
ejpam-5015	20	37	coefficients	coefficient	NOUN
ejpam-5015	20	38	for	for	ADP
ejpam-5015	20	39	each	each	DET
ejpam-5015	20	40	independent	independent	ADJ
ejpam-5015	20	41	variable	variable	NOUN
ejpam-5015	20	42	,	,	PUNCT
ejpam-5015	20	43	and	and	CCONJ
ejpam-5015	20	44	the	the	DET
ejpam-5015	20	45	term	term	NOUN
ejpam-5015	20	46	ϵ	ϵ	AUX
ejpam-5015	20	47	represents	represent	VERB
ejpam-5015	20	48	the	the	DET
ejpam-5015	20	49	error	error	NOUN
ejpam-5015	20	50	.	.	PUNCT
ejpam-5015	21	1	this	this	DET
ejpam-5015	21	2	equation	equation	NOUN
ejpam-5015	21	3	serves	serve	VERB
ejpam-5015	21	4	as	as	ADP
ejpam-5015	21	5	a	a	DET
ejpam-5015	21	6	general	general	ADJ
ejpam-5015	21	7	representation	representation	NOUN
ejpam-5015	21	8	of	of	ADP
ejpam-5015	21	9	linear	linear	ADJ
ejpam-5015	21	10	regression	regression	NOUN
ejpam-5015	21	11	and	and	CCONJ
ejpam-5015	21	12	can	can	AUX
ejpam-5015	21	13	be	be	AUX
ejpam-5015	21	14	modified	modify	VERB
ejpam-5015	21	15	to	to	PART
ejpam-5015	21	16	accommodate	accommodate	VERB
ejpam-5015	21	17	polynomial	polynomial	ADJ
ejpam-5015	21	18	regression	regression	NOUN
ejpam-5015	21	19	,	,	PUNCT
ejpam-5015	21	20	as	as	SCONJ
ejpam-5015	21	21	we	we	PRON
ejpam-5015	21	22	will	will	AUX
ejpam-5015	21	23	explore	explore	VERB
ejpam-5015	21	24	later	later	ADV
ejpam-5015	21	25	in	in	ADP
ejpam-5015	21	26	this	this	DET
ejpam-5015	21	27	section	section	NOUN
ejpam-5015	21	28	.	.	PUNCT
ejpam-5015	22	1	as	as	SCONJ
ejpam-5015	22	2	previously	previously	ADV
ejpam-5015	22	3	mentioned	mention	VERB
ejpam-5015	22	4	,	,	PUNCT
ejpam-5015	22	5	linear	linear	ADJ
ejpam-5015	22	6	regression	regression	NOUN
ejpam-5015	22	7	can	can	AUX
ejpam-5015	22	8	be	be	AUX
ejpam-5015	22	9	categorized	categorize	VERB
ejpam-5015	22	10	into	into	ADP
ejpam-5015	22	11	different	different	ADJ
ejpam-5015	22	12	types	type	NOUN
ejpam-5015	22	13	,	,	PUNCT
ejpam-5015	22	14	and	and	CCONJ
ejpam-5015	22	15	one	one	NUM
ejpam-5015	22	16	such	such	ADJ
ejpam-5015	22	17	type	type	NOUN
ejpam-5015	22	18	is	be	AUX
ejpam-5015	22	19	simple	simple	ADJ
ejpam-5015	22	20	linear	linear	ADJ
ejpam-5015	22	21	regression	regression	NOUN
ejpam-5015	22	22	.	.	PUNCT
ejpam-5015	23	1	in	in	ADP
ejpam-5015	23	2	simple	simple	ADJ
ejpam-5015	23	3	linear	linear	ADJ
ejpam-5015	23	4	regression	regression	NOUN
ejpam-5015	23	5	,	,	PUNCT
ejpam-5015	23	6	the	the	DET
ejpam-5015	23	7	objective	objective	NOUN
ejpam-5015	23	8	is	be	AUX
ejpam-5015	23	9	to	to	PART
ejpam-5015	23	10	establish	establish	VERB
ejpam-5015	23	11	a	a	DET
ejpam-5015	23	12	model	model	NOUN
ejpam-5015	23	13	that	that	PRON
ejpam-5015	23	14	relates	relate	VERB
ejpam-5015	23	15	a	a	DET
ejpam-5015	23	16	single	single	ADJ
ejpam-5015	23	17	dependent	dependent	ADJ
ejpam-5015	23	18	variable	variable	ADJ
ejpam-5015	23	19	y	y	PROPN
ejpam-5015	23	20	to	to	ADP
ejpam-5015	23	21	a	a	DET
ejpam-5015	23	22	single	single	ADJ
ejpam-5015	23	23	independent	independent	ADJ
ejpam-5015	23	24	variable	variable	NOUN
ejpam-5015	23	25	x.	x.	NOUN
ejpam-5015	23	26	by	by	ADP
ejpam-5015	23	27	substituting	substitute	VERB
ejpam-5015	23	28	n	n	NOUN
ejpam-5015	23	29	=	=	SYM
ejpam-5015	23	30	1	1	NUM
ejpam-5015	23	31	into	into	ADP
ejpam-5015	23	32	equation	equation	NOUN
ejpam-5015	23	33	1	1	NUM
ejpam-5015	23	34	,	,	PUNCT
ejpam-5015	23	35	we	we	PRON
ejpam-5015	23	36	obtain	obtain	VERB
ejpam-5015	23	37	the	the	DET
ejpam-5015	23	38	equation	equation	NOUN
ejpam-5015	23	39	specifically	specifically	ADV
ejpam-5015	23	40	for	for	ADP
ejpam-5015	23	41	simple	simple	ADJ
ejpam-5015	23	42	linear	linear	ADJ
ejpam-5015	23	43	regression	regression	NOUN
ejpam-5015	23	44	:	:	PUNCT
ejpam-5015	24	1	y	y	PROPN
ejpam-5015	24	2	=	=	SYM
ejpam-5015	24	3	β0	β0	PROPN
ejpam-5015	25	1	+	+	CCONJ
ejpam-5015	25	2	β1x+	β1x+	PROPN
ejpam-5015	25	3	ϵ	ϵ	X
ejpam-5015	25	4	(	(	PUNCT
ejpam-5015	25	5	2	2	NUM
ejpam-5015	25	6	)	)	PUNCT
ejpam-5015	25	7	note	note	NOUN
ejpam-5015	25	8	that	that	SCONJ
ejpam-5015	25	9	x1	x1	PROPN
ejpam-5015	25	10	was	be	AUX
ejpam-5015	25	11	referred	refer	VERB
ejpam-5015	25	12	to	to	ADP
ejpam-5015	25	13	as	as	ADP
ejpam-5015	25	14	x	x	PRON
ejpam-5015	25	15	since	since	SCONJ
ejpam-5015	25	16	it	it	PRON
ejpam-5015	25	17	is	be	AUX
ejpam-5015	25	18	the	the	DET
ejpam-5015	25	19	only	only	ADJ
ejpam-5015	25	20	independent	independent	ADJ
ejpam-5015	25	21	variable	variable	NOUN
ejpam-5015	25	22	in	in	ADP
ejpam-5015	25	23	the	the	DET
ejpam-5015	25	24	data	datum	NOUN
ejpam-5015	25	25	set	set	VERB
ejpam-5015	25	26	.	.	PUNCT
ejpam-5015	26	1	the	the	DET
ejpam-5015	26	2	error	error	NOUN
ejpam-5015	26	3	in	in	ADP
ejpam-5015	26	4	this	this	DET
ejpam-5015	26	5	context	context	NOUN
ejpam-5015	26	6	is	be	AUX
ejpam-5015	26	7	defined	define	VERB
ejpam-5015	26	8	as	as	ADP
ejpam-5015	26	9	the	the	DET
ejpam-5015	26	10	euclidean	euclidean	ADJ
ejpam-5015	26	11	distance	distance	NOUN
ejpam-5015	26	12	between	between	ADP
ejpam-5015	26	13	each	each	DET
ejpam-5015	26	14	data	data	NOUN
ejpam-5015	26	15	point	point	NOUN
ejpam-5015	26	16	and	and	CCONJ
ejpam-5015	26	17	the	the	DET
ejpam-5015	26	18	model	model	NOUN
ejpam-5015	26	19	.	.	PUNCT
ejpam-5015	27	1	the	the	DET
ejpam-5015	27	2	objective	objective	NOUN
ejpam-5015	27	3	of	of	ADP
ejpam-5015	27	4	simple	simple	ADJ
ejpam-5015	27	5	linear	linear	ADJ
ejpam-5015	27	6	regression	regression	NOUN
ejpam-5015	27	7	is	be	AUX
ejpam-5015	27	8	to	to	PART
ejpam-5015	27	9	determine	determine	VERB
ejpam-5015	27	10	the	the	DET
ejpam-5015	27	11	optimal	optimal	ADJ
ejpam-5015	27	12	values	value	NOUN
ejpam-5015	27	13	of	of	ADP
ejpam-5015	27	14	β0	β0	NOUN
ejpam-5015	27	15	and	and	CCONJ
ejpam-5015	27	16	β1	β1	PROPN
ejpam-5015	27	17	that	that	PRON
ejpam-5015	27	18	minimize	minimize	VERB
ejpam-5015	27	19	this	this	DET
ejpam-5015	27	20	error	error	NOUN
ejpam-5015	27	21	.	.	PUNCT
ejpam-5015	28	1	simple	simple	ADJ
ejpam-5015	28	2	linear	linear	ADJ
ejpam-5015	28	3	regression	regression	NOUN
ejpam-5015	28	4	offers	offer	VERB
ejpam-5015	28	5	several	several	ADJ
ejpam-5015	28	6	advantages	advantage	NOUN
ejpam-5015	28	7	and	and	CCONJ
ejpam-5015	28	8	disadvantages	disadvantage	NOUN
ejpam-5015	28	9	.	.	PUNCT
ejpam-5015	29	1	some	some	PRON
ejpam-5015	29	2	of	of	ADP
ejpam-5015	29	3	the	the	DET
ejpam-5015	29	4	advantages	advantage	NOUN
ejpam-5015	29	5	include	include	VERB
ejpam-5015	29	6	simplicity	simplicity	NOUN
ejpam-5015	29	7	,	,	PUNCT
ejpam-5015	29	8	high	high	ADJ
ejpam-5015	29	9	performance	performance	NOUN
ejpam-5015	29	10	,	,	PUNCT
ejpam-5015	29	11	and	and	CCONJ
ejpam-5015	29	12	interpretability	interpretability	NOUN
ejpam-5015	29	13	.	.	PUNCT
ejpam-5015	30	1	the	the	DET
ejpam-5015	30	2	simplicity	simplicity	NOUN
ejpam-5015	30	3	arises	arise	VERB
ejpam-5015	30	4	from	from	ADP
ejpam-5015	30	5	the	the	DET
ejpam-5015	30	6	model	model	NOUN
ejpam-5015	30	7	’s	’s	PART
ejpam-5015	30	8	relationship	relationship	NOUN
ejpam-5015	30	9	between	between	ADP
ejpam-5015	30	10	the	the	DET
ejpam-5015	30	11	dependent	dependent	ADJ
ejpam-5015	30	12	variable	variable	ADJ
ejpam-5015	30	13	y	y	PROPN
ejpam-5015	30	14	and	and	CCONJ
ejpam-5015	30	15	a	a	DET
ejpam-5015	30	16	single	single	ADJ
ejpam-5015	30	17	independent	independent	ADJ
ejpam-5015	30	18	variable	variable	ADJ
ejpam-5015	30	19	x.	x.	NOUN
ejpam-5015	31	1	this	this	DET
ejpam-5015	31	2	simplicity	simplicity	NOUN
ejpam-5015	31	3	contributes	contribute	VERB
ejpam-5015	31	4	to	to	ADP
ejpam-5015	31	5	its	its	PRON
ejpam-5015	31	6	high	high	ADJ
ejpam-5015	31	7	performance	performance	NOUN
ejpam-5015	31	8	,	,	PUNCT
ejpam-5015	31	9	making	make	VERB
ejpam-5015	31	10	it	it	PRON
ejpam-5015	31	11	suitable	suitable	ADJ
ejpam-5015	31	12	for	for	ADP
ejpam-5015	31	13	real	real	ADJ
ejpam-5015	31	14	-	-	PUNCT
ejpam-5015	31	15	time	time	NOUN
ejpam-5015	31	16	systems	system	NOUN
ejpam-5015	31	17	.	.	PUNCT
ejpam-5015	32	1	additionally	additionally	ADV
ejpam-5015	32	2	,	,	PUNCT
ejpam-5015	32	3	the	the	DET
ejpam-5015	32	4	model	model	NOUN
ejpam-5015	32	5	is	be	AUX
ejpam-5015	32	6	easily	easily	ADV
ejpam-5015	32	7	interpretable	interpretable	ADJ
ejpam-5015	32	8	,	,	PUNCT
ejpam-5015	32	9	with	with	ADP
ejpam-5015	32	10	the	the	DET
ejpam-5015	32	11	intercept	intercept	NOUN
ejpam-5015	32	12	(	(	PUNCT
ejpam-5015	32	13	β0	β0	NOUN
ejpam-5015	32	14	)	)	PUNCT
ejpam-5015	32	15	representing	represent	VERB
ejpam-5015	32	16	the	the	DET
ejpam-5015	32	17	expected	expect	VERB
ejpam-5015	32	18	value	value	NOUN
ejpam-5015	32	19	of	of	ADP
ejpam-5015	32	20	y	y	PRON
ejpam-5015	32	21	when	when	SCONJ
ejpam-5015	32	22	x	x	PRON
ejpam-5015	32	23	is	be	AUX
ejpam-5015	32	24	zero	zero	NUM
ejpam-5015	32	25	and	and	CCONJ
ejpam-5015	32	26	the	the	DET
ejpam-5015	32	27	slope	slope	NOUN
ejpam-5015	32	28	coefficient	coefficient	NOUN
ejpam-5015	32	29	(	(	PUNCT
ejpam-5015	32	30	β1	β1	PROPN
ejpam-5015	32	31	)	)	PUNCT
ejpam-5015	32	32	indicating	indicate	VERB
ejpam-5015	32	33	the	the	DET
ejpam-5015	32	34	change	change	NOUN
ejpam-5015	32	35	in	in	ADP
ejpam-5015	32	36	y	y	PROPN
ejpam-5015	32	37	for	for	ADP
ejpam-5015	32	38	each	each	DET
ejpam-5015	32	39	unit	unit	NOUN
ejpam-5015	32	40	increase	increase	VERB
ejpam-5015	32	41	in	in	ADP
ejpam-5015	32	42	x.	x.	NOUN
ejpam-5015	32	43	simple	simple	ADJ
ejpam-5015	32	44	linear	linear	PROPN
ejpam-5015	32	45	regression	regression	NOUN
ejpam-5015	32	46	also	also	ADV
ejpam-5015	32	47	has	have	VERB
ejpam-5015	32	48	some	some	DET
ejpam-5015	32	49	disadvantages	disadvantage	NOUN
ejpam-5015	32	50	.	.	PUNCT
ejpam-5015	33	1	one	one	NUM
ejpam-5015	33	2	such	such	ADJ
ejpam-5015	33	3	disadvantage	disadvantage	NOUN
ejpam-5015	33	4	is	be	AUX
ejpam-5015	33	5	the	the	DET
ejpam-5015	33	6	linearity	linearity	NOUN
ejpam-5015	33	7	assumption	assumption	NOUN
ejpam-5015	33	8	,	,	PUNCT
ejpam-5015	33	9	which	which	PRON
ejpam-5015	33	10	assumes	assume	VERB
ejpam-5015	33	11	that	that	SCONJ
ejpam-5015	33	12	the	the	DET
ejpam-5015	33	13	relationship	relationship	NOUN
ejpam-5015	33	14	between	between	ADP
ejpam-5015	33	15	the	the	DET
ejpam-5015	33	16	variables	variable	NOUN
ejpam-5015	33	17	is	be	AUX
ejpam-5015	33	18	strictly	strictly	ADV
ejpam-5015	33	19	linear	linear	ADJ
ejpam-5015	33	20	.	.	PUNCT
ejpam-5015	34	1	in	in	ADP
ejpam-5015	34	2	reality	reality	NOUN
ejpam-5015	34	3	,	,	PUNCT
ejpam-5015	34	4	observations	observation	NOUN
ejpam-5015	34	5	often	often	ADV
ejpam-5015	34	6	exhibit	exhibit	VERB
ejpam-5015	34	7	non	non	ADJ
ejpam-5015	34	8	-	-	ADJ
ejpam-5015	34	9	linear	linear	ADJ
ejpam-5015	34	10	patterns	pattern	NOUN
ejpam-5015	34	11	,	,	PUNCT
ejpam-5015	34	12	making	make	VERB
ejpam-5015	34	13	this	this	DET
ejpam-5015	34	14	assumption	assumption	NOUN
ejpam-5015	34	15	restrictive	restrictive	ADJ
ejpam-5015	34	16	and	and	CCONJ
ejpam-5015	34	17	potentially	potentially	ADV
ejpam-5015	34	18	leading	lead	VERB
ejpam-5015	34	19	to	to	ADP
ejpam-5015	34	20	higher	high	ADJ
ejpam-5015	34	21	mean	mean	ADJ
ejpam-5015	34	22	square	square	ADJ
ejpam-5015	34	23	error	error	NOUN
ejpam-5015	34	24	.	.	PUNCT
ejpam-5015	35	1	another	another	DET
ejpam-5015	35	2	drawback	drawback	NOUN
ejpam-5015	35	3	is	be	AUX
ejpam-5015	35	4	the	the	DET
ejpam-5015	35	5	sensitivity	sensitivity	NOUN
ejpam-5015	35	6	of	of	ADP
ejpam-5015	35	7	simple	simple	ADJ
ejpam-5015	35	8	linear	linear	ADJ
ejpam-5015	35	9	regression	regression	NOUN
ejpam-5015	35	10	to	to	ADP
ejpam-5015	35	11	outliers	outlier	NOUN
ejpam-5015	35	12	.	.	PUNCT
ejpam-5015	36	1	outliers	outlier	NOUN
ejpam-5015	36	2	can	can	AUX
ejpam-5015	36	3	disproportionately	disproportionately	ADV
ejpam-5015	36	4	influence	influence	VERB
ejpam-5015	36	5	the	the	DET
ejpam-5015	36	6	model	model	NOUN
ejpam-5015	36	7	’s	’s	PART
ejpam-5015	36	8	estimates	estimate	NOUN
ejpam-5015	36	9	,	,	PUNCT
ejpam-5015	36	10	leading	lead	VERB
ejpam-5015	36	11	to	to	ADP
ejpam-5015	36	12	distorted	distorted	ADJ
ejpam-5015	36	13	results	result	NOUN
ejpam-5015	36	14	and	and	CCONJ
ejpam-5015	36	15	increased	increase	VERB
ejpam-5015	36	16	mean	mean	ADJ
ejpam-5015	36	17	square	square	NOUN
ejpam-5015	36	18	error	error	NOUN
ejpam-5015	36	19	.	.	PUNCT
ejpam-5015	37	1	as	as	SCONJ
ejpam-5015	37	2	mentioned	mention	VERB
ejpam-5015	37	3	earlier	early	ADV
ejpam-5015	37	4	,	,	PUNCT
ejpam-5015	37	5	while	while	SCONJ
ejpam-5015	37	6	equation	equation	NOUN
ejpam-5015	37	7	1	1	NUM
ejpam-5015	37	8	represents	represent	VERB
ejpam-5015	37	9	the	the	DET
ejpam-5015	37	10	multi	multi	ADJ
ejpam-5015	37	11	-	-	ADJ
ejpam-5015	37	12	variable	variable	ADJ
ejpam-5015	37	13	regression	regression	NOUN
ejpam-5015	37	14	,	,	PUNCT
ejpam-5015	37	15	it	it	PRON
ejpam-5015	37	16	can	can	AUX
ejpam-5015	37	17	also	also	ADV
ejpam-5015	37	18	be	be	AUX
ejpam-5015	37	19	considered	consider	VERB
ejpam-5015	37	20	as	as	ADP
ejpam-5015	37	21	a	a	DET
ejpam-5015	37	22	general	general	ADJ
ejpam-5015	37	23	equation	equation	NOUN
ejpam-5015	37	24	of	of	ADP
ejpam-5015	37	25	regression	regression	NOUN
ejpam-5015	37	26	.	.	PUNCT
ejpam-5015	38	1	as	as	SCONJ
ejpam-5015	38	2	seen	see	VERB
ejpam-5015	38	3	before	before	ADV
ejpam-5015	38	4	,	,	PUNCT
ejpam-5015	38	5	equation	equation	NOUN
ejpam-5015	38	6	2	2	NUM
ejpam-5015	38	7	is	be	AUX
ejpam-5015	38	8	a	a	DET
ejpam-5015	38	9	special	special	ADJ
ejpam-5015	38	10	case	case	NOUN
ejpam-5015	38	11	of	of	ADP
ejpam-5015	38	12	equation	equation	NOUN
ejpam-5015	38	13	1	1	NUM
ejpam-5015	38	14	.	.	PUNCT
ejpam-5015	38	15	similar	similar	ADJ
ejpam-5015	38	16	to	to	ADP
ejpam-5015	38	17	simple	simple	ADJ
ejpam-5015	38	18	linear	linear	ADJ
ejpam-5015	38	19	regression	regression	NOUN
ejpam-5015	38	20	,	,	PUNCT
ejpam-5015	38	21	polynomial	polynomial	ADJ
ejpam-5015	38	22	regression	regression	NOUN
ejpam-5015	38	23	is	be	AUX
ejpam-5015	38	24	a	a	DET
ejpam-5015	38	25	regression	regression	NOUN
ejpam-5015	38	26	model	model	NOUN
ejpam-5015	38	27	that	that	PRON
ejpam-5015	38	28	establishes	establish	VERB
ejpam-5015	38	29	a	a	DET
ejpam-5015	38	30	relationship	relationship	NOUN
ejpam-5015	38	31	between	between	ADP
ejpam-5015	38	32	a	a	DET
ejpam-5015	38	33	single	single	ADJ
ejpam-5015	38	34	independent	independent	ADJ
ejpam-5015	38	35	variable	variable	NOUN
ejpam-5015	38	36	x	x	PUNCT
ejpam-5015	38	37	and	and	CCONJ
ejpam-5015	38	38	the	the	DET
ejpam-5015	38	39	dependent	dependent	ADJ
ejpam-5015	38	40	variable	variable	ADJ
ejpam-5015	38	41	y.	y.	NOUN
ejpam-5015	38	42	in	in	ADP
ejpam-5015	38	43	contrast	contrast	NOUN
ejpam-5015	38	44	to	to	ADP
ejpam-5015	38	45	simple	simple	ADJ
ejpam-5015	38	46	linear	linear	ADJ
ejpam-5015	38	47	regression	regression	NOUN
ejpam-5015	38	48	,	,	PUNCT
ejpam-5015	38	49	polynomial	polynomial	ADJ
ejpam-5015	38	50	regression	regression	NOUN
ejpam-5015	38	51	offers	offer	VERB
ejpam-5015	38	52	improved	improved	ADJ
ejpam-5015	38	53	accuracy	accuracy	NOUN
ejpam-5015	38	54	by	by	ADP
ejpam-5015	38	55	incorporating	incorporate	VERB
ejpam-5015	38	56	higher	high	ADJ
ejpam-5015	38	57	-	-	PUNCT
ejpam-5015	38	58	degree	degree	NOUN
ejpam-5015	38	59	polynomials	polynomial	NOUN
ejpam-5015	38	60	.	.	PUNCT
ejpam-5015	39	1	additionally	additionally	ADV
ejpam-5015	39	2	,	,	PUNCT
ejpam-5015	39	3	polynomial	polynomial	ADJ
ejpam-5015	39	4	regression	regression	NOUN
ejpam-5015	39	5	can	can	AUX
ejpam-5015	39	6	be	be	AUX
ejpam-5015	39	7	viewed	view	VERB
ejpam-5015	39	8	as	as	ADP
ejpam-5015	39	9	a	a	DET
ejpam-5015	39	10	special	special	ADJ
ejpam-5015	39	11	case	case	NOUN
ejpam-5015	39	12	of	of	ADP
ejpam-5015	39	13	linear	linear	PROPN
ejpam-5015	39	14	regression	regression	NOUN
ejpam-5015	39	15	.	.	PUNCT
ejpam-5015	40	1	the	the	DET
ejpam-5015	40	2	equation	equation	NOUN
ejpam-5015	40	3	3	3	NUM
ejpam-5015	40	4	defines	define	VERB
ejpam-5015	40	5	polynomial	polynomial	ADJ
ejpam-5015	40	6	regression	regression	NOUN
ejpam-5015	40	7	as	as	SCONJ
ejpam-5015	40	8	follows	follow	VERB
ejpam-5015	40	9	:	:	PUNCT
ejpam-5015	41	1	y	y	PROPN
ejpam-5015	41	2	=	=	SYM
ejpam-5015	41	3	β0	β0	PROPN
ejpam-5015	41	4	+	+	CCONJ
ejpam-5015	41	5	β1x+	β1x+	NOUN
ejpam-5015	41	6	β2x2	β2x2	PUNCT
ejpam-5015	41	7	+	+	CCONJ
ejpam-5015	41	8	.	.	PUNCT
ejpam-5015	41	9	.	.	PUNCT
ejpam-5015	42	1	.+	.+	NOUN
ejpam-5015	42	2	xn	xn	PUNCT
ejpam-5015	43	1	+	+	NUM
ejpam-5015	43	2	ϵ	ϵ	X
ejpam-5015	43	3	(	(	PUNCT
ejpam-5015	43	4	3	3	NUM
ejpam-5015	43	5	)	)	PUNCT
ejpam-5015	43	6	i.	i.	PROPN
ejpam-5015	43	7	nawajah	nawajah	PROPN
ejpam-5015	43	8	,	,	PUNCT
ejpam-5015	43	9	h.	h.	PROPN
ejpam-5015	43	10	kanj	kanj	PROPN
ejpam-5015	43	11	,	,	PUNCT
ejpam-5015	43	12	y.	y.	PROPN
ejpam-5015	43	13	kotb	kotb	PROPN
ejpam-5015	43	14	,	,	PUNCT
ejpam-5015	43	15	j.	j.	PROPN
ejpam-5015	43	16	hoxha	hoxha	PROPN
ejpam-5015	43	17	,	,	PUNCT
ejpam-5015	43	18	m.	m.	PROPN
ejpam-5015	43	19	alakkoumi	alakkoumi	PROPN
ejpam-5015	43	20	,	,	PUNCT
ejpam-5015	43	21	k.	k.	PROPN
ejpam-5015	43	22	jebreen	jebreen	PROPN
ejpam-5015	43	23	/	/	SYM
ejpam-5015	43	24	eur	eur	PROPN
ejpam-5015	43	25	.	.	PUNCT
ejpam-5015	44	1	j.	j.	PROPN
ejpam-5015	44	2	pure	pure	PROPN
ejpam-5015	44	3	appl	appl	PROPN
ejpam-5015	44	4	.	.	PROPN
ejpam-5015	44	5	math	math	PROPN
ejpam-5015	44	6	,	,	PUNCT
ejpam-5015	44	7	17	17	NUM
ejpam-5015	44	8	(	(	PUNCT
ejpam-5015	44	9	1	1	NUM
ejpam-5015	44	10	)	)	PUNCT
ejpam-5015	44	11	(	(	PUNCT
ejpam-5015	44	12	2024	2024	NUM
ejpam-5015	44	13	)	)	PUNCT
ejpam-5015	44	14	,	,	PUNCT
ejpam-5015	44	15	180	180	NUM
ejpam-5015	44	16	-	-	SYM
ejpam-5015	44	17	200	200	NUM
ejpam-5015	44	18	182	182	NUM
ejpam-5015	44	19	since	since	SCONJ
ejpam-5015	44	20	data	datum	NOUN
ejpam-5015	44	21	is	be	AUX
ejpam-5015	44	22	being	be	AUX
ejpam-5015	44	23	collected	collect	VERB
ejpam-5015	44	24	from	from	ADP
ejpam-5015	44	25	real	real	ADJ
ejpam-5015	44	26	life	life	NOUN
ejpam-5015	44	27	scenarios	scenario	NOUN
ejpam-5015	44	28	,	,	PUNCT
ejpam-5015	44	29	there	there	PRON
ejpam-5015	44	30	is	be	VERB
ejpam-5015	44	31	a	a	DET
ejpam-5015	44	32	possibility	possibility	NOUN
ejpam-5015	44	33	of	of	ADP
ejpam-5015	44	34	error	error	NOUN
ejpam-5015	44	35	or	or	CCONJ
ejpam-5015	44	36	uncertainly	uncertainly	ADV
ejpam-5015	44	37	about	about	ADP
ejpam-5015	44	38	the	the	DET
ejpam-5015	44	39	validity	validity	NOUN
ejpam-5015	44	40	of	of	ADP
ejpam-5015	44	41	the	the	DET
ejpam-5015	44	42	gathered	gather	VERB
ejpam-5015	44	43	data	datum	NOUN
ejpam-5015	44	44	.	.	PUNCT
ejpam-5015	45	1	that	that	PRON
ejpam-5015	45	2	is	be	AUX
ejpam-5015	45	3	when	when	SCONJ
ejpam-5015	45	4	bayesian	bayesian	NOUN
ejpam-5015	45	5	statistics	statistic	NOUN
ejpam-5015	45	6	come	come	VERB
ejpam-5015	45	7	into	into	ADP
ejpam-5015	45	8	place	place	NOUN
ejpam-5015	45	9	.	.	PUNCT
ejpam-5015	46	1	bayesian	bayesian	NOUN
ejpam-5015	46	2	statistics	statistic	NOUN
ejpam-5015	46	3	is	be	AUX
ejpam-5015	46	4	a	a	DET
ejpam-5015	46	5	powerful	powerful	ADJ
ejpam-5015	46	6	technique	technique	NOUN
ejpam-5015	46	7	that	that	PRON
ejpam-5015	46	8	performs	perform	VERB
ejpam-5015	46	9	predictions	prediction	NOUN
ejpam-5015	46	10	based	base	VERB
ejpam-5015	46	11	on	on	ADP
ejpam-5015	46	12	history	history	NOUN
ejpam-5015	46	13	of	of	ADP
ejpam-5015	46	14	data	datum	NOUN
ejpam-5015	46	15	.	.	PUNCT
ejpam-5015	47	1	it	it	PRON
ejpam-5015	47	2	combines	combine	VERB
ejpam-5015	47	3	the	the	DET
ejpam-5015	47	4	uncertainty	uncertainty	NOUN
ejpam-5015	47	5	of	of	ADP
ejpam-5015	47	6	data	datum	NOUN
ejpam-5015	47	7	with	with	ADP
ejpam-5015	47	8	the	the	DET
ejpam-5015	47	9	model	model	NOUN
ejpam-5015	47	10	which	which	PRON
ejpam-5015	47	11	allows	allow	VERB
ejpam-5015	47	12	predictions	prediction	NOUN
ejpam-5015	47	13	to	to	PART
ejpam-5015	47	14	be	be	AUX
ejpam-5015	47	15	realistic	realistic	ADJ
ejpam-5015	47	16	and	and	CCONJ
ejpam-5015	47	17	match	match	VERB
ejpam-5015	47	18	the	the	DET
ejpam-5015	47	19	real	real	ADJ
ejpam-5015	47	20	world	world	NOUN
ejpam-5015	47	21	event	event	NOUN
ejpam-5015	47	22	.	.	PUNCT
ejpam-5015	48	1	the	the	DET
ejpam-5015	48	2	equation	equation	NOUN
ejpam-5015	48	3	of	of	ADP
ejpam-5015	48	4	bayes	bayes	PROPN
ejpam-5015	48	5	rule	rule	NOUN
ejpam-5015	48	6	is	be	AUX
ejpam-5015	48	7	as	as	SCONJ
ejpam-5015	48	8	follows	follow	VERB
ejpam-5015	48	9	:	:	PUNCT
ejpam-5015	48	10	p(a|b	p(a|b	NUM
ejpam-5015	48	11	)	)	PUNCT
ejpam-5015	48	12	=	=	SYM
ejpam-5015	48	13	p(b|a)×	p(b|a)×	PROPN
ejpam-5015	48	14	p(a	p(a	NOUN
ejpam-5015	48	15	)	)	PUNCT
ejpam-5015	48	16	p(b	p(b	PROPN
ejpam-5015	48	17	)	)	PUNCT
ejpam-5015	48	18	(	(	PUNCT
ejpam-5015	48	19	4	4	X
ejpam-5015	48	20	)	)	PUNCT
ejpam-5015	48	21	equation	equation	NOUN
ejpam-5015	48	22	4	4	NUM
ejpam-5015	48	23	deals	deal	NOUN
ejpam-5015	48	24	with	with	ADP
ejpam-5015	48	25	causalities	causality	NOUN
ejpam-5015	48	26	.	.	PUNCT
ejpam-5015	49	1	the	the	DET
ejpam-5015	49	2	equation	equation	NOUN
ejpam-5015	49	3	evaluates	evaluate	VERB
ejpam-5015	49	4	the	the	DET
ejpam-5015	49	5	probability	probability	NOUN
ejpam-5015	49	6	for	for	ADP
ejpam-5015	49	7	event	event	NOUN
ejpam-5015	49	8	a	a	PRON
ejpam-5015	49	9	to	to	PART
ejpam-5015	49	10	happen	happen	AUX
ejpam-5015	49	11	given	give	VERB
ejpam-5015	49	12	that	that	DET
ejpam-5015	49	13	event	event	NOUN
ejpam-5015	49	14	b	b	NOUN
ejpam-5015	49	15	has	have	AUX
ejpam-5015	49	16	already	already	ADV
ejpam-5015	49	17	occurred	occur	VERB
ejpam-5015	49	18	and	and	CCONJ
ejpam-5015	49	19	been	be	AUX
ejpam-5015	49	20	observed	observe	VERB
ejpam-5015	49	21	.	.	PUNCT
ejpam-5015	50	1	this	this	DET
ejpam-5015	50	2	probability	probability	NOUN
ejpam-5015	50	3	depends	depend	VERB
ejpam-5015	50	4	on	on	ADP
ejpam-5015	50	5	history	history	NOUN
ejpam-5015	50	6	.	.	PUNCT
ejpam-5015	51	1	history	history	NOUN
ejpam-5015	51	2	here	here	ADV
ejpam-5015	51	3	is	be	AUX
ejpam-5015	51	4	seen	see	VERB
ejpam-5015	51	5	as	as	ADP
ejpam-5015	51	6	prior	prior	ADJ
ejpam-5015	51	7	knowledge	knowledge	NOUN
ejpam-5015	51	8	represented	represent	VERB
ejpam-5015	51	9	by	by	ADP
ejpam-5015	51	10	p(a	p(a	PROPN
ejpam-5015	51	11	)	)	PUNCT
ejpam-5015	51	12	that	that	PRON
ejpam-5015	51	13	is	be	AUX
ejpam-5015	51	14	the	the	DET
ejpam-5015	51	15	the	the	DET
ejpam-5015	51	16	probability	probability	NOUN
ejpam-5015	51	17	of	of	ADP
ejpam-5015	51	18	the	the	DET
ejpam-5015	51	19	occurrence	occurrence	NOUN
ejpam-5015	51	20	of	of	ADP
ejpam-5015	51	21	event	event	NOUN
ejpam-5015	51	22	a.	a.	NOUN
ejpam-5015	51	23	the	the	DET
ejpam-5015	51	24	prior	prior	ADJ
ejpam-5015	51	25	probability	probability	NOUN
ejpam-5015	51	26	is	be	AUX
ejpam-5015	51	27	also	also	ADV
ejpam-5015	51	28	known	know	VERB
ejpam-5015	51	29	to	to	PART
ejpam-5015	51	30	be	be	AUX
ejpam-5015	51	31	the	the	DET
ejpam-5015	51	32	initial	initial	ADJ
ejpam-5015	51	33	belief	belief	NOUN
ejpam-5015	51	34	that	that	SCONJ
ejpam-5015	51	35	even	even	ADV
ejpam-5015	51	36	a	a	PRON
ejpam-5015	51	37	would	would	AUX
ejpam-5015	51	38	occur	occur	VERB
ejpam-5015	51	39	.	.	PUNCT
ejpam-5015	52	1	the	the	DET
ejpam-5015	52	2	marginal	marginal	ADJ
ejpam-5015	52	3	likelihood	likelihood	NOUN
ejpam-5015	52	4	p(b	p(b	PROPN
ejpam-5015	52	5	)	)	PUNCT
ejpam-5015	52	6	,	,	PUNCT
ejpam-5015	52	7	also	also	ADV
ejpam-5015	52	8	known	know	VERB
ejpam-5015	52	9	as	as	ADP
ejpam-5015	52	10	evidence	evidence	NOUN
ejpam-5015	52	11	,	,	PUNCT
ejpam-5015	52	12	is	be	AUX
ejpam-5015	52	13	the	the	DET
ejpam-5015	52	14	overall	overall	ADJ
ejpam-5015	52	15	probability	probability	NOUN
ejpam-5015	52	16	for	for	ADP
ejpam-5015	52	17	event	event	NOUN
ejpam-5015	52	18	b	b	PROPN
ejpam-5015	52	19	to	to	PART
ejpam-5015	52	20	occur	occur	VERB
ejpam-5015	52	21	.	.	PUNCT
ejpam-5015	53	1	this	this	PRON
ejpam-5015	53	2	is	be	AUX
ejpam-5015	53	3	particularly	particularly	ADV
ejpam-5015	53	4	important	important	ADJ
ejpam-5015	53	5	since	since	SCONJ
ejpam-5015	53	6	bayes	bayes	PROPN
ejpam-5015	53	7	studies	study	VERB
ejpam-5015	53	8	the	the	DET
ejpam-5015	53	9	causality	causality	NOUN
ejpam-5015	53	10	relationship	relationship	NOUN
ejpam-5015	53	11	between	between	ADP
ejpam-5015	53	12	b	b	PROPN
ejpam-5015	53	13	and	and	CCONJ
ejpam-5015	53	14	a	a	PRON
ejpam-5015	53	15	,	,	PUNCT
ejpam-5015	53	16	that	that	PRON
ejpam-5015	53	17	is	be	AUX
ejpam-5015	53	18	the	the	DET
ejpam-5015	53	19	frequency	frequency	NOUN
ejpam-5015	53	20	of	of	ADP
ejpam-5015	53	21	b	b	NOUN
ejpam-5015	53	22	causing	cause	VERB
ejpam-5015	53	23	a.	a.	NOUN
ejpam-5015	53	24	the	the	DET
ejpam-5015	53	25	likelihood	likelihood	NOUN
ejpam-5015	53	26	of	of	ADP
ejpam-5015	53	27	event	event	NOUN
ejpam-5015	53	28	a	a	DET
ejpam-5015	53	29	causing	cause	VERB
ejpam-5015	53	30	event	event	NOUN
ejpam-5015	53	31	b	b	NOUN
ejpam-5015	53	32	to	to	PART
ejpam-5015	53	33	occur	occur	VERB
ejpam-5015	53	34	is	be	AUX
ejpam-5015	53	35	represented	represent	VERB
ejpam-5015	53	36	by	by	ADP
ejpam-5015	53	37	p(b|a	p(b|a	NOUN
ejpam-5015	53	38	)	)	PUNCT
ejpam-5015	53	39	.	.	PUNCT
ejpam-5015	54	1	finaly	finaly	VERB
ejpam-5015	54	2	the	the	DET
ejpam-5015	54	3	posterior	posterior	ADJ
ejpam-5015	54	4	probability	probability	NOUN
ejpam-5015	54	5	or	or	CCONJ
ejpam-5015	54	6	the	the	DET
ejpam-5015	54	7	most	most	ADV
ejpam-5015	54	8	updated	update	VERB
ejpam-5015	54	9	probability	probability	NOUN
ejpam-5015	54	10	of	of	ADP
ejpam-5015	54	11	event	event	NOUN
ejpam-5015	54	12	b	b	NUM
ejpam-5015	54	13	causing	cause	VERB
ejpam-5015	54	14	the	the	DET
ejpam-5015	54	15	occurrence	occurrence	NOUN
ejpam-5015	54	16	of	of	ADP
ejpam-5015	54	17	a	a	PRON
ejpam-5015	54	18	is	be	AUX
ejpam-5015	54	19	given	give	VERB
ejpam-5015	54	20	by	by	ADP
ejpam-5015	54	21	p(a|b	p(a|b	NOUN
ejpam-5015	54	22	)	)	PUNCT
ejpam-5015	54	23	.	.	PUNCT
ejpam-5015	55	1	the	the	DET
ejpam-5015	55	2	problem	problem	NOUN
ejpam-5015	55	3	with	with	ADP
ejpam-5015	55	4	regression	regression	NOUN
ejpam-5015	55	5	is	be	AUX
ejpam-5015	55	6	the	the	DET
ejpam-5015	55	7	fact	fact	NOUN
ejpam-5015	55	8	that	that	SCONJ
ejpam-5015	55	9	it	it	PRON
ejpam-5015	55	10	deals	deal	VERB
ejpam-5015	55	11	with	with	ADP
ejpam-5015	55	12	continuous	continuous	ADJ
ejpam-5015	55	13	data	datum	NOUN
ejpam-5015	55	14	that	that	PRON
ejpam-5015	55	15	could	could	AUX
ejpam-5015	55	16	literally	literally	ADV
ejpam-5015	55	17	be	be	AUX
ejpam-5015	55	18	infinite	infinite	ADJ
ejpam-5015	55	19	when	when	SCONJ
ejpam-5015	55	20	observed	observe	VERB
ejpam-5015	55	21	from	from	ADP
ejpam-5015	55	22	a	a	DET
ejpam-5015	55	23	continuously	continuously	ADV
ejpam-5015	55	24	active	active	ADJ
ejpam-5015	55	25	environment	environment	NOUN
ejpam-5015	55	26	.	.	PUNCT
ejpam-5015	56	1	when	when	SCONJ
ejpam-5015	56	2	data	datum	NOUN
ejpam-5015	56	3	exceeds	exceed	VERB
ejpam-5015	56	4	certain	certain	ADJ
ejpam-5015	56	5	size	size	NOUN
ejpam-5015	56	6	,	,	PUNCT
ejpam-5015	56	7	the	the	DET
ejpam-5015	56	8	model	model	NOUN
ejpam-5015	56	9	could	could	AUX
ejpam-5015	56	10	be	be	AUX
ejpam-5015	56	11	vulnerable	vulnerable	ADJ
ejpam-5015	56	12	to	to	ADP
ejpam-5015	56	13	over	over	ADV
ejpam-5015	56	14	-	-	PUNCT
ejpam-5015	56	15	fitting	fitting	ADJ
ejpam-5015	56	16	.	.	PUNCT
ejpam-5015	57	1	we	we	PRON
ejpam-5015	57	2	use	use	VERB
ejpam-5015	57	3	sampling	sample	VERB
ejpam-5015	57	4	to	to	PART
ejpam-5015	57	5	make	make	VERB
ejpam-5015	57	6	sure	sure	ADJ
ejpam-5015	57	7	regression	regression	NOUN
ejpam-5015	57	8	is	be	AUX
ejpam-5015	57	9	performed	perform	VERB
ejpam-5015	57	10	smoothly	smoothly	ADV
ejpam-5015	57	11	and	and	CCONJ
ejpam-5015	57	12	avoid	avoid	VERB
ejpam-5015	57	13	any	any	DET
ejpam-5015	57	14	possible	possible	ADJ
ejpam-5015	57	15	data	datum	NOUN
ejpam-5015	57	16	problems	problem	NOUN
ejpam-5015	57	17	.	.	PUNCT
ejpam-5015	58	1	sampling	sample	VERB
ejpam-5015	58	2	is	be	AUX
ejpam-5015	58	3	much	much	ADV
ejpam-5015	58	4	more	more	ADV
ejpam-5015	58	5	efficient	efficient	ADJ
ejpam-5015	58	6	than	than	ADP
ejpam-5015	58	7	data	data	NOUN
ejpam-5015	58	8	sample	sample	NOUN
ejpam-5015	58	9	selection	selection	NOUN
ejpam-5015	58	10	from	from	ADP
ejpam-5015	58	11	a	a	DET
ejpam-5015	58	12	given	give	VERB
ejpam-5015	58	13	population	population	NOUN
ejpam-5015	58	14	.	.	PUNCT
ejpam-5015	59	1	sampling	sample	VERB
ejpam-5015	59	2	also	also	ADV
ejpam-5015	59	3	ensures	ensure	VERB
ejpam-5015	59	4	data	datum	NOUN
ejpam-5015	59	5	availability	availability	NOUN
ejpam-5015	59	6	since	since	SCONJ
ejpam-5015	59	7	collecting	collect	VERB
ejpam-5015	59	8	data	datum	NOUN
ejpam-5015	59	9	for	for	ADP
ejpam-5015	59	10	entire	entire	ADJ
ejpam-5015	59	11	population	population	NOUN
ejpam-5015	59	12	might	might	AUX
ejpam-5015	59	13	no	no	ADV
ejpam-5015	59	14	be	be	AUX
ejpam-5015	59	15	feasible	feasible	ADJ
ejpam-5015	59	16	specially	specially	ADV
ejpam-5015	59	17	for	for	ADP
ejpam-5015	59	18	application	application	NOUN
ejpam-5015	59	19	that	that	PRON
ejpam-5015	59	20	involve	involve	VERB
ejpam-5015	59	21	big	big	ADJ
ejpam-5015	59	22	data	datum	NOUN
ejpam-5015	59	23	[	[	X
ejpam-5015	59	24	5	5	NUM
ejpam-5015	59	25	]	]	PUNCT
ejpam-5015	59	26	.	.	PUNCT
ejpam-5015	60	1	one	one	NUM
ejpam-5015	60	2	of	of	ADP
ejpam-5015	60	3	the	the	DET
ejpam-5015	60	4	sampling	sample	VERB
ejpam-5015	60	5	techniques	technique	NOUN
ejpam-5015	60	6	is	be	AUX
ejpam-5015	60	7	the	the	DET
ejpam-5015	60	8	rank	rank	NOUN
ejpam-5015	60	9	set	set	NOUN
ejpam-5015	60	10	sampling	sample	VERB
ejpam-5015	60	11	(	(	PUNCT
ejpam-5015	60	12	rss	rss	NOUN
ejpam-5015	60	13	for	for	ADP
ejpam-5015	60	14	short	short	ADJ
ejpam-5015	60	15	)	)	PUNCT
ejpam-5015	61	1	[	[	X
ejpam-5015	61	2	22	22	NUM
ejpam-5015	61	3	]	]	PUNCT
ejpam-5015	61	4	.	.	PUNCT
ejpam-5015	62	1	rss	rss	PROPN
ejpam-5015	62	2	is	be	AUX
ejpam-5015	62	3	very	very	ADV
ejpam-5015	62	4	useful	useful	ADJ
ejpam-5015	62	5	when	when	SCONJ
ejpam-5015	62	6	data	datum	NOUN
ejpam-5015	62	7	sizes	size	NOUN
ejpam-5015	62	8	are	be	AUX
ejpam-5015	62	9	huge	huge	ADJ
ejpam-5015	62	10	or	or	CCONJ
ejpam-5015	62	11	if	if	SCONJ
ejpam-5015	62	12	the	the	DET
ejpam-5015	62	13	evaluation	evaluation	NOUN
ejpam-5015	62	14	or	or	CCONJ
ejpam-5015	62	15	measurement	measurement	NOUN
ejpam-5015	62	16	of	of	ADP
ejpam-5015	62	17	the	the	DET
ejpam-5015	62	18	independent	independent	ADJ
ejpam-5015	62	19	variables	variable	NOUN
ejpam-5015	62	20	is	be	AUX
ejpam-5015	62	21	computationally	computationally	ADV
ejpam-5015	62	22	expensive	expensive	ADJ
ejpam-5015	62	23	.	.	PUNCT
ejpam-5015	63	1	real	real	ADJ
ejpam-5015	63	2	time	time	NOUN
ejpam-5015	63	3	system	system	NOUN
ejpam-5015	63	4	that	that	PRON
ejpam-5015	63	5	uses	use	VERB
ejpam-5015	63	6	regression	regression	VERB
ejpam-5015	63	7	analysis	analysis	NOUN
ejpam-5015	63	8	as	as	ADP
ejpam-5015	63	9	an	an	DET
ejpam-5015	63	10	example	example	NOUN
ejpam-5015	63	11	can	can	AUX
ejpam-5015	63	12	make	make	VERB
ejpam-5015	63	13	great	great	ADJ
ejpam-5015	63	14	benefit	benefit	NOUN
ejpam-5015	63	15	of	of	ADP
ejpam-5015	63	16	rss	rss	NOUN
ejpam-5015	63	17	sampling	sampling	NOUN
ejpam-5015	63	18	since	since	SCONJ
ejpam-5015	63	19	system	system	NOUN
ejpam-5015	63	20	tasks	task	NOUN
ejpam-5015	63	21	have	have	VERB
ejpam-5015	63	22	deadlines	deadline	NOUN
ejpam-5015	63	23	to	to	PART
ejpam-5015	63	24	meet	meet	VERB
ejpam-5015	63	25	.	.	PUNCT
ejpam-5015	64	1	rank	rank	PROPN
ejpam-5015	64	2	set	set	NOUN
ejpam-5015	64	3	sampling	sample	VERB
ejpam-5015	64	4	performs	perform	NOUN
ejpam-5015	64	5	grouping	group	VERB
ejpam-5015	64	6	on	on	ADP
ejpam-5015	64	7	observations	observation	NOUN
ejpam-5015	64	8	in	in	ADP
ejpam-5015	64	9	the	the	DET
ejpam-5015	64	10	available	available	ADJ
ejpam-5015	64	11	population	population	NOUN
ejpam-5015	64	12	.	.	PUNCT
ejpam-5015	65	1	every	every	DET
ejpam-5015	65	2	group	group	NOUN
ejpam-5015	65	3	has	have	VERB
ejpam-5015	65	4	one	one	NUM
ejpam-5015	65	5	or	or	CCONJ
ejpam-5015	65	6	more	more	ADJ
ejpam-5015	65	7	observations	observation	NOUN
ejpam-5015	65	8	.	.	PUNCT
ejpam-5015	66	1	groups	group	NOUN
ejpam-5015	66	2	are	be	AUX
ejpam-5015	66	3	then	then	ADV
ejpam-5015	66	4	ranked	rank	VERB
ejpam-5015	66	5	and	and	CCONJ
ejpam-5015	66	6	chosen	choose	VERB
ejpam-5015	66	7	for	for	ADP
ejpam-5015	66	8	sampling	sample	VERB
ejpam-5015	66	9	.	.	PUNCT
ejpam-5015	67	1	the	the	DET
ejpam-5015	67	2	structure	structure	NOUN
ejpam-5015	67	3	of	of	ADP
ejpam-5015	67	4	this	this	DET
ejpam-5015	67	5	article	article	NOUN
ejpam-5015	67	6	is	be	AUX
ejpam-5015	67	7	as	as	SCONJ
ejpam-5015	67	8	follows	follow	VERB
ejpam-5015	67	9	:	:	PUNCT
ejpam-5015	67	10	section	section	NOUN
ejpam-5015	67	11	1	1	NUM
ejpam-5015	67	12	provides	provide	VERB
ejpam-5015	67	13	an	an	DET
ejpam-5015	67	14	introduction	introduction	NOUN
ejpam-5015	67	15	to	to	ADP
ejpam-5015	67	16	the	the	DET
ejpam-5015	67	17	topic	topic	NOUN
ejpam-5015	67	18	.	.	PUNCT
ejpam-5015	68	1	section	section	NOUN
ejpam-5015	68	2	2	2	NUM
ejpam-5015	68	3	presents	present	VERB
ejpam-5015	68	4	a	a	DET
ejpam-5015	68	5	review	review	NOUN
ejpam-5015	68	6	of	of	ADP
ejpam-5015	68	7	prior	prior	ADJ
ejpam-5015	68	8	research	research	NOUN
ejpam-5015	68	9	in	in	ADP
ejpam-5015	68	10	the	the	DET
ejpam-5015	68	11	field	field	NOUN
ejpam-5015	68	12	.	.	PUNCT
ejpam-5015	69	1	section	section	NOUN
ejpam-5015	69	2	3	3	NUM
ejpam-5015	69	3	outlines	outline	VERB
ejpam-5015	69	4	the	the	DET
ejpam-5015	69	5	proposed	propose	VERB
ejpam-5015	69	6	model	model	NOUN
ejpam-5015	69	7	described	describe	VERB
ejpam-5015	69	8	in	in	ADP
ejpam-5015	69	9	this	this	DET
ejpam-5015	69	10	paper	paper	NOUN
ejpam-5015	69	11	.	.	PUNCT
ejpam-5015	70	1	section	section	NOUN
ejpam-5015	70	2	4	4	NUM
ejpam-5015	70	3	introduces	introduce	VERB
ejpam-5015	70	4	the	the	DET
ejpam-5015	70	5	bayes	bayes	PROPN
ejpam-5015	70	6	estimator	estimator	NOUN
ejpam-5015	70	7	and	and	CCONJ
ejpam-5015	70	8	the	the	DET
ejpam-5015	70	9	model	model	NOUN
ejpam-5015	70	10	selector	selector	NOUN
ejpam-5015	70	11	proposed	propose	VERB
ejpam-5015	70	12	in	in	ADP
ejpam-5015	70	13	this	this	DET
ejpam-5015	70	14	study	study	NOUN
ejpam-5015	70	15	.	.	PUNCT
ejpam-5015	71	1	section	section	NOUN
ejpam-5015	71	2	5	5	NUM
ejpam-5015	71	3	discusses	discuss	VERB
ejpam-5015	71	4	the	the	DET
ejpam-5015	71	5	bayes	bayes	NOUN
ejpam-5015	71	6	factor	factor	NOUN
ejpam-5015	71	7	of	of	ADP
ejpam-5015	71	8	estimators	estimator	NOUN
ejpam-5015	71	9	utilized	utilize	VERB
ejpam-5015	71	10	in	in	ADP
ejpam-5015	71	11	this	this	DET
ejpam-5015	71	12	article	article	NOUN
ejpam-5015	71	13	.	.	PUNCT
ejpam-5015	72	1	section	section	NOUN
ejpam-5015	72	2	6	6	NUM
ejpam-5015	72	3	describes	describe	VERB
ejpam-5015	72	4	the	the	DET
ejpam-5015	72	5	simulation	simulation	NOUN
ejpam-5015	72	6	methodology	methodology	NOUN
ejpam-5015	72	7	and	and	CCONJ
ejpam-5015	72	8	presents	present	VERB
ejpam-5015	72	9	the	the	DET
ejpam-5015	72	10	corresponding	corresponding	ADJ
ejpam-5015	72	11	results	result	NOUN
ejpam-5015	72	12	.	.	PUNCT
ejpam-5015	73	1	finally	finally	ADV
ejpam-5015	73	2	,	,	PUNCT
ejpam-5015	73	3	section	section	NOUN
ejpam-5015	73	4	8	8	NUM
ejpam-5015	73	5	offers	offer	VERB
ejpam-5015	73	6	a	a	DET
ejpam-5015	73	7	discussion	discussion	NOUN
ejpam-5015	73	8	of	of	ADP
ejpam-5015	73	9	the	the	DET
ejpam-5015	73	10	findings	finding	NOUN
ejpam-5015	73	11	and	and	CCONJ
ejpam-5015	73	12	concludes	conclude	VERB
ejpam-5015	73	13	the	the	DET
ejpam-5015	73	14	article	article	NOUN
ejpam-5015	73	15	[	[	X
ejpam-5015	73	16	16	16	NUM
ejpam-5015	73	17	,	,	PUNCT
ejpam-5015	73	18	19	19	NUM
ejpam-5015	73	19	]	]	PUNCT
ejpam-5015	73	20	.	.	PUNCT
ejpam-5015	74	1	i.	i.	PROPN
ejpam-5015	74	2	nawajah	nawajah	PROPN
ejpam-5015	74	3	,	,	PUNCT
ejpam-5015	74	4	h.	h.	PROPN
ejpam-5015	74	5	kanj	kanj	PROPN
ejpam-5015	74	6	,	,	PUNCT
ejpam-5015	74	7	y.	y.	PROPN
ejpam-5015	74	8	kotb	kotb	PROPN
ejpam-5015	74	9	,	,	PUNCT
ejpam-5015	74	10	j.	j.	PROPN
ejpam-5015	74	11	hoxha	hoxha	PROPN
ejpam-5015	74	12	,	,	PUNCT
ejpam-5015	74	13	m.	m.	PROPN
ejpam-5015	74	14	alakkoumi	alakkoumi	PROPN
ejpam-5015	74	15	,	,	PUNCT
ejpam-5015	74	16	k.	k.	PROPN
ejpam-5015	74	17	jebreen	jebreen	PROPN
ejpam-5015	74	18	/	/	SYM
ejpam-5015	74	19	eur	eur	PROPN
ejpam-5015	74	20	.	.	PUNCT
ejpam-5015	75	1	j.	j.	PROPN
ejpam-5015	75	2	pure	pure	PROPN
ejpam-5015	75	3	appl	appl	PROPN
ejpam-5015	75	4	.	.	PROPN
ejpam-5015	75	5	math	math	PROPN
ejpam-5015	75	6	,	,	PUNCT
ejpam-5015	75	7	17	17	NUM
ejpam-5015	75	8	(	(	PUNCT
ejpam-5015	75	9	1	1	NUM
ejpam-5015	75	10	)	)	PUNCT
ejpam-5015	75	11	(	(	PUNCT
ejpam-5015	75	12	2024	2024	NUM
ejpam-5015	75	13	)	)	PUNCT
ejpam-5015	75	14	,	,	PUNCT
ejpam-5015	75	15	180	180	NUM
ejpam-5015	75	16	-	-	SYM
ejpam-5015	75	17	200	200	NUM
ejpam-5015	75	18	183	183	NUM
ejpam-5015	75	19	2	2	NUM
ejpam-5015	75	20	.	.	PUNCT
ejpam-5015	75	21	previous	previous	ADJ
ejpam-5015	75	22	work	work	NOUN
ejpam-5015	75	23	the	the	DET
ejpam-5015	75	24	introduction	introduction	NOUN
ejpam-5015	75	25	of	of	ADP
ejpam-5015	75	26	ranked	rank	VERB
ejpam-5015	75	27	set	set	ADJ
ejpam-5015	75	28	sampling	sampling	NOUN
ejpam-5015	75	29	(	(	PUNCT
ejpam-5015	75	30	rss	rss	PROPN
ejpam-5015	75	31	)	)	PUNCT
ejpam-5015	75	32	,	,	PUNCT
ejpam-5015	75	33	a	a	DET
ejpam-5015	75	34	relatively	relatively	ADV
ejpam-5015	75	35	new	new	ADJ
ejpam-5015	75	36	sampling	sampling	NOUN
ejpam-5015	75	37	technique	technique	NOUN
ejpam-5015	75	38	for	for	ADP
ejpam-5015	75	39	estimating	estimate	VERB
ejpam-5015	75	40	population	population	NOUN
ejpam-5015	75	41	mean	mean	VERB
ejpam-5015	75	42	,	,	PUNCT
ejpam-5015	75	43	was	be	AUX
ejpam-5015	75	44	originally	originally	ADV
ejpam-5015	75	45	presented	present	VERB
ejpam-5015	75	46	in	in	ADP
ejpam-5015	75	47	a	a	DET
ejpam-5015	75	48	paper	paper	NOUN
ejpam-5015	75	49	by	by	ADP
ejpam-5015	75	50	mcintyre	mcintyre	PROPN
ejpam-5015	76	1	[	[	X
ejpam-5015	76	2	22	22	NUM
ejpam-5015	76	3	]	]	PUNCT
ejpam-5015	76	4	.	.	PUNCT
ejpam-5015	77	1	rss	rss	NOUN
ejpam-5015	77	2	involves	involve	VERB
ejpam-5015	77	3	the	the	DET
ejpam-5015	77	4	following	follow	VERB
ejpam-5015	77	5	steps	step	NOUN
ejpam-5015	77	6	:	:	PUNCT
ejpam-5015	77	7	firstly	firstly	ADV
ejpam-5015	77	8	,	,	PUNCT
ejpam-5015	77	9	a	a	DET
ejpam-5015	77	10	visual	visual	ADJ
ejpam-5015	77	11	inspection	inspection	NOUN
ejpam-5015	77	12	is	be	AUX
ejpam-5015	77	13	employed	employ	VERB
ejpam-5015	77	14	to	to	PART
ejpam-5015	77	15	randomly	randomly	VERB
ejpam-5015	77	16	select	select	ADJ
ejpam-5015	77	17	m2	m2	PROPN
ejpam-5015	77	18	sample	sample	NOUN
ejpam-5015	77	19	units	unit	NOUN
ejpam-5015	77	20	from	from	ADP
ejpam-5015	77	21	the	the	DET
ejpam-5015	77	22	target	target	NOUN
ejpam-5015	77	23	population	population	NOUN
ejpam-5015	77	24	.	.	PUNCT
ejpam-5015	78	1	secondly	secondly	ADV
ejpam-5015	78	2	,	,	PUNCT
ejpam-5015	78	3	these	these	DET
ejpam-5015	78	4	selected	select	VERB
ejpam-5015	78	5	units	unit	NOUN
ejpam-5015	78	6	are	be	AUX
ejpam-5015	78	7	allocated	allocate	VERB
ejpam-5015	78	8	into	into	ADP
ejpam-5015	78	9	m	m	PROPN
ejpam-5015	78	10	sets	set	NOUN
ejpam-5015	78	11	as	as	ADV
ejpam-5015	78	12	randomly	randomly	ADV
ejpam-5015	78	13	as	as	ADP
ejpam-5015	78	14	possible	possible	ADJ
ejpam-5015	78	15	,	,	PUNCT
ejpam-5015	78	16	with	with	ADP
ejpam-5015	78	17	each	each	DET
ejpam-5015	78	18	set	set	VERB
ejpam-5015	78	19	comprising	comprise	VERB
ejpam-5015	78	20	m	m	NOUN
ejpam-5015	78	21	units	unit	NOUN
ejpam-5015	78	22	.	.	PUNCT
ejpam-5015	79	1	thirdly	thirdly	ADV
ejpam-5015	79	2	,	,	PUNCT
ejpam-5015	79	3	an	an	DET
ejpam-5015	79	4	rss	rss	NOUN
ejpam-5015	79	5	of	of	ADP
ejpam-5015	79	6	size	size	NOUN
ejpam-5015	79	7	m	m	VERB
ejpam-5015	79	8	is	be	AUX
ejpam-5015	79	9	constructed	construct	VERB
ejpam-5015	79	10	for	for	ADP
ejpam-5015	79	11	analysis	analysis	NOUN
ejpam-5015	79	12	by	by	ADP
ejpam-5015	79	13	sequentially	sequentially	ADV
ejpam-5015	79	14	selecting	select	VERB
ejpam-5015	79	15	the	the	DET
ejpam-5015	79	16	smallest	small	ADJ
ejpam-5015	79	17	ranked	rank	VERB
ejpam-5015	79	18	unit	unit	NOUN
ejpam-5015	79	19	from	from	ADP
ejpam-5015	79	20	the	the	DET
ejpam-5015	79	21	first	first	ADJ
ejpam-5015	79	22	set	set	NOUN
ejpam-5015	79	23	,	,	PUNCT
ejpam-5015	79	24	the	the	DET
ejpam-5015	79	25	second	second	ADJ
ejpam-5015	79	26	smallest	small	ADJ
ejpam-5015	79	27	ranked	rank	VERB
ejpam-5015	79	28	unit	unit	NOUN
ejpam-5015	79	29	from	from	ADP
ejpam-5015	79	30	the	the	DET
ejpam-5015	79	31	second	second	ADJ
ejpam-5015	79	32	set	set	NOUN
ejpam-5015	79	33	,	,	PUNCT
ejpam-5015	79	34	and	and	CCONJ
ejpam-5015	79	35	so	so	ADV
ejpam-5015	79	36	on	on	ADV
ejpam-5015	79	37	,	,	PUNCT
ejpam-5015	79	38	until	until	SCONJ
ejpam-5015	79	39	the	the	DET
ejpam-5015	79	40	largest	large	ADJ
ejpam-5015	79	41	ranked	rank	VERB
ejpam-5015	79	42	unit	unit	NOUN
ejpam-5015	79	43	is	be	AUX
ejpam-5015	79	44	chosen	choose	VERB
ejpam-5015	79	45	from	from	ADP
ejpam-5015	79	46	the	the	DET
ejpam-5015	79	47	last	last	ADJ
ejpam-5015	79	48	set	set	NOUN
ejpam-5015	79	49	.	.	PUNCT
ejpam-5015	80	1	this	this	DET
ejpam-5015	80	2	process	process	NOUN
ejpam-5015	80	3	can	can	AUX
ejpam-5015	80	4	be	be	AUX
ejpam-5015	80	5	repeated	repeat	VERB
ejpam-5015	80	6	r	r	NOUN
ejpam-5015	80	7	times	time	NOUN
ejpam-5015	80	8	to	to	PART
ejpam-5015	80	9	obtain	obtain	VERB
ejpam-5015	80	10	a	a	DET
ejpam-5015	80	11	desired	desire	VERB
ejpam-5015	80	12	sample	sample	NOUN
ejpam-5015	80	13	size	size	NOUN
ejpam-5015	80	14	of	of	ADP
ejpam-5015	80	15	n	n	PROPN
ejpam-5015	80	16	=	=	SYM
ejpam-5015	80	17	rm	rm	PROPN
ejpam-5015	81	1	[	[	X
ejpam-5015	81	2	26	26	NUM
ejpam-5015	81	3	]	]	PUNCT
ejpam-5015	81	4	.	.	PUNCT
ejpam-5015	82	1	several	several	ADJ
ejpam-5015	82	2	authors	author	NOUN
ejpam-5015	82	3	have	have	AUX
ejpam-5015	82	4	evaluated	evaluate	VERB
ejpam-5015	82	5	the	the	DET
ejpam-5015	82	6	effectiveness	effectiveness	NOUN
ejpam-5015	82	7	of	of	ADP
ejpam-5015	82	8	bayesian	bayesian	NOUN
ejpam-5015	82	9	approaches	approach	NOUN
ejpam-5015	82	10	in	in	ADP
ejpam-5015	82	11	the	the	DET
ejpam-5015	82	12	context	context	NOUN
ejpam-5015	82	13	of	of	ADP
ejpam-5015	82	14	rss	rss	NOUN
ejpam-5015	82	15	,	,	PUNCT
ejpam-5015	82	16	including	include	VERB
ejpam-5015	82	17	al	al	PROPN
ejpam-5015	82	18	-	-	PUNCT
ejpam-5015	82	19	saleh	saleh	PROPN
ejpam-5015	82	20	et	et	PROPN
ejpam-5015	82	21	al	al	PROPN
ejpam-5015	82	22	.	.	PUNCT
ejpam-5015	83	1	[	[	X
ejpam-5015	83	2	2	2	NUM
ejpam-5015	83	3	]	]	PUNCT
ejpam-5015	83	4	,	,	PUNCT
ejpam-5015	83	5	alodat	alodat	PROPN
ejpam-5015	83	6	and	and	CCONJ
ejpam-5015	83	7	al	al	PROPN
ejpam-5015	83	8	sagheer	sagheer	NOUN
ejpam-5015	84	1	[	[	X
ejpam-5015	84	2	8	8	NUM
ejpam-5015	84	3	]	]	PUNCT
ejpam-5015	84	4	,	,	PUNCT
ejpam-5015	84	5	wolfe	wolfe	PROPN
ejpam-5015	85	1	[	[	X
ejpam-5015	85	2	27	27	NUM
ejpam-5015	85	3	]	]	PUNCT
ejpam-5015	85	4	,	,	PUNCT
ejpam-5015	85	5	kohlschmidt	kohlschmidt	PROPN
ejpam-5015	85	6	et	et	PROPN
ejpam-5015	85	7	al	al	PROPN
ejpam-5015	85	8	.	.	PUNCT
ejpam-5015	86	1	[	[	X
ejpam-5015	86	2	20	20	NUM
ejpam-5015	86	3	]	]	PUNCT
ejpam-5015	86	4	,	,	PUNCT
ejpam-5015	86	5	and	and	CCONJ
ejpam-5015	86	6	al	al	PROPN
ejpam-5015	86	7	-	-	PUNCT
ejpam-5015	86	8	saleh	saleh	PROPN
ejpam-5015	86	9	and	and	CCONJ
ejpam-5015	86	10	al	al	PROPN
ejpam-5015	86	11	-	-	PUNCT
ejpam-5015	86	12	shrafa	shrafa	NOUN
ejpam-5015	87	1	[	[	X
ejpam-5015	87	2	3	3	NUM
ejpam-5015	87	3	]	]	PUNCT
ejpam-5015	87	4	.	.	PUNCT
ejpam-5015	88	1	alodat	alodat	PROPN
ejpam-5015	88	2	et	et	PROPN
ejpam-5015	88	3	al	al	PROPN
ejpam-5015	89	1	[	[	X
ejpam-5015	89	2	6	6	NUM
ejpam-5015	89	3	]	]	PUNCT
ejpam-5015	89	4	initially	initially	ADV
ejpam-5015	89	5	proposed	propose	VERB
ejpam-5015	89	6	the	the	DET
ejpam-5015	89	7	application	application	NOUN
ejpam-5015	89	8	of	of	ADP
ejpam-5015	89	9	bayesian	bayesian	NOUN
ejpam-5015	89	10	statistics	statistic	NOUN
ejpam-5015	89	11	to	to	PART
ejpam-5015	89	12	rss	rss	VERB
ejpam-5015	89	13	,	,	PUNCT
ejpam-5015	89	14	and	and	CCONJ
ejpam-5015	89	15	al	al	PROPN
ejpam-5015	89	16	-	-	PUNCT
ejpam-5015	89	17	hamide	hamide	NOUN
ejpam-5015	89	18	et	et	PROPN
ejpam-5015	89	19	al	al	PROPN
ejpam-5015	89	20	.	.	PUNCT
ejpam-5015	90	1	[	[	X
ejpam-5015	90	2	4	4	NUM
ejpam-5015	90	3	]	]	PUNCT
ejpam-5015	90	4	further	far	ADV
ejpam-5015	90	5	studied	study	VERB
ejpam-5015	90	6	bayesian	bayesian	NOUN
ejpam-5015	90	7	inference	inference	NOUN
ejpam-5015	90	8	for	for	ADP
ejpam-5015	90	9	the	the	DET
ejpam-5015	90	10	linear	linear	PROPN
ejpam-5015	90	11	regression	regression	NOUN
ejpam-5015	90	12	model	model	NOUN
ejpam-5015	90	13	,	,	PUNCT
ejpam-5015	90	14	assuming	assume	VERB
ejpam-5015	90	15	a	a	DET
ejpam-5015	90	16	prior	prior	ADJ
ejpam-5015	90	17	distribution	distribution	NOUN
ejpam-5015	90	18	for	for	ADP
ejpam-5015	90	19	the	the	DET
ejpam-5015	90	20	regression	regression	NOUN
ejpam-5015	90	21	parameters	parameter	NOUN
ejpam-5015	90	22	following	follow	VERB
ejpam-5015	90	23	the	the	DET
ejpam-5015	90	24	alpha	alpha	NOUN
ejpam-5015	90	25	-	-	PUNCT
ejpam-5015	90	26	skew	skew	NOUN
ejpam-5015	90	27	-	-	PUNCT
ejpam-5015	90	28	normal	normal	ADJ
ejpam-5015	90	29	distribution	distribution	NOUN
ejpam-5015	90	30	.	.	PUNCT
ejpam-5015	91	1	muttlak	muttlak	ADJ
ejpam-5015	91	2	[	[	X
ejpam-5015	91	3	23	23	NUM
ejpam-5015	91	4	]	]	PUNCT
ejpam-5015	91	5	introduced	introduce	VERB
ejpam-5015	91	6	median	median	NOUN
ejpam-5015	91	7	ranked	rank	VERB
ejpam-5015	91	8	set	set	ADJ
ejpam-5015	91	9	sampling	sampling	NOUN
ejpam-5015	91	10	(	(	PUNCT
ejpam-5015	91	11	mrss	mrss	NOUN
ejpam-5015	91	12	)	)	PUNCT
ejpam-5015	91	13	,	,	PUNCT
ejpam-5015	91	14	which	which	PRON
ejpam-5015	91	15	involves	involve	VERB
ejpam-5015	91	16	quantifying	quantify	VERB
ejpam-5015	91	17	the	the	DET
ejpam-5015	91	18	median	median	NOUN
ejpam-5015	91	19	of	of	ADP
ejpam-5015	91	20	each	each	PRON
ejpam-5015	91	21	set	set	VERB
ejpam-5015	91	22	from	from	ADP
ejpam-5015	91	23	the	the	DET
ejpam-5015	91	24	aforementioned	aforementioned	ADJ
ejpam-5015	91	25	m	m	NOUN
ejpam-5015	91	26	sets	set	NOUN
ejpam-5015	91	27	.	.	PUNCT
ejpam-5015	92	1	within	within	ADP
ejpam-5015	92	2	each	each	DET
ejpam-5015	92	3	group	group	NOUN
ejpam-5015	92	4	,	,	PUNCT
ejpam-5015	92	5	the	the	DET
ejpam-5015	92	6	units	unit	NOUN
ejpam-5015	92	7	are	be	AUX
ejpam-5015	92	8	ranked	rank	VERB
ejpam-5015	92	9	after	after	ADP
ejpam-5015	92	10	randomly	randomly	ADV
ejpam-5015	92	11	distributing	distribute	VERB
ejpam-5015	92	12	the	the	DET
ejpam-5015	92	13	chosen	choose	VERB
ejpam-5015	92	14	m2	m2	PROPN
ejpam-5015	92	15	units	unit	NOUN
ejpam-5015	92	16	into	into	ADP
ejpam-5015	92	17	m	m	PROPN
ejpam-5015	92	18	sets	set	NOUN
ejpam-5015	92	19	of	of	ADP
ejpam-5015	92	20	size	size	NOUN
ejpam-5015	92	21	m.	m.	NOUN
ejpam-5015	92	22	if	if	SCONJ
ejpam-5015	92	23	m	m	NOUN
ejpam-5015	92	24	is	be	AUX
ejpam-5015	92	25	odd	odd	ADJ
ejpam-5015	92	26	,	,	PUNCT
ejpam-5015	92	27	the	the	DET
ejpam-5015	92	28	m+1	m+1	NUM
ejpam-5015	92	29	2	2	NUM
ejpam-5015	92	30	th	th	NUM
ejpam-5015	92	31	smallest	small	ADJ
ejpam-5015	92	32	rank	rank	NOUN
ejpam-5015	92	33	unit	unit	NOUN
ejpam-5015	92	34	(	(	PUNCT
ejpam-5015	92	35	median	median	PROPN
ejpam-5015	92	36	)	)	PUNCT
ejpam-5015	92	37	is	be	AUX
ejpam-5015	92	38	selected	select	VERB
ejpam-5015	92	39	from	from	ADP
ejpam-5015	92	40	each	each	DET
ejpam-5015	92	41	set	set	NOUN
ejpam-5015	92	42	,	,	PUNCT
ejpam-5015	92	43	whereas	whereas	SCONJ
ejpam-5015	92	44	if	if	SCONJ
ejpam-5015	92	45	m	m	NOUN
ejpam-5015	92	46	is	be	AUX
ejpam-5015	92	47	even	even	ADV
ejpam-5015	92	48	,	,	PUNCT
ejpam-5015	92	49	the	the	DET
ejpam-5015	92	50	m	m	PROPN
ejpam-5015	92	51	2	2	NUM
ejpam-5015	92	52	th	th	NUM
ejpam-5015	92	53	smallest	small	ADJ
ejpam-5015	92	54	rank	rank	NOUN
ejpam-5015	92	55	unit	unit	NOUN
ejpam-5015	92	56	is	be	AUX
ejpam-5015	92	57	chosen	choose	VERB
ejpam-5015	92	58	from	from	ADP
ejpam-5015	92	59	the	the	DET
ejpam-5015	92	60	first	first	ADJ
ejpam-5015	92	61	m	m	ADJ
ejpam-5015	92	62	2	2	NUM
ejpam-5015	92	63	set	set	NOUN
ejpam-5015	92	64	.	.	PUNCT
ejpam-5015	93	1	this	this	DET
ejpam-5015	93	2	process	process	NOUN
ejpam-5015	93	3	is	be	AUX
ejpam-5015	93	4	repeated	repeat	VERB
ejpam-5015	93	5	r	r	NOUN
ejpam-5015	93	6	times	time	NOUN
ejpam-5015	93	7	until	until	SCONJ
ejpam-5015	93	8	a	a	DET
ejpam-5015	93	9	sample	sample	NOUN
ejpam-5015	93	10	of	of	ADP
ejpam-5015	93	11	size	size	NOUN
ejpam-5015	93	12	n	n	PROPN
ejpam-5015	93	13	=	=	PROPN
ejpam-5015	93	14	rm	rm	PROPN
ejpam-5015	93	15	is	be	AUX
ejpam-5015	93	16	obtained	obtain	VERB
ejpam-5015	93	17	.	.	PUNCT
ejpam-5015	94	1	alodat	alodat	PROPN
ejpam-5015	94	2	et	et	PROPN
ejpam-5015	94	3	al	al	PROPN
ejpam-5015	94	4	.	.	PUNCT
ejpam-5015	95	1	[	[	X
ejpam-5015	95	2	6	6	NUM
ejpam-5015	95	3	]	]	PUNCT
ejpam-5015	95	4	analyzed	analyze	VERB
ejpam-5015	95	5	parameter	parameter	NOUN
ejpam-5015	95	6	estimators	estimator	NOUN
ejpam-5015	95	7	for	for	ADP
ejpam-5015	95	8	a	a	DET
ejpam-5015	95	9	simple	simple	ADJ
ejpam-5015	95	10	linear	linear	NOUN
ejpam-5015	95	11	regression	regression	NOUN
ejpam-5015	95	12	model	model	NOUN
ejpam-5015	95	13	using	use	VERB
ejpam-5015	95	14	the	the	DET
ejpam-5015	95	15	mrss	mrss	ADJ
ejpam-5015	95	16	scheme	scheme	NOUN
ejpam-5015	95	17	.	.	PUNCT
ejpam-5015	96	1	additionally	additionally	ADV
ejpam-5015	96	2	,	,	PUNCT
ejpam-5015	96	3	in	in	ADP
ejpam-5015	96	4	his	his	PRON
ejpam-5015	96	5	another	another	DET
ejpam-5015	96	6	article	article	NOUN
ejpam-5015	96	7	alodat	alodat	VERB
ejpam-5015	96	8	et	et	PROPN
ejpam-5015	96	9	al	al	PROPN
ejpam-5015	96	10	.	.	PUNCT
ejpam-5015	97	1	[	[	X
ejpam-5015	97	2	7	7	X
ejpam-5015	97	3	]	]	PUNCT
ejpam-5015	97	4	discussed	discuss	VERB
ejpam-5015	97	5	the	the	DET
ejpam-5015	97	6	large	large	ADJ
ejpam-5015	97	7	sample	sample	NOUN
ejpam-5015	97	8	properties	property	NOUN
ejpam-5015	97	9	of	of	ADP
ejpam-5015	97	10	the	the	DET
ejpam-5015	97	11	parameter	parameter	NOUN
ejpam-5015	97	12	estimators	estimator	NOUN
ejpam-5015	97	13	for	for	ADP
ejpam-5015	97	14	simple	simple	ADJ
ejpam-5015	97	15	linear	linear	ADJ
ejpam-5015	97	16	regression	regression	NOUN
ejpam-5015	97	17	based	base	VERB
ejpam-5015	97	18	on	on	ADP
ejpam-5015	97	19	the	the	DET
ejpam-5015	97	20	mrss	mrss	PROPN
ejpam-5015	97	21	design	design	NOUN
ejpam-5015	97	22	.	.	PUNCT
ejpam-5015	98	1	in	in	ADP
ejpam-5015	98	2	a	a	DET
ejpam-5015	98	3	study	study	NOUN
ejpam-5015	98	4	by	by	ADP
ejpam-5015	98	5	al	al	PROPN
ejpam-5015	98	6	-	-	PUNCT
ejpam-5015	98	7	hadhrami	hadhrami	PROPN
ejpam-5015	98	8	et	et	PROPN
ejpam-5015	98	9	al	al	PROPN
ejpam-5015	98	10	.	.	PUNCT
ejpam-5015	99	1	[	[	X
ejpam-5015	99	2	1	1	NUM
ejpam-5015	99	3	]	]	PUNCT
ejpam-5015	99	4	,	,	PUNCT
ejpam-5015	99	5	it	it	PRON
ejpam-5015	99	6	was	be	AUX
ejpam-5015	99	7	demonstrated	demonstrate	VERB
ejpam-5015	99	8	that	that	SCONJ
ejpam-5015	99	9	bayesian	bayesian	NOUN
ejpam-5015	99	10	estimation	estimation	NOUN
ejpam-5015	99	11	of	of	ADP
ejpam-5015	99	12	the	the	DET
ejpam-5015	99	13	mean	mean	NOUN
ejpam-5015	99	14	of	of	ADP
ejpam-5015	99	15	a	a	DET
ejpam-5015	99	16	normal	normal	ADJ
ejpam-5015	99	17	distribution	distribution	NOUN
ejpam-5015	99	18	using	use	VERB
ejpam-5015	99	19	moving	move	VERB
ejpam-5015	99	20	extreme	extreme	ADJ
ejpam-5015	99	21	ranked	rank	VERB
ejpam-5015	99	22	set	set	NOUN
ejpam-5015	99	23	sampling	sampling	NOUN
ejpam-5015	99	24	is	be	AUX
ejpam-5015	99	25	more	more	ADV
ejpam-5015	99	26	efficient	efficient	ADJ
ejpam-5015	99	27	than	than	ADP
ejpam-5015	99	28	the	the	DET
ejpam-5015	99	29	frequentist	frequentist	NOUN
ejpam-5015	99	30	approach	approach	NOUN
ejpam-5015	99	31	of	of	ADP
ejpam-5015	99	32	simple	simple	ADJ
ejpam-5015	99	33	random	random	ADJ
ejpam-5015	99	34	sampling	sampling	NOUN
ejpam-5015	99	35	(	(	PUNCT
ejpam-5015	99	36	srs	srs	PROPN
ejpam-5015	99	37	)	)	PUNCT
ejpam-5015	99	38	.	.	PUNCT
ejpam-5015	100	1	hassan	hassan	PROPN
ejpam-5015	100	2	[	[	X
ejpam-5015	100	3	13	13	NUM
ejpam-5015	100	4	]	]	PUNCT
ejpam-5015	100	5	obtained	obtain	VERB
ejpam-5015	100	6	the	the	DET
ejpam-5015	100	7	maximum	maximum	ADJ
ejpam-5015	100	8	likelihood	likelihood	NOUN
ejpam-5015	100	9	and	and	CCONJ
ejpam-5015	100	10	bayesian	bayesian	NOUN
ejpam-5015	100	11	estimators	estimator	NOUN
ejpam-5015	100	12	of	of	ADP
ejpam-5015	100	13	shape	shape	NOUN
ejpam-5015	100	14	and	and	CCONJ
ejpam-5015	100	15	scale	scale	NOUN
ejpam-5015	100	16	parameters	parameter	NOUN
ejpam-5015	100	17	of	of	ADP
ejpam-5015	100	18	the	the	DET
ejpam-5015	100	19	exponentiated	exponentiated	ADJ
ejpam-5015	100	20	exponential	exponential	ADJ
ejpam-5015	100	21	distribution	distribution	NOUN
ejpam-5015	100	22	based	base	VERB
ejpam-5015	100	23	on	on	ADP
ejpam-5015	100	24	srs	srs	PROPN
ejpam-5015	100	25	and	and	CCONJ
ejpam-5015	100	26	rss	rss	PROPN
ejpam-5015	100	27	.	.	PUNCT
ejpam-5015	101	1	li	li	PROPN
ejpam-5015	101	2	and	and	CCONJ
ejpam-5015	101	3	balakrshnan	balakrshnan	PROPN
ejpam-5015	102	1	[	[	X
ejpam-5015	102	2	21	21	NUM
ejpam-5015	102	3	]	]	PUNCT
ejpam-5015	102	4	developed	develop	VERB
ejpam-5015	102	5	the	the	DET
ejpam-5015	102	6	best	good	ADJ
ejpam-5015	102	7	linear	linear	ADJ
ejpam-5015	102	8	unbiased	unbiased	ADJ
ejpam-5015	102	9	estimators	estimator	NOUN
ejpam-5015	102	10	for	for	ADP
ejpam-5015	102	11	parameters	parameter	NOUN
ejpam-5015	102	12	of	of	ADP
ejpam-5015	102	13	a	a	DET
ejpam-5015	102	14	simple	simple	ADJ
ejpam-5015	102	15	linear	linear	NOUN
ejpam-5015	102	16	regression	regression	NOUN
ejpam-5015	102	17	model	model	NOUN
ejpam-5015	102	18	using	use	VERB
ejpam-5015	102	19	ordered	order	VERB
ejpam-5015	102	20	rss	rss	NOUN
ejpam-5015	102	21	.	.	PUNCT
ejpam-5015	103	1	haq	haq	PROPN
ejpam-5015	103	2	et	et	PROPN
ejpam-5015	103	3	al	al	PROPN
ejpam-5015	103	4	.	.	PUNCT
ejpam-5015	104	1	[	[	X
ejpam-5015	104	2	12	12	NUM
ejpam-5015	104	3	]	]	PUNCT
ejpam-5015	104	4	investigated	investigate	VERB
ejpam-5015	104	5	the	the	DET
ejpam-5015	104	6	best	good	ADJ
ejpam-5015	104	7	linear	linear	ADJ
ejpam-5015	104	8	unbiased	unbiased	ADJ
ejpam-5015	104	9	estimators	estimator	NOUN
ejpam-5015	104	10	based	base	VERB
ejpam-5015	104	11	on	on	ADP
ejpam-5015	104	12	double	double	ADJ
ejpam-5015	104	13	rss	rss	NOUN
ejpam-5015	104	14	and	and	CCONJ
ejpam-5015	104	15	ordered	order	VERB
ejpam-5015	104	16	double	double	ADJ
ejpam-5015	104	17	ranked	rank	VERB
ejpam-5015	104	18	set	set	NOUN
ejpam-5015	104	19	sampling	sampling	NOUN
ejpam-5015	104	20	(	(	PUNCT
ejpam-5015	104	21	drss	drss	ADJ
ejpam-5015	104	22	)	)	PUNCT
ejpam-5015	104	23	for	for	ADP
ejpam-5015	104	24	the	the	DET
ejpam-5015	104	25	simple	simple	ADJ
ejpam-5015	104	26	linear	linear	ADJ
ejpam-5015	104	27	regression	regression	NOUN
ejpam-5015	104	28	model	model	NOUN
ejpam-5015	104	29	with	with	ADP
ejpam-5015	104	30	replicated	replicate	VERB
ejpam-5015	104	31	observations	observation	NOUN
ejpam-5015	104	32	.	.	PUNCT
ejpam-5015	105	1	yao	yao	PROPN
ejpam-5015	105	2	et	et	PROPN
ejpam-5015	105	3	al	al	PROPN
ejpam-5015	105	4	.	.	PUNCT
ejpam-5015	106	1	[	[	X
ejpam-5015	106	2	28	28	NUM
ejpam-5015	106	3	]	]	PUNCT
ejpam-5015	106	4	recently	recently	ADV
ejpam-5015	106	5	derived	derive	VERB
ejpam-5015	106	6	the	the	DET
ejpam-5015	106	7	best	good	ADJ
ejpam-5015	106	8	linear	linear	ADJ
ejpam-5015	106	9	unbiased	unbiased	ADJ
ejpam-5015	106	10	estimators	estimator	NOUN
ejpam-5015	106	11	for	for	ADP
ejpam-5015	106	12	simple	simple	ADJ
ejpam-5015	106	13	linear	linear	ADJ
ejpam-5015	106	14	regression	regression	NOUN
ejpam-5015	106	15	based	base	VERB
ejpam-5015	106	16	on	on	ADP
ejpam-5015	106	17	moving	move	VERB
ejpam-5015	106	18	extremes	extreme	NOUN
ejpam-5015	106	19	rss	rss	PROPN
ejpam-5015	106	20	,	,	PUNCT
ejpam-5015	106	21	which	which	PRON
ejpam-5015	106	22	were	be	AUX
ejpam-5015	106	23	found	find	VERB
ejpam-5015	106	24	to	to	PART
ejpam-5015	106	25	be	be	AUX
ejpam-5015	106	26	more	more	ADV
ejpam-5015	106	27	efficient	efficient	ADJ
ejpam-5015	106	28	than	than	ADP
ejpam-5015	106	29	the	the	DET
ejpam-5015	106	30	estimators	estimator	NOUN
ejpam-5015	106	31	obtained	obtain	VERB
ejpam-5015	106	32	under	under	ADP
ejpam-5015	106	33	srs	srs	PROPN
ejpam-5015	106	34	.	.	PROPN
ejpam-5015	107	1	in	in	ADP
ejpam-5015	107	2	a	a	DET
ejpam-5015	107	3	study	study	NOUN
ejpam-5015	107	4	by	by	ADP
ejpam-5015	107	5	sazak	sazak	NOUN
ejpam-5015	107	6	and	and	CCONJ
ejpam-5015	107	7	ozel	ozel	ADJ
ejpam-5015	107	8	[	[	X
ejpam-5015	107	9	25	25	NUM
ejpam-5015	107	10	]	]	PUNCT
ejpam-5015	107	11	,	,	PUNCT
ejpam-5015	107	12	the	the	DET
ejpam-5015	107	13	modified	modify	VERB
ejpam-5015	107	14	maximum	maximum	ADJ
ejpam-5015	107	15	likelihood	likelihood	NOUN
ejpam-5015	107	16	parameter	parameter	NOUN
ejpam-5015	107	17	estimation	estimation	NOUN
ejpam-5015	107	18	of	of	ADP
ejpam-5015	107	19	the	the	DET
ejpam-5015	107	20	regression	regression	NOUN
ejpam-5015	107	21	model	model	NOUN
ejpam-5015	107	22	using	use	VERB
ejpam-5015	107	23	bivariate	bivariate	ADJ
ejpam-5015	107	24	mrss	mrss	NOUN
ejpam-5015	107	25	was	be	AUX
ejpam-5015	107	26	investigated	investigate	VERB
ejpam-5015	107	27	.	.	PUNCT
ejpam-5015	108	1	the	the	DET
ejpam-5015	108	2	obtained	obtain	VERB
ejpam-5015	108	3	estimators	estimator	NOUN
ejpam-5015	108	4	were	be	AUX
ejpam-5015	108	5	compared	compare	VERB
ejpam-5015	108	6	with	with	ADP
ejpam-5015	108	7	the	the	DET
ejpam-5015	108	8	least	least	ADJ
ejpam-5015	108	9	squares	square	NOUN
ejpam-5015	108	10	estimators	estimator	NOUN
ejpam-5015	108	11	based	base	VERB
ejpam-5015	108	12	on	on	ADP
ejpam-5015	108	13	mrss	mrss	NOUN
ejpam-5015	108	14	,	,	PUNCT
ejpam-5015	108	15	as	as	ADV
ejpam-5015	108	16	well	well	ADV
ejpam-5015	108	17	as	as	ADP
ejpam-5015	108	18	with	with	ADP
ejpam-5015	108	19	the	the	DET
ejpam-5015	108	20	modified	modified	ADJ
ejpam-5015	108	21	maximum	maximum	ADJ
ejpam-5015	108	22	likelihood	likelihood	NOUN
ejpam-5015	108	23	and	and	CCONJ
ejpam-5015	108	24	least	least	ADJ
ejpam-5015	108	25	squares	square	NOUN
ejpam-5015	108	26	estimators	estimator	NOUN
ejpam-5015	108	27	based	base	VERB
ejpam-5015	108	28	on	on	ADP
ejpam-5015	108	29	rss	rss	PROPN
ejpam-5015	108	30	.	.	PUNCT
ejpam-5015	109	1	when	when	SCONJ
ejpam-5015	109	2	estimating	estimate	VERB
ejpam-5015	109	3	the	the	DET
ejpam-5015	109	4	population	population	NOUN
ejpam-5015	109	5	mean	mean	VERB
ejpam-5015	109	6	under	under	ADP
ejpam-5015	109	7	symmetrical	symmetrical	ADJ
ejpam-5015	109	8	unimodal	unimodal	ADJ
ejpam-5015	109	9	distributions	distribution	NOUN
ejpam-5015	109	10	,	,	PUNCT
ejpam-5015	109	11	mei	mei	PROPN
ejpam-5015	110	1	.	.	PUNCT
ejpam-5015	110	2	nawajah	nawajah	PROPN
ejpam-5015	110	3	,	,	PUNCT
ejpam-5015	110	4	h.	h.	PROPN
ejpam-5015	110	5	kanj	kanj	PROPN
ejpam-5015	110	6	,	,	PUNCT
ejpam-5015	110	7	y.	y.	PROPN
ejpam-5015	110	8	kotb	kotb	PROPN
ejpam-5015	110	9	,	,	PUNCT
ejpam-5015	110	10	j.	j.	PROPN
ejpam-5015	110	11	hoxha	hoxha	PROPN
ejpam-5015	110	12	,	,	PUNCT
ejpam-5015	110	13	m.	m.	PROPN
ejpam-5015	110	14	alakkoumi	alakkoumi	PROPN
ejpam-5015	110	15	,	,	PUNCT
ejpam-5015	110	16	k.	k.	PROPN
ejpam-5015	111	1	jebreen	jebreen	PROPN
ejpam-5015	111	2	/	/	SYM
ejpam-5015	111	3	eur	eur	PROPN
ejpam-5015	111	4	.	.	PUNCT
ejpam-5015	112	1	j.	j.	PROPN
ejpam-5015	112	2	pure	pure	PROPN
ejpam-5015	112	3	appl	appl	PROPN
ejpam-5015	112	4	.	.	PROPN
ejpam-5015	112	5	math	math	PROPN
ejpam-5015	112	6	,	,	PUNCT
ejpam-5015	112	7	17	17	NUM
ejpam-5015	112	8	(	(	PUNCT
ejpam-5015	112	9	1	1	NUM
ejpam-5015	112	10	)	)	PUNCT
ejpam-5015	112	11	(	(	PUNCT
ejpam-5015	112	12	2024	2024	NUM
ejpam-5015	112	13	)	)	PUNCT
ejpam-5015	112	14	,	,	PUNCT
ejpam-5015	112	15	180	180	NUM
ejpam-5015	112	16	-	-	SYM
ejpam-5015	112	17	200	200	NUM
ejpam-5015	112	18	184	184	NUM
ejpam-5015	112	19	dian	dian	NOUN
ejpam-5015	112	20	ranked	rank	VERB
ejpam-5015	112	21	set	set	ADJ
ejpam-5015	112	22	sampling	sampling	NOUN
ejpam-5015	112	23	(	(	PUNCT
ejpam-5015	112	24	mrss	mrss	NOUN
ejpam-5015	112	25	)	)	PUNCT
ejpam-5015	112	26	,	,	PUNCT
ejpam-5015	112	27	a	a	DET
ejpam-5015	112	28	variation	variation	NOUN
ejpam-5015	112	29	of	of	ADP
ejpam-5015	112	30	rss	rss	NOUN
ejpam-5015	112	31	,	,	PUNCT
ejpam-5015	112	32	outperforms	outperform	VERB
ejpam-5015	112	33	classical	classical	ADJ
ejpam-5015	112	34	rss	rss	NOUN
ejpam-5015	113	1	[	[	X
ejpam-5015	113	2	23	23	NUM
ejpam-5015	113	3	]	]	PUNCT
ejpam-5015	113	4	.	.	PUNCT
ejpam-5015	114	1	numerous	numerous	ADJ
ejpam-5015	114	2	studies	study	NOUN
ejpam-5015	114	3	have	have	AUX
ejpam-5015	114	4	been	be	AUX
ejpam-5015	114	5	conducted	conduct	VERB
ejpam-5015	114	6	on	on	ADP
ejpam-5015	114	7	mrss	mrss	NOUN
ejpam-5015	114	8	and	and	CCONJ
ejpam-5015	114	9	its	its	PRON
ejpam-5015	114	10	uses	use	NOUN
ejpam-5015	114	11	[	[	X
ejpam-5015	114	12	9	9	NUM
ejpam-5015	114	13	,	,	PUNCT
ejpam-5015	114	14	11	11	NUM
ejpam-5015	114	15	]	]	PUNCT
ejpam-5015	114	16	.	.	PUNCT
ejpam-5015	115	1	however	however	ADV
ejpam-5015	115	2	,	,	PUNCT
ejpam-5015	115	3	in	in	ADP
ejpam-5015	115	4	the	the	DET
ejpam-5015	115	5	case	case	NOUN
ejpam-5015	115	6	of	of	ADP
ejpam-5015	115	7	asymmetric	asymmetric	ADJ
ejpam-5015	115	8	distributions	distribution	NOUN
ejpam-5015	115	9	,	,	PUNCT
ejpam-5015	115	10	mrss	mrss	PROPN
ejpam-5015	115	11	can	can	AUX
ejpam-5015	115	12	outperform	outperform	VERB
ejpam-5015	115	13	rss	rss	NOUN
ejpam-5015	115	14	.	.	PUNCT
ejpam-5015	116	1	moreover	moreover	ADV
ejpam-5015	116	2	,	,	PUNCT
ejpam-5015	116	3	mrss	mrss	PROPN
ejpam-5015	116	4	can	can	AUX
ejpam-5015	116	5	improve	improve	VERB
ejpam-5015	116	6	estimator	estimator	NOUN
ejpam-5015	116	7	efficiency	efficiency	NOUN
ejpam-5015	116	8	since	since	SCONJ
ejpam-5015	116	9	error	error	NOUN
ejpam-5015	116	10	terms	term	NOUN
ejpam-5015	116	11	in	in	ADP
ejpam-5015	116	12	regression	regression	NOUN
ejpam-5015	116	13	models	model	NOUN
ejpam-5015	116	14	generally	generally	ADV
ejpam-5015	116	15	have	have	VERB
ejpam-5015	116	16	a	a	DET
ejpam-5015	116	17	normal	normal	ADJ
ejpam-5015	116	18	distribution	distribution	NOUN
ejpam-5015	116	19	.	.	PUNCT
ejpam-5015	117	1	in	in	ADP
ejpam-5015	117	2	order	order	NOUN
ejpam-5015	117	3	to	to	PART
ejpam-5015	117	4	develop	develop	VERB
ejpam-5015	117	5	effective	effective	ADJ
ejpam-5015	117	6	estimators	estimator	NOUN
ejpam-5015	117	7	of	of	ADP
ejpam-5015	117	8	regression	regression	NOUN
ejpam-5015	117	9	model	model	NOUN
ejpam-5015	117	10	parameters	parameter	NOUN
ejpam-5015	117	11	,	,	PUNCT
ejpam-5015	117	12	the	the	DET
ejpam-5015	117	13	bayesian	bayesian	NOUN
ejpam-5015	117	14	regression	regression	NOUN
ejpam-5015	117	15	estimators	estimator	NOUN
ejpam-5015	117	16	were	be	AUX
ejpam-5015	117	17	examined	examine	VERB
ejpam-5015	117	18	in	in	ADP
ejpam-5015	117	19	this	this	DET
ejpam-5015	117	20	study	study	NOUN
ejpam-5015	117	21	utilizing	utilize	VERB
ejpam-5015	117	22	a	a	DET
ejpam-5015	117	23	median	median	NOUN
ejpam-5015	117	24	ranked	rank	VERB
ejpam-5015	117	25	set	set	NOUN
ejpam-5015	117	26	sample	sample	NOUN
ejpam-5015	117	27	.	.	PUNCT
ejpam-5015	118	1	3	3	X
ejpam-5015	118	2	.	.	NUM
ejpam-5015	118	3	proposed	propose	VERB
ejpam-5015	118	4	model	model	NOUN
ejpam-5015	118	5	this	this	DET
ejpam-5015	118	6	article	article	NOUN
ejpam-5015	118	7	focuses	focus	VERB
ejpam-5015	118	8	on	on	ADP
ejpam-5015	118	9	conducting	conduct	VERB
ejpam-5015	118	10	a	a	DET
ejpam-5015	118	11	bayesian	bayesian	NOUN
ejpam-5015	118	12	analysis	analysis	NOUN
ejpam-5015	118	13	of	of	ADP
ejpam-5015	118	14	the	the	DET
ejpam-5015	118	15	simple	simple	ADJ
ejpam-5015	118	16	linear	linear	PROPN
ejpam-5015	118	17	regression	regression	NOUN
ejpam-5015	118	18	model	model	NOUN
ejpam-5015	118	19	using	use	VERB
ejpam-5015	118	20	ranked	rank	VERB
ejpam-5015	118	21	set	set	ADJ
ejpam-5015	118	22	sampling	sampling	NOUN
ejpam-5015	118	23	(	(	PUNCT
ejpam-5015	118	24	rss	rss	NOUN
ejpam-5015	118	25	)	)	PUNCT
ejpam-5015	118	26	.	.	PUNCT
ejpam-5015	119	1	we	we	PRON
ejpam-5015	119	2	investigate	investigate	VERB
ejpam-5015	119	3	the	the	DET
ejpam-5015	119	4	estimation	estimation	NOUN
ejpam-5015	119	5	of	of	ADP
ejpam-5015	119	6	regression	regression	NOUN
ejpam-5015	119	7	parameters	parameter	NOUN
ejpam-5015	119	8	by	by	ADP
ejpam-5015	119	9	incorporating	incorporate	VERB
ejpam-5015	119	10	a	a	DET
ejpam-5015	119	11	prior	prior	ADJ
ejpam-5015	119	12	distribution	distribution	NOUN
ejpam-5015	119	13	.	.	PUNCT
ejpam-5015	120	1	equation	equation	NOUN
ejpam-5015	120	2	5	5	NUM
ejpam-5015	120	3	represents	represent	VERB
ejpam-5015	120	4	the	the	DET
ejpam-5015	120	5	modified	modify	VERB
ejpam-5015	120	6	simple	simple	ADJ
ejpam-5015	120	7	linear	linear	ADJ
ejpam-5015	120	8	regression	regression	NOUN
ejpam-5015	120	9	model	model	NOUN
ejpam-5015	120	10	defined	define	VERB
ejpam-5015	120	11	by	by	ADP
ejpam-5015	120	12	equation	equation	NOUN
ejpam-5015	120	13	2	2	NUM
ejpam-5015	120	14	,	,	PUNCT
ejpam-5015	120	15	while	while	SCONJ
ejpam-5015	120	16	taking	take	VERB
ejpam-5015	120	17	sampling	sample	VERB
ejpam-5015	120	18	process	process	NOUN
ejpam-5015	120	19	into	into	ADP
ejpam-5015	120	20	consideration	consideration	NOUN
ejpam-5015	120	21	.	.	PUNCT
ejpam-5015	121	1	yij	yij	NOUN
ejpam-5015	121	2	=	=	SYM
ejpam-5015	121	3	β0	β0	PROPN
ejpam-5015	122	1	+	+	CCONJ
ejpam-5015	122	2	β1xij	β1xij	PROPN
ejpam-5015	123	1	+	+	CCONJ
ejpam-5015	123	2	ϵij	ϵij	NOUN
ejpam-5015	123	3	(	(	PUNCT
ejpam-5015	123	4	5	5	NUM
ejpam-5015	123	5	)	)	PUNCT
ejpam-5015	123	6	where	where	SCONJ
ejpam-5015	123	7	1	1	NUM
ejpam-5015	123	8	≤	≤	NUM
ejpam-5015	123	9	i	i	NOUN
ejpam-5015	123	10	≤	≤	ADJ
ejpam-5015	123	11	r	r	NOUN
ejpam-5015	123	12	and	and	CCONJ
ejpam-5015	123	13	1	1	NUM
ejpam-5015	123	14	≤	≤	NUM
ejpam-5015	123	15	j	j	PROPN
ejpam-5015	123	16	≤	≤	PROPN
ejpam-5015	123	17	n	n	CCONJ
ejpam-5015	123	18	(	(	PUNCT
ejpam-5015	123	19	6	6	NUM
ejpam-5015	123	20	)	)	PUNCT
ejpam-5015	123	21	where	where	SCONJ
ejpam-5015	123	22	r	r	NOUN
ejpam-5015	123	23	is	be	AUX
ejpam-5015	123	24	the	the	DET
ejpam-5015	123	25	iteration	iteration	NOUN
ejpam-5015	123	26	number	number	NOUN
ejpam-5015	123	27	of	of	ADP
ejpam-5015	123	28	the	the	DET
ejpam-5015	123	29	optimization	optimization	NOUN
ejpam-5015	123	30	process	process	NOUN
ejpam-5015	123	31	,	,	PUNCT
ejpam-5015	123	32	and	and	CCONJ
ejpam-5015	123	33	n	n	PRON
ejpam-5015	123	34	is	be	AUX
ejpam-5015	123	35	the	the	DET
ejpam-5015	123	36	group	group	NOUN
ejpam-5015	123	37	size	size	NOUN
ejpam-5015	123	38	.	.	PUNCT
ejpam-5015	124	1	the	the	DET
ejpam-5015	124	2	group	group	NOUN
ejpam-5015	124	3	size	size	NOUN
ejpam-5015	124	4	n	n	PROPN
ejpam-5015	124	5	=	=	SYM
ejpam-5015	124	6	2m−	2m−	PROPN
ejpam-5015	124	7	1	1	NUM
ejpam-5015	124	8	where	where	SCONJ
ejpam-5015	124	9	m	m	PROPN
ejpam-5015	124	10	is	be	AUX
ejpam-5015	124	11	the	the	DET
ejpam-5015	124	12	number	number	NOUN
ejpam-5015	124	13	of	of	ADP
ejpam-5015	124	14	groups	group	NOUN
ejpam-5015	124	15	.	.	PUNCT
ejpam-5015	125	1	in	in	ADP
ejpam-5015	125	2	each	each	DET
ejpam-5015	125	3	group	group	NOUN
ejpam-5015	125	4	,	,	PUNCT
ejpam-5015	125	5	we	we	PRON
ejpam-5015	125	6	have	have	VERB
ejpam-5015	125	7	an	an	DET
ejpam-5015	125	8	odd	odd	ADJ
ejpam-5015	125	9	number	number	NOUN
ejpam-5015	125	10	of	of	ADP
ejpam-5015	125	11	samples	sample	NOUN
ejpam-5015	125	12	,	,	PUNCT
ejpam-5015	125	13	that	that	PRON
ejpam-5015	125	14	increases	increase	VERB
ejpam-5015	125	15	linearly	linearly	ADV
ejpam-5015	125	16	with	with	ADP
ejpam-5015	125	17	the	the	DET
ejpam-5015	125	18	number	number	NOUN
ejpam-5015	125	19	of	of	ADP
ejpam-5015	125	20	groups	group	NOUN
ejpam-5015	125	21	.	.	PUNCT
ejpam-5015	126	1	ϵij	ϵij	NOUN
ejpam-5015	126	2	is	be	AUX
ejpam-5015	126	3	the	the	DET
ejpam-5015	126	4	error	error	NOUN
ejpam-5015	126	5	for	for	ADP
ejpam-5015	126	6	group	group	NOUN
ejpam-5015	126	7	i	i	PRON
ejpam-5015	126	8	and	and	CCONJ
ejpam-5015	126	9	data	datum	NOUN
ejpam-5015	126	10	sample	sample	NOUN
ejpam-5015	126	11	j.	j.	PROPN
ejpam-5015	126	12	the	the	DET
ejpam-5015	126	13	normal	normal	ADJ
ejpam-5015	126	14	distribution	distribution	NOUN
ejpam-5015	126	15	ℵ(µ	ℵ(µ	PROPN
ejpam-5015	126	16	,	,	PUNCT
ejpam-5015	126	17	σ2	σ2	NOUN
ejpam-5015	126	18	)	)	PUNCT
ejpam-5015	126	19	with	with	ADP
ejpam-5015	126	20	mean	mean	NOUN
ejpam-5015	126	21	µ	µ	X
ejpam-5015	126	22	=	=	SYM
ejpam-5015	126	23	0	0	NUM
ejpam-5015	126	24	and	and	CCONJ
ejpam-5015	126	25	standard	standard	ADJ
ejpam-5015	126	26	deviation	deviation	NOUN
ejpam-5015	126	27	of	of	ADP
ejpam-5015	126	28	σ	σ	PROPN
ejpam-5015	126	29	is	be	AUX
ejpam-5015	126	30	used	use	VERB
ejpam-5015	126	31	to	to	PART
ejpam-5015	126	32	calculate	calculate	VERB
ejpam-5015	126	33	the	the	DET
ejpam-5015	126	34	error	error	NOUN
ejpam-5015	126	35	ϵ.	ϵ.	NOUN
ejpam-5015	126	36	β0	β0	PROPN
ejpam-5015	126	37	is	be	AUX
ejpam-5015	126	38	the	the	DET
ejpam-5015	126	39	interception	interception	NOUN
ejpam-5015	126	40	and	and	CCONJ
ejpam-5015	126	41	β1	β1	PROPN
ejpam-5015	126	42	is	be	AUX
ejpam-5015	126	43	the	the	DET
ejpam-5015	126	44	slope	slope	NOUN
ejpam-5015	126	45	and	and	CCONJ
ejpam-5015	126	46	both	both	PRON
ejpam-5015	126	47	are	be	AUX
ejpam-5015	126	48	unknown	unknown	ADJ
ejpam-5015	126	49	parameters	parameter	NOUN
ejpam-5015	126	50	that	that	PRON
ejpam-5015	126	51	need	need	VERB
ejpam-5015	126	52	to	to	PART
ejpam-5015	126	53	be	be	AUX
ejpam-5015	126	54	found	find	VERB
ejpam-5015	126	55	through	through	ADP
ejpam-5015	126	56	the	the	DET
ejpam-5015	126	57	regression	regression	NOUN
ejpam-5015	126	58	process	process	NOUN
ejpam-5015	126	59	.	.	PUNCT
ejpam-5015	127	1	assume	assume	VERB
ejpam-5015	127	2	that	that	SCONJ
ejpam-5015	127	3	we	we	PRON
ejpam-5015	127	4	have	have	VERB
ejpam-5015	127	5	a	a	DET
ejpam-5015	127	6	performance	performance	NOUN
ejpam-5015	127	7	of	of	ADP
ejpam-5015	127	8	the	the	DET
ejpam-5015	127	9	mean	mean	NOUN
ejpam-5015	127	10	ranked	rank	VERB
ejpam-5015	127	11	set	set	ADJ
ejpam-5015	127	12	sampling	sampling	NOUN
ejpam-5015	127	13	(	(	PUNCT
ejpam-5015	127	14	mrss	mrss	NOUN
ejpam-5015	127	15	)	)	PUNCT
ejpam-5015	127	16	on	on	ADP
ejpam-5015	127	17	the	the	DET
ejpam-5015	127	18	variable	variable	NOUN
ejpam-5015	127	19	of	of	ADP
ejpam-5015	127	20	interest	interest	NOUN
ejpam-5015	127	21	and	and	CCONJ
ejpam-5015	127	22	yj(m	yj(m	NOUN
ejpam-5015	127	23	)	)	PUNCT
ejpam-5015	127	24	=	=	SYM
ejpam-5015	127	25	median(yj1	median(yj1	NOUN
ejpam-5015	127	26	,	,	PUNCT
ejpam-5015	127	27	.	.	PUNCT
ejpam-5015	127	28	.	.	PUNCT
ejpam-5015	127	29	.	.	PUNCT
ejpam-5015	128	1	,	,	PUNCT
ejpam-5015	128	2	yjn	yjn	NOUN
ejpam-5015	128	3	)	)	PUNCT
ejpam-5015	128	4	(	(	PUNCT
ejpam-5015	128	5	7	7	X
ejpam-5015	128	6	)	)	PUNCT
ejpam-5015	129	1	where	where	SCONJ
ejpam-5015	129	2	yj(m	yj(m	NOUN
ejpam-5015	129	3	)	)	PUNCT
ejpam-5015	129	4	is	be	AUX
ejpam-5015	129	5	the	the	DET
ejpam-5015	129	6	median	median	NOUN
ejpam-5015	129	7	of	of	ADP
ejpam-5015	129	8	group	group	PROPN
ejpam-5015	129	9	m	m	PROPN
ejpam-5015	129	10	in	in	ADP
ejpam-5015	129	11	iteration	iteration	NOUN
ejpam-5015	129	12	j.	j.	PROPN
ejpam-5015	130	1	the	the	DET
ejpam-5015	130	2	regression	regression	NOUN
ejpam-5015	130	3	of	of	ADP
ejpam-5015	130	4	y	y	PROPN
ejpam-5015	130	5	′s	′s	PROPN
ejpam-5015	130	6	j(m	j(m	PROPN
ejpam-5015	130	7	)	)	PUNCT
ejpam-5015	130	8	on	on	ADP
ejpam-5015	130	9	x	x	X
ejpam-5015	130	10	′s	′s	PROPN
ejpam-5015	130	11	j	j	PROPN
ejpam-5015	130	12	can	can	AUX
ejpam-5015	130	13	be	be	AUX
ejpam-5015	130	14	written	write	VERB
ejpam-5015	130	15	as	as	SCONJ
ejpam-5015	130	16	follows	follow	VERB
ejpam-5015	130	17	:	:	PUNCT
ejpam-5015	130	18	yj(m	yj(m	NUM
ejpam-5015	130	19	)	)	PUNCT
ejpam-5015	130	20	=	=	SYM
ejpam-5015	130	21	b0	b0	NOUN
ejpam-5015	130	22	+	+	NOUN
ejpam-5015	130	23	b1xj(m	b1xj(m	PROPN
ejpam-5015	130	24	)	)	PUNCT
ejpam-5015	130	25	+	+	NUM
ejpam-5015	130	26	ϵj(m	ϵj(m	NOUN
ejpam-5015	130	27	)	)	PUNCT
ejpam-5015	130	28	,	,	PUNCT
ejpam-5015	130	29	(	(	PUNCT
ejpam-5015	130	30	8)	8)	NUM
ejpam-5015	130	31	where	where	SCONJ
ejpam-5015	130	32	ϵj(m	ϵj(m	NOUN
ejpam-5015	130	33	)	)	PUNCT
ejpam-5015	130	34	=	=	SYM
ejpam-5015	130	35	median(ϵj1	median(ϵj1	PROPN
ejpam-5015	130	36	,	,	PUNCT
ejpam-5015	130	37	.	.	PUNCT
ejpam-5015	130	38	.	.	PUNCT
ejpam-5015	130	39	.	.	PUNCT
ejpam-5015	131	1	,	,	PUNCT
ejpam-5015	131	2	ϵjn	ϵjn	NOUN
ejpam-5015	131	3	)	)	PUNCT
ejpam-5015	131	4	(	(	PUNCT
ejpam-5015	131	5	9	9	X
ejpam-5015	131	6	)	)	PUNCT
ejpam-5015	131	7	it	it	PRON
ejpam-5015	131	8	can	can	AUX
ejpam-5015	131	9	be	be	AUX
ejpam-5015	131	10	noted	note	VERB
ejpam-5015	131	11	that	that	SCONJ
ejpam-5015	131	12	ϵj(m)′s	ϵj(m)′	NOUN
ejpam-5015	131	13	are	be	AUX
ejpam-5015	131	14	independently	independently	ADV
ejpam-5015	131	15	and	and	CCONJ
ejpam-5015	131	16	identically	identically	ADV
ejpam-5015	131	17	distribution	distribution	NOUN
ejpam-5015	131	18	(	(	PUNCT
ejpam-5015	131	19	iid	iid	NOUN
ejpam-5015	131	20	)	)	PUNCT
ejpam-5015	131	21	errors	error	NOUN
ejpam-5015	131	22	and	and	CCONJ
ejpam-5015	131	23	have	have	VERB
ejpam-5015	131	24	constant	constant	ADJ
ejpam-5015	131	25	variance	variance	NOUN
ejpam-5015	131	26	with	with	ADP
ejpam-5015	131	27	the	the	DET
ejpam-5015	131	28	probability	probability	NOUN
ejpam-5015	131	29	density	density	NOUN
ejpam-5015	131	30	function	function	NOUN
ejpam-5015	131	31	(	(	PUNCT
ejpam-5015	131	32	pdf	pdf	NOUN
ejpam-5015	131	33	):	):	PUNCT
ejpam-5015	131	34	f(ϵ	f(ϵ	PROPN
ejpam-5015	131	35	)	)	PUNCT
ejpam-5015	131	36	=	=	PRON
ejpam-5015	132	1	(	(	PUNCT
ejpam-5015	132	2	2m−	2m−	PROPN
ejpam-5015	132	3	1	1	NUM
ejpam-5015	132	4	)	)	PUNCT
ejpam-5015	132	5	!	!	PUNCT
ejpam-5015	133	1	(	(	PUNCT
ejpam-5015	133	2	m−	m−	PROPN
ejpam-5015	133	3	1)(m−	1)(m−	NUM
ejpam-5015	133	4	1	1	NUM
ejpam-5015	133	5	)	)	PUNCT
ejpam-5015	133	6	!	!	PUNCT
ejpam-5015	134	1	φ	φ	PROPN
ejpam-5015	134	2	(	(	PUNCT
ejpam-5015	134	3	ϵ	ϵ	PROPN
ejpam-5015	134	4	σ	σ	PROPN
ejpam-5015	134	5	)	)	PUNCT
ejpam-5015	134	6	m−1×	m−1×	PROPN
ejpam-5015	134	7	i.	i.	PROPN
ejpam-5015	134	8	nawajah	nawajah	PROPN
ejpam-5015	134	9	,	,	PUNCT
ejpam-5015	134	10	h.	h.	PROPN
ejpam-5015	134	11	kanj	kanj	PROPN
ejpam-5015	134	12	,	,	PUNCT
ejpam-5015	134	13	y.	y.	PROPN
ejpam-5015	134	14	kotb	kotb	PROPN
ejpam-5015	134	15	,	,	PUNCT
ejpam-5015	134	16	j.	j.	PROPN
ejpam-5015	134	17	hoxha	hoxha	PROPN
ejpam-5015	134	18	,	,	PUNCT
ejpam-5015	134	19	m.	m.	PROPN
ejpam-5015	134	20	alakkoumi	alakkoumi	PROPN
ejpam-5015	134	21	,	,	PUNCT
ejpam-5015	134	22	k.	k.	PROPN
ejpam-5015	134	23	jebreen	jebreen	PROPN
ejpam-5015	134	24	/	/	SYM
ejpam-5015	134	25	eur	eur	PROPN
ejpam-5015	134	26	.	.	PUNCT
ejpam-5015	135	1	j.	j.	PROPN
ejpam-5015	135	2	pure	pure	PROPN
ejpam-5015	135	3	appl	appl	PROPN
ejpam-5015	135	4	.	.	PROPN
ejpam-5015	135	5	math	math	PROPN
ejpam-5015	135	6	,	,	PUNCT
ejpam-5015	135	7	17	17	NUM
ejpam-5015	135	8	(	(	PUNCT
ejpam-5015	135	9	1	1	NUM
ejpam-5015	135	10	)	)	PUNCT
ejpam-5015	135	11	(	(	PUNCT
ejpam-5015	135	12	2024	2024	NUM
ejpam-5015	135	13	)	)	PUNCT
ejpam-5015	135	14	,	,	PUNCT
ejpam-5015	135	15	180	180	NUM
ejpam-5015	135	16	-	-	SYM
ejpam-5015	135	17	200	200	NUM
ejpam-5015	135	18	185	185	NUM
ejpam-5015	135	19	φ	φ	PROPN
ejpam-5015	135	20	(	(	PUNCT
ejpam-5015	135	21	−ϵ	−ϵ	PROPN
ejpam-5015	135	22	σ	σ	PROPN
ejpam-5015	135	23	)	)	PUNCT
ejpam-5015	135	24	m−1θ	m−1θ	PROPN
ejpam-5015	135	25	(	(	PUNCT
ejpam-5015	135	26	ϵ	ϵ	PROPN
ejpam-5015	135	27	σ	σ	PROPN
ejpam-5015	135	28	)	)	PUNCT
ejpam-5015	135	29	1	1	NUM
ejpam-5015	135	30	σ	σ	NOUN
ejpam-5015	135	31	;	;	PUNCT
ejpam-5015	135	32	with−∞	with−∞	PROPN
ejpam-5015	135	33	<	<	X
ejpam-5015	136	1	ϵ	ϵ	X
ejpam-5015	136	2	<	<	X
ejpam-5015	136	3	∞	∞	PROPN
ejpam-5015	136	4	(	(	PUNCT
ejpam-5015	136	5	10	10	NUM
ejpam-5015	136	6	)	)	PUNCT
ejpam-5015	136	7	where	where	SCONJ
ejpam-5015	136	8	θ	θ	PROPN
ejpam-5015	136	9	is	be	AUX
ejpam-5015	136	10	the	the	DET
ejpam-5015	136	11	pdf	pdf	NOUN
ejpam-5015	136	12	of	of	ADP
ejpam-5015	136	13	a	a	DET
ejpam-5015	136	14	standard	standard	ADJ
ejpam-5015	136	15	normal	normal	ADJ
ejpam-5015	136	16	random	random	ADJ
ejpam-5015	136	17	variable	variable	NOUN
ejpam-5015	136	18	(	(	PUNCT
ejpam-5015	136	19	i.e	i.e	PROPN
ejpam-5015	136	20	ℵ(0	ℵ(0	PROPN
ejpam-5015	136	21	,	,	PUNCT
ejpam-5015	136	22	1	1	NUM
ejpam-5015	136	23	)	)	PUNCT
ejpam-5015	136	24	)	)	PUNCT
ejpam-5015	136	25	and	and	CCONJ
ejpam-5015	136	26	φ	φ	X
ejpam-5015	136	27	a	a	DET
ejpam-5015	136	28	cumulative	cumulative	ADJ
ejpam-5015	136	29	standard	standard	ADJ
ejpam-5015	136	30	normal	normal	ADJ
ejpam-5015	136	31	distribution	distribution	NOUN
ejpam-5015	136	32	(	(	PUNCT
ejpam-5015	136	33	cdf	cdf	PROPN
ejpam-5015	136	34	)	)	PUNCT
ejpam-5015	136	35	.	.	PUNCT
ejpam-5015	137	1	utilizing	utilize	VERB
ejpam-5015	137	2	the	the	DET
ejpam-5015	137	3	mrss	mrss	ADJ
ejpam-5015	137	4	scheme	scheme	NOUN
ejpam-5015	137	5	,	,	PUNCT
ejpam-5015	137	6	the	the	DET
ejpam-5015	137	7	ordinary	ordinary	ADJ
ejpam-5015	137	8	least	least	ADJ
ejpam-5015	137	9	squares	square	NOUN
ejpam-5015	137	10	estimators	estimator	NOUN
ejpam-5015	137	11	of	of	ADP
ejpam-5015	137	12	β0	β0	NOUN
ejpam-5015	137	13	and	and	CCONJ
ejpam-5015	137	14	β1	β1	PROPN
ejpam-5015	137	15	can	can	AUX
ejpam-5015	137	16	be	be	AUX
ejpam-5015	137	17	easily	easily	ADV
ejpam-5015	137	18	obtained	obtain	VERB
ejpam-5015	137	19	as	as	SCONJ
ejpam-5015	137	20	follows	follow	VERB
ejpam-5015	137	21	:	:	PUNCT
ejpam-5015	138	1			NOUN
ejpam-5015	138	2	β̂0	β̂0	NOUN
ejpam-5015	138	3	m	m	VERB
ejpam-5015	138	4	=	=	ADJ
ejpam-5015	138	5	ȳm	ȳm	PROPN
ejpam-5015	138	6	−	−	PROPN
ejpam-5015	138	7	β̂1	β̂1	PROPN
ejpam-5015	138	8	m	m	VERB
ejpam-5015	138	9	x̄	x̄	NOUN
ejpam-5015	138	10	,	,	PUNCT
ejpam-5015	138	11	β̂0	β̂0	PROPN
ejpam-5015	138	12	m	m	VERB
ejpam-5015	138	13	=	=	NOUN
ejpam-5015	138	14	∑r	∑r	PROPN
ejpam-5015	138	15	j=1(yj(m)−ȳm	j=1(yj(m)−ȳm	PROPN
ejpam-5015	138	16	)	)	PUNCT
ejpam-5015	138	17	(	(	PUNCT
ejpam-5015	138	18	xj−x̄	xj−x̄	PROPN
ejpam-5015	138	19	)	)	PUNCT
ejpam-5015	138	20	sxx	sxx	NOUN
ejpam-5015	138	21	,	,	PUNCT
ejpam-5015	138	22	(	(	PUNCT
ejpam-5015	138	23	11	11	NUM
ejpam-5015	138	24	)	)	PUNCT
ejpam-5015	139	1	where	where	SCONJ
ejpam-5015	139	2	x̄	x̄	PRON
ejpam-5015	140	1	=	=	PUNCT
ejpam-5015	141	1	1	1	NUM
ejpam-5015	141	2	r	r	NOUN
ejpam-5015	141	3	r∑	r∑	NOUN
ejpam-5015	141	4	j=1	j=1	PROPN
ejpam-5015	141	5	xj	xj	PROPN
ejpam-5015	141	6	,	,	PUNCT
ejpam-5015	141	7	(	(	PUNCT
ejpam-5015	141	8	12	12	NUM
ejpam-5015	141	9	)	)	PUNCT
ejpam-5015	141	10	ȳm	ȳm	PROPN
ejpam-5015	141	11	=	=	SYM
ejpam-5015	141	12	1	1	NUM
ejpam-5015	141	13	r	r	NOUN
ejpam-5015	141	14	r∑	r∑	NOUN
ejpam-5015	141	15	j=1	j=1	NOUN
ejpam-5015	141	16	yj(m	yj(m	NOUN
ejpam-5015	141	17	)	)	PUNCT
ejpam-5015	141	18	,	,	PUNCT
ejpam-5015	141	19	(	(	PUNCT
ejpam-5015	141	20	13	13	NUM
ejpam-5015	141	21	)	)	PUNCT
ejpam-5015	141	22	and	and	CCONJ
ejpam-5015	141	23	sxx	sxx	NOUN
ejpam-5015	141	24	=	=	SYM
ejpam-5015	141	25	r∑	r∑	NOUN
ejpam-5015	141	26	j=1	j=1	NOUN
ejpam-5015	141	27	(	(	PUNCT
ejpam-5015	141	28	xj	xj	PROPN
ejpam-5015	141	29	−	−	PROPN
ejpam-5015	141	30	x̄)2	x̄)2	PROPN
ejpam-5015	141	31	(	(	PUNCT
ejpam-5015	141	32	14	14	NUM
ejpam-5015	141	33	)	)	PUNCT
ejpam-5015	141	34	in	in	ADP
ejpam-5015	141	35	this	this	DET
ejpam-5015	141	36	work	work	NOUN
ejpam-5015	141	37	,	,	PUNCT
ejpam-5015	141	38	the	the	DET
ejpam-5015	141	39	bayesian	bayesian	NOUN
ejpam-5015	141	40	estimator	estimator	NOUN
ejpam-5015	141	41	of	of	ADP
ejpam-5015	141	42	the	the	DET
ejpam-5015	141	43	parameters	parameter	NOUN
ejpam-5015	141	44	for	for	ADP
ejpam-5015	141	45	the	the	DET
ejpam-5015	141	46	simple	simple	ADJ
ejpam-5015	141	47	linear	linear	PROPN
ejpam-5015	141	48	regression	regression	NOUN
ejpam-5015	141	49	model	model	NOUN
ejpam-5015	141	50	is	be	AUX
ejpam-5015	141	51	obtained	obtain	VERB
ejpam-5015	141	52	employing	employ	VERB
ejpam-5015	141	53	mrss	mrss	NOUN
ejpam-5015	142	1	and	and	CCONJ
ejpam-5015	142	2	it	it	PRON
ejpam-5015	142	3	is	be	AUX
ejpam-5015	142	4	compared	compare	VERB
ejpam-5015	142	5	to	to	ADP
ejpam-5015	142	6	srs	srs	PROPN
ejpam-5015	142	7	setup	setup	NOUN
ejpam-5015	142	8	.	.	PUNCT
ejpam-5015	143	1	4	4	X
ejpam-5015	143	2	.	.	X
ejpam-5015	143	3	bayes	bayes	PROPN
ejpam-5015	143	4	estimator	estimator	NOUN
ejpam-5015	143	5	and	and	CCONJ
ejpam-5015	143	6	model	model	NOUN
ejpam-5015	143	7	selector	selector	NOUN
ejpam-5015	143	8	in	in	ADP
ejpam-5015	143	9	this	this	DET
ejpam-5015	143	10	section	section	NOUN
ejpam-5015	143	11	,	,	PUNCT
ejpam-5015	143	12	we	we	PRON
ejpam-5015	143	13	find	find	VERB
ejpam-5015	143	14	the	the	DET
ejpam-5015	143	15	bayes	bayes	PROPN
ejpam-5015	143	16	estimator	estimator	NOUN
ejpam-5015	143	17	of	of	ADP
ejpam-5015	143	18	each	each	DET
ejpam-5015	143	19	parameter	parameter	NOUN
ejpam-5015	143	20	in	in	ADP
ejpam-5015	143	21	the	the	DET
ejpam-5015	143	22	model	model	NOUN
ejpam-5015	143	23	defined	define	VERB
ejpam-5015	143	24	by	by	ADP
ejpam-5015	143	25	equation	equation	NOUN
ejpam-5015	143	26	5	5	NUM
ejpam-5015	143	27	.	.	PROPN
ejpam-5015	143	28	4.1	4.1	NUM
ejpam-5015	143	29	.	.	PUNCT
ejpam-5015	144	1	bayesian	bayesian	NOUN
ejpam-5015	144	2	model	model	NOUN
ejpam-5015	144	3	based	base	VERB
ejpam-5015	144	4	on	on	ADP
ejpam-5015	144	5	the	the	DET
ejpam-5015	144	6	likelihood	likelihood	NOUN
ejpam-5015	144	7	function	function	NOUN
ejpam-5015	144	8	and	and	CCONJ
ejpam-5015	144	9	the	the	DET
ejpam-5015	144	10	prior	prior	ADJ
ejpam-5015	144	11	distribution	distribution	NOUN
ejpam-5015	144	12	,	,	PUNCT
ejpam-5015	144	13	a	a	DET
ejpam-5015	144	14	bayesian	bayesian	NOUN
ejpam-5015	144	15	model	model	NOUN
ejpam-5015	144	16	is	be	AUX
ejpam-5015	144	17	described	describe	VERB
ejpam-5015	144	18	,	,	PUNCT
ejpam-5015	144	19	where	where	SCONJ
ejpam-5015	144	20	the	the	DET
ejpam-5015	144	21	likelihood	likelihood	NOUN
ejpam-5015	144	22	function	function	NOUN
ejpam-5015	144	23	is	be	AUX
ejpam-5015	144	24	the	the	DET
ejpam-5015	144	25	conditional	conditional	ADJ
ejpam-5015	144	26	distribution	distribution	NOUN
ejpam-5015	144	27	of	of	ADP
ejpam-5015	144	28	the	the	DET
ejpam-5015	144	29	response	response	NOUN
ejpam-5015	144	30	variable	variable	NOUN
ejpam-5015	144	31	,	,	PUNCT
ejpam-5015	144	32	given	give	VERB
ejpam-5015	144	33	all	all	DET
ejpam-5015	144	34	the	the	DET
ejpam-5015	144	35	parameters	parameter	NOUN
ejpam-5015	144	36	and	and	CCONJ
ejpam-5015	144	37	covariates	covariate	NOUN
ejpam-5015	144	38	.	.	PUNCT
ejpam-5015	145	1	we	we	PRON
ejpam-5015	145	2	have	have	VERB
ejpam-5015	145	3	the	the	DET
ejpam-5015	145	4	following	follow	VERB
ejpam-5015	145	5	prior	prior	ADJ
ejpam-5015	145	6	distribution	distribution	NOUN
ejpam-5015	145	7	of	of	ADP
ejpam-5015	145	8	each	each	DET
ejpam-5015	145	9	parameter	parameter	NOUN
ejpam-5015	145	10	,	,	PUNCT
ejpam-5015	145	11	(	(	PUNCT
ejpam-5015	145	12	β0	β0	ADV
ejpam-5015	145	13	,	,	PUNCT
ejpam-5015	145	14	β1	β1	PROPN
ejpam-5015	145	15	,	,	PUNCT
ejpam-5015	145	16	σ2	σ2	PROPN
ejpam-5015	145	17	):	):	PUNCT
ejpam-5015	145	18	m1	m1	PROPN
ejpam-5015	145	19	:	:	PUNCT
ejpam-5015	145	20			NOUN
ejpam-5015	145	21	yj(m	yj(m	NOUN
ejpam-5015	145	22	)	)	PUNCT
ejpam-5015	145	23	=	=	SYM
ejpam-5015	146	1	β0	β0	PROPN
ejpam-5015	146	2	+	+	CCONJ
ejpam-5015	146	3	β1xj	β1xj	PUNCT
ejpam-5015	146	4	+	+	CCONJ
ejpam-5015	146	5	ϵj(m	ϵj(m	NOUN
ejpam-5015	146	6	)	)	PUNCT
ejpam-5015	146	7	,	,	PUNCT
ejpam-5015	146	8	1	1	NUM
ejpam-5015	146	9	≤	≤	NUM
ejpam-5015	146	10	j	j	PROPN
ejpam-5015	147	1	≤	≤	NUM
ejpam-5015	147	2	r	r	NOUN
ejpam-5015	147	3	β0	β0	NOUN
ejpam-5015	147	4	∼	∼	NOUN
ejpam-5015	147	5	ℵ(a	ℵ(a	NOUN
ejpam-5015	147	6	,	,	PUNCT
ejpam-5015	147	7	b2	b2	NOUN
ejpam-5015	147	8	)	)	PUNCT
ejpam-5015	147	9	β1	β1	NOUN
ejpam-5015	147	10	∼	∼	NOUN
ejpam-5015	147	11	ℵ(δ	ℵ(δ	PROPN
ejpam-5015	147	12	,	,	PUNCT
ejpam-5015	147	13	g2	g2	PROPN
ejpam-5015	147	14	)	)	PUNCT
ejpam-5015	147	15	σ2	σ2	NOUN
ejpam-5015	147	16	∼	∼	NOUN
ejpam-5015	147	17	ig(α	ig(α	NOUN
ejpam-5015	147	18	,	,	PUNCT
ejpam-5015	147	19	β	β	X
ejpam-5015	147	20	)	)	PUNCT
ejpam-5015	147	21	(	(	PUNCT
ejpam-5015	147	22	15	15	NUM
ejpam-5015	147	23	)	)	PUNCT
ejpam-5015	147	24	i.	i.	PROPN
ejpam-5015	147	25	nawajah	nawajah	PROPN
ejpam-5015	147	26	,	,	PUNCT
ejpam-5015	147	27	h.	h.	PROPN
ejpam-5015	147	28	kanj	kanj	PROPN
ejpam-5015	147	29	,	,	PUNCT
ejpam-5015	147	30	y.	y.	PROPN
ejpam-5015	147	31	kotb	kotb	PROPN
ejpam-5015	147	32	,	,	PUNCT
ejpam-5015	147	33	j.	j.	PROPN
ejpam-5015	147	34	hoxha	hoxha	PROPN
ejpam-5015	147	35	,	,	PUNCT
ejpam-5015	147	36	m.	m.	PROPN
ejpam-5015	147	37	alakkoumi	alakkoumi	PROPN
ejpam-5015	147	38	,	,	PUNCT
ejpam-5015	147	39	k.	k.	PROPN
ejpam-5015	148	1	jebreen	jebreen	PROPN
ejpam-5015	148	2	/	/	SYM
ejpam-5015	148	3	eur	eur	PROPN
ejpam-5015	148	4	.	.	PUNCT
ejpam-5015	149	1	j.	j.	PROPN
ejpam-5015	149	2	pure	pure	PROPN
ejpam-5015	149	3	appl	appl	PROPN
ejpam-5015	149	4	.	.	PROPN
ejpam-5015	149	5	math	math	PROPN
ejpam-5015	149	6	,	,	PUNCT
ejpam-5015	149	7	17	17	NUM
ejpam-5015	149	8	(	(	PUNCT
ejpam-5015	149	9	1	1	NUM
ejpam-5015	149	10	)	)	PUNCT
ejpam-5015	149	11	(	(	PUNCT
ejpam-5015	149	12	2024	2024	NUM
ejpam-5015	149	13	)	)	PUNCT
ejpam-5015	149	14	,	,	PUNCT
ejpam-5015	149	15	180	180	NUM
ejpam-5015	149	16	-	-	SYM
ejpam-5015	149	17	200	200	NUM
ejpam-5015	149	18	186	186	NUM
ejpam-5015	149	19	note	note	NOUN
ejpam-5015	149	20	that	that	SCONJ
ejpam-5015	149	21	,	,	PUNCT
ejpam-5015	149	22	ℵ(µ	ℵ(µ	PROPN
ejpam-5015	149	23	,	,	PUNCT
ejpam-5015	149	24	σ2	σ2	NOUN
ejpam-5015	149	25	)	)	PUNCT
ejpam-5015	149	26	is	be	AUX
ejpam-5015	149	27	the	the	DET
ejpam-5015	149	28	normal	normal	ADJ
ejpam-5015	149	29	distribution	distribution	NOUN
ejpam-5015	149	30	with	with	ADP
ejpam-5015	149	31	mean	mean	ADJ
ejpam-5015	149	32	µ	µ	NOUN
ejpam-5015	149	33	and	and	CCONJ
ejpam-5015	149	34	variance	variance	NOUN
ejpam-5015	149	35	σ2	σ2	PROPN
ejpam-5015	149	36	and	and	CCONJ
ejpam-5015	149	37	ig(α	ig(α	NOUN
ejpam-5015	149	38	,	,	PUNCT
ejpam-5015	149	39	β	β	X
ejpam-5015	149	40	)	)	PUNCT
ejpam-5015	149	41	is	be	AUX
ejpam-5015	149	42	the	the	DET
ejpam-5015	149	43	inverse	inverse	NOUN
ejpam-5015	149	44	γ	γ	NOUN
ejpam-5015	149	45	distribution	distribution	NOUN
ejpam-5015	149	46	.	.	PUNCT
ejpam-5015	150	1	as	as	ADV
ejpam-5015	150	2	far	far	ADV
ejpam-5015	150	3	as	as	SCONJ
ejpam-5015	150	4	the	the	DET
ejpam-5015	150	5	prior	prior	NOUN
ejpam-5015	150	6	is	be	AUX
ejpam-5015	150	7	concerned	concern	VERB
ejpam-5015	150	8	,	,	PUNCT
ejpam-5015	150	9	all	all	DET
ejpam-5015	150	10	the	the	DET
ejpam-5015	150	11	hyperparameters	hyperparameter	NOUN
ejpam-5015	150	12	a	a	DET
ejpam-5015	150	13	,	,	PUNCT
ejpam-5015	150	14	b2,δ	b2,δ	PROPN
ejpam-5015	150	15	,	,	PUNCT
ejpam-5015	150	16	g2	g2	PROPN
ejpam-5015	150	17	,	,	PUNCT
ejpam-5015	150	18	α	α	NOUN
ejpam-5015	150	19	,	,	PUNCT
ejpam-5015	150	20	and	and	CCONJ
ejpam-5015	150	21	β	β	X
ejpam-5015	150	22	are	be	AUX
ejpam-5015	150	23	considered	consider	VERB
ejpam-5015	150	24	a	a	DET
ejpam-5015	150	25	priori	priori	X
ejpam-5015	150	26	(	(	PUNCT
ejpam-5015	150	27	conditionally	conditionally	ADV
ejpam-5015	150	28	)	)	PUNCT
ejpam-5015	150	29	independent	independent	ADJ
ejpam-5015	150	30	.	.	PUNCT
ejpam-5015	151	1	here	here	ADV
ejpam-5015	151	2	,	,	PUNCT
ejpam-5015	151	3	the	the	DET
ejpam-5015	151	4	fixed	fix	VERB
ejpam-5015	151	5	effects	effect	NOUN
ejpam-5015	151	6	parameters	parameter	NOUN
ejpam-5015	151	7	have	have	VERB
ejpam-5015	151	8	weakly	weakly	ADV
ejpam-5015	151	9	informative	informative	ADJ
ejpam-5015	151	10	marginal	marginal	ADJ
ejpam-5015	151	11	priors	prior	NOUN
ejpam-5015	151	12	,	,	PUNCT
ejpam-5015	151	13	i.e.	i.e.	X
ejpam-5015	151	14	,	,	PUNCT
ejpam-5015	151	15	in	in	ADP
ejpam-5015	151	16	this	this	DET
ejpam-5015	151	17	case	case	NOUN
ejpam-5015	151	18	,	,	PUNCT
ejpam-5015	151	19	the	the	DET
ejpam-5015	151	20	normal	normal	ADJ
ejpam-5015	151	21	distribution	distribution	NOUN
ejpam-5015	151	22	ℵ	ℵ	NOUN
ejpam-5015	151	23	is	be	AUX
ejpam-5015	151	24	centered	center	VERB
ejpam-5015	151	25	at	at	ADP
ejpam-5015	151	26	0	0	NUM
ejpam-5015	151	27	,	,	PUNCT
ejpam-5015	151	28	with	with	ADP
ejpam-5015	151	29	a	a	DET
ejpam-5015	151	30	large	large	ADJ
ejpam-5015	151	31	variance	variance	NOUN
ejpam-5015	151	32	.	.	PUNCT
ejpam-5015	152	1	particularly	particularly	ADV
ejpam-5015	152	2	,	,	PUNCT
ejpam-5015	152	3	we	we	PRON
ejpam-5015	152	4	let	let	VERB
ejpam-5015	152	5	that	that	PRON
ejpam-5015	152	6	:	:	PUNCT
ejpam-5015	152	7	a	a	X
ejpam-5015	152	8	,	,	PUNCT
ejpam-5015	152	9	δ	δ	PROPN
ejpam-5015	152	10	∼	∼	NOUN
ejpam-5015	152	11	ℵ(0	ℵ(0	PROPN
ejpam-5015	152	12	,	,	PUNCT
ejpam-5015	152	13	50),b	50),b	NUM
ejpam-5015	152	14	,	,	PUNCT
ejpam-5015	152	15	g	g	ADP
ejpam-5015	152	16	∼	∼	NOUN
ejpam-5015	152	17	uniform(0,10	uniform(0,10	NOUN
ejpam-5015	152	18	)	)	PUNCT
ejpam-5015	152	19	and	and	CCONJ
ejpam-5015	152	20	α	α	NOUN
ejpam-5015	152	21	,	,	PUNCT
ejpam-5015	152	22	β	β	X
ejpam-5015	152	23	∼	∼	NOUN
ejpam-5015	152	24	γ(2	γ(2	PROPN
ejpam-5015	152	25	,	,	PUNCT
ejpam-5015	152	26	2	2	NUM
ejpam-5015	152	27	)	)	PUNCT
ejpam-5015	152	28	.	.	PUNCT
ejpam-5015	153	1	distributions	distribution	NOUN
ejpam-5015	153	2	that	that	PRON
ejpam-5015	153	3	are	be	AUX
ejpam-5015	153	4	flat	flat	ADJ
ejpam-5015	153	5	along	along	ADP
ejpam-5015	153	6	the	the	DET
ejpam-5015	153	7	whole	whole	ADJ
ejpam-5015	153	8	real	real	ADJ
ejpam-5015	153	9	number	number	NOUN
ejpam-5015	153	10	line	line	NOUN
ejpam-5015	153	11	are	be	AUX
ejpam-5015	153	12	considered	consider	VERB
ejpam-5015	153	13	weakly	weakly	ADJ
ejpam-5015	153	14	informative	informative	ADJ
ejpam-5015	153	15	priors	prior	NOUN
ejpam-5015	153	16	because	because	SCONJ
ejpam-5015	153	17	they	they	PRON
ejpam-5015	153	18	do	do	AUX
ejpam-5015	153	19	n’t	not	PART
ejpam-5015	153	20	provide	provide	VERB
ejpam-5015	153	21	any	any	DET
ejpam-5015	153	22	information	information	NOUN
ejpam-5015	153	23	.	.	PUNCT
ejpam-5015	154	1	let	let	VERB
ejpam-5015	154	2	πj(θ	πj(θ	PUNCT
ejpam-5015	154	3	)	)	PUNCT
ejpam-5015	154	4	,	,	PUNCT
ejpam-5015	154	5	j	j	PROPN
ejpam-5015	154	6	=	=	SYM
ejpam-5015	154	7	1	1	NUM
ejpam-5015	154	8	,	,	PUNCT
ejpam-5015	154	9	2	2	NUM
ejpam-5015	154	10	,	,	PUNCT
ejpam-5015	154	11	3	3	NUM
ejpam-5015	154	12	,	,	PUNCT
ejpam-5015	154	13	be	be	AUX
ejpam-5015	154	14	the	the	DET
ejpam-5015	154	15	unknown	unknown	ADJ
ejpam-5015	154	16	parameters	parameter	NOUN
ejpam-5015	154	17	of	of	ADP
ejpam-5015	154	18	the	the	DET
ejpam-5015	154	19	prior	prior	ADJ
ejpam-5015	154	20	distribution	distribution	NOUN
ejpam-5015	154	21	and	and	CCONJ
ejpam-5015	154	22	define	define	VERB
ejpam-5015	154	23	the	the	DET
ejpam-5015	154	24	marginal	marginal	ADJ
ejpam-5015	154	25	density	density	NOUN
ejpam-5015	154	26	of	of	ADP
ejpam-5015	154	27	the	the	DET
ejpam-5015	154	28	random	random	ADJ
ejpam-5015	154	29	variable	variable	NOUN
ejpam-5015	154	30	y	y	NOUN
ejpam-5015	154	31	,	,	PUNCT
ejpam-5015	154	32	we	we	PRON
ejpam-5015	154	33	obtain	obtain	VERB
ejpam-5015	154	34	this	this	DET
ejpam-5015	154	35	equation	equation	NOUN
ejpam-5015	154	36	:	:	PUNCT
ejpam-5015	154	37	m1y	m1y	X
ejpam-5015	154	38	=	=	PUNCT
ejpam-5015	154	39	∫	∫	PROPN
ejpam-5015	154	40	f2(y	f2(y	PROPN
ejpam-5015	154	41	|	|	ADV
ejpam-5015	154	42	θ)∂y	θ)∂y	PROPN
ejpam-5015	154	43	,	,	PUNCT
ejpam-5015	154	44	(	(	PUNCT
ejpam-5015	154	45	16	16	NUM
ejpam-5015	154	46	)	)	PUNCT
ejpam-5015	154	47	where	where	SCONJ
ejpam-5015	154	48	θ	θ	NOUN
ejpam-5015	154	49	=	=	SYM
ejpam-5015	154	50	(	(	PUNCT
ejpam-5015	154	51	β0	β0	PROPN
ejpam-5015	154	52	,	,	PUNCT
ejpam-5015	154	53	β1	β1	PROPN
ejpam-5015	154	54	,	,	PUNCT
ejpam-5015	154	55	σ	σ	PROPN
ejpam-5015	154	56	2	2	NUM
ejpam-5015	154	57	)	)	PUNCT
ejpam-5015	154	58	(	(	PUNCT
ejpam-5015	154	59	17	17	NUM
ejpam-5015	154	60	)	)	PUNCT
ejpam-5015	154	61	the	the	DET
ejpam-5015	154	62	distribution	distribution	NOUN
ejpam-5015	154	63	of	of	ADP
ejpam-5015	154	64	yj(m	yj(m	NOUN
ejpam-5015	154	65	)	)	PUNCT
ejpam-5015	154	66	is	be	AUX
ejpam-5015	154	67	given	give	VERB
ejpam-5015	154	68	by	by	ADP
ejpam-5015	154	69	:	:	PUNCT
ejpam-5015	154	70	f(yj(m	f(yj(m	NUM
ejpam-5015	154	71	)	)	PUNCT
ejpam-5015	154	72	;	;	PUNCT
ejpam-5015	154	73	θ	θ	X
ejpam-5015	154	74	)	)	PUNCT
ejpam-5015	154	75	=	=	SYM
ejpam-5015	154	76	cm	cm	PROPN
ejpam-5015	154	77	σ	σ	PROPN
ejpam-5015	154	78	φ	φ	PROPN
ejpam-5015	154	79	(	(	PUNCT
ejpam-5015	154	80	yj(m	yj(m	NOUN
ejpam-5015	154	81	)	)	PUNCT
ejpam-5015	155	1	−	−	PROPN
ejpam-5015	155	2	β0	β0	NOUN
ejpam-5015	155	3	−	−	PROPN
ejpam-5015	155	4	β1xj	β1xj	PUNCT
ejpam-5015	155	5	σ	σ	NOUN
ejpam-5015	155	6	)	)	PUNCT
ejpam-5015	156	1	m−1	m−1	PROPN
ejpam-5015	156	2	×	×	NOUN
ejpam-5015	157	1	[	[	X
ejpam-5015	157	2	1−	1−	NUM
ejpam-5015	157	3	φ	φ	NUM
ejpam-5015	157	4	(	(	PUNCT
ejpam-5015	157	5	yj(m	yj(m	NOUN
ejpam-5015	157	6	)	)	PUNCT
ejpam-5015	157	7	−	−	PROPN
ejpam-5015	157	8	β0	β0	NOUN
ejpam-5015	157	9	−	−	PROPN
ejpam-5015	157	10	β1xj	β1xj	PUNCT
ejpam-5015	157	11	σ	σ	PROPN
ejpam-5015	157	12	)	)	PUNCT
ejpam-5015	157	13	]	]	PUNCT
ejpam-5015	157	14	m−1	m−1	PROPN
ejpam-5015	157	15	×θ	×θ	VERB
ejpam-5015	157	16	(	(	PUNCT
ejpam-5015	157	17	yj(m	yj(m	NOUN
ejpam-5015	157	18	)	)	PUNCT
ejpam-5015	157	19	−	−	PROPN
ejpam-5015	157	20	β0	β0	NOUN
ejpam-5015	157	21	−	−	PROPN
ejpam-5015	157	22	β1xj	β1xj	PUNCT
ejpam-5015	157	23	σ	σ	PROPN
ejpam-5015	157	24	)	)	PUNCT
ejpam-5015	157	25	(	(	PUNCT
ejpam-5015	157	26	18	18	NUM
ejpam-5015	157	27	)	)	PUNCT
ejpam-5015	157	28	where	where	SCONJ
ejpam-5015	157	29	θ	θ	NOUN
ejpam-5015	157	30	=	=	SYM
ejpam-5015	157	31	(	(	PUNCT
ejpam-5015	157	32	β0	β0	PROPN
ejpam-5015	157	33	,	,	PUNCT
ejpam-5015	157	34	β1	β1	PROPN
ejpam-5015	157	35	,	,	PUNCT
ejpam-5015	157	36	σ	σ	PROPN
ejpam-5015	157	37	2	2	NUM
ejpam-5015	157	38	)	)	PUNCT
ejpam-5015	157	39	(	(	PUNCT
ejpam-5015	157	40	19	19	NUM
ejpam-5015	157	41	)	)	PUNCT
ejpam-5015	157	42	and	and	CCONJ
ejpam-5015	157	43	cm	cm	NOUN
ejpam-5015	157	44	=	=	SYM
ejpam-5015	157	45	(	(	PUNCT
ejpam-5015	157	46	2m−	2m−	PROPN
ejpam-5015	157	47	1	1	NUM
ejpam-5015	157	48	)	)	PUNCT
ejpam-5015	157	49	!	!	PUNCT
ejpam-5015	158	1	(	(	PUNCT
ejpam-5015	158	2	m−	m−	PROPN
ejpam-5015	158	3	1)!2	1)!2	NUM
ejpam-5015	158	4	.	.	PUNCT
ejpam-5015	159	1	(	(	PUNCT
ejpam-5015	159	2	20	20	NUM
ejpam-5015	159	3	)	)	PUNCT
ejpam-5015	159	4	we	we	PRON
ejpam-5015	159	5	assume	assume	VERB
ejpam-5015	159	6	that	that	SCONJ
ejpam-5015	159	7	θ	θ	PROPN
ejpam-5015	159	8	has	have	VERB
ejpam-5015	159	9	the	the	DET
ejpam-5015	159	10	following	follow	VERB
ejpam-5015	159	11	prior	prior	ADJ
ejpam-5015	159	12	distribution	distribution	NOUN
ejpam-5015	159	13	:	:	PUNCT
ejpam-5015	159	14	π(θ	π(θ	NOUN
ejpam-5015	159	15	)	)	PUNCT
ejpam-5015	160	1	=	=	SYM
ejpam-5015	160	2	π(β0	π(β0	NOUN
ejpam-5015	160	3	,	,	PUNCT
ejpam-5015	160	4	β1	β1	PROPN
ejpam-5015	160	5	,	,	PUNCT
ejpam-5015	160	6	σ	σ	PROPN
ejpam-5015	160	7	2	2	NUM
ejpam-5015	160	8	)	)	PUNCT
ejpam-5015	160	9	=	=	PUNCT
ejpam-5015	160	10	π1(β0)π2(β1)π3(σ	π1(β0)π2(β1)π3(σ	NOUN
ejpam-5015	160	11	2	2	NUM
ejpam-5015	160	12	)	)	PUNCT
ejpam-5015	160	13	,	,	PUNCT
ejpam-5015	160	14	(	(	PUNCT
ejpam-5015	160	15	21	21	NUM
ejpam-5015	160	16	)	)	PUNCT
ejpam-5015	160	17	where	where	SCONJ
ejpam-5015	160	18	π1(β0	π1(β0	NOUN
ejpam-5015	160	19	)	)	PUNCT
ejpam-5015	160	20	=	=	SYM
ejpam-5015	160	21	1√	1√	NUM
ejpam-5015	160	22	2πb	2πb	NOUN
ejpam-5015	161	1	exp{−	exp{−	PUNCT
ejpam-5015	161	2	1	1	NUM
ejpam-5015	161	3	2b2	2b2	NUM
ejpam-5015	161	4	(	(	PUNCT
ejpam-5015	161	5	β0	β0	NOUN
ejpam-5015	161	6	−	−	PROPN
ejpam-5015	161	7	a)2	a)2	PROPN
ejpam-5015	161	8	}	}	PUNCT
ejpam-5015	161	9	(	(	PUNCT
ejpam-5015	161	10	22	22	NUM
ejpam-5015	161	11	)	)	PUNCT
ejpam-5015	161	12	and	and	CCONJ
ejpam-5015	161	13	−∞	−∞	X
ejpam-5015	161	14	<	<	X
ejpam-5015	161	15	β0	β0	NOUN
ejpam-5015	161	16	<	<	X
ejpam-5015	161	17	∞	∞	PROPN
ejpam-5015	161	18	(	(	PUNCT
ejpam-5015	161	19	23	23	NUM
ejpam-5015	161	20	)	)	PUNCT
ejpam-5015	161	21	π2(β1	π2(β1	PROPN
ejpam-5015	161	22	)	)	PUNCT
ejpam-5015	161	23	=	=	SYM
ejpam-5015	161	24	1√	1√	NUM
ejpam-5015	161	25	2πb	2πb	NOUN
ejpam-5015	162	1	exp{−	exp{−	PUNCT
ejpam-5015	162	2	1	1	NUM
ejpam-5015	162	3	2g2	2g2	NUM
ejpam-5015	162	4	(	(	PUNCT
ejpam-5015	162	5	β1	β1	PROPN
ejpam-5015	162	6	−	−	PROPN
ejpam-5015	162	7	δ)2	δ)2	PROPN
ejpam-5015	162	8	}	}	PUNCT
ejpam-5015	162	9	(	(	PUNCT
ejpam-5015	162	10	24	24	NUM
ejpam-5015	162	11	)	)	PUNCT
ejpam-5015	162	12	i.	i.	PROPN
ejpam-5015	162	13	nawajah	nawajah	PROPN
ejpam-5015	162	14	,	,	PUNCT
ejpam-5015	162	15	h.	h.	PROPN
ejpam-5015	162	16	kanj	kanj	PROPN
ejpam-5015	162	17	,	,	PUNCT
ejpam-5015	162	18	y.	y.	PROPN
ejpam-5015	162	19	kotb	kotb	PROPN
ejpam-5015	162	20	,	,	PUNCT
ejpam-5015	162	21	j.	j.	PROPN
ejpam-5015	162	22	hoxha	hoxha	PROPN
ejpam-5015	162	23	,	,	PUNCT
ejpam-5015	162	24	m.	m.	PROPN
ejpam-5015	162	25	alakkoumi	alakkoumi	PROPN
ejpam-5015	162	26	,	,	PUNCT
ejpam-5015	162	27	k.	k.	PROPN
ejpam-5015	162	28	jebreen	jebreen	PROPN
ejpam-5015	162	29	/	/	SYM
ejpam-5015	162	30	eur	eur	PROPN
ejpam-5015	162	31	.	.	PUNCT
ejpam-5015	163	1	j.	j.	PROPN
ejpam-5015	163	2	pure	pure	PROPN
ejpam-5015	163	3	appl	appl	PROPN
ejpam-5015	163	4	.	.	PROPN
ejpam-5015	163	5	math	math	PROPN
ejpam-5015	163	6	,	,	PUNCT
ejpam-5015	163	7	17	17	NUM
ejpam-5015	163	8	(	(	PUNCT
ejpam-5015	163	9	1	1	NUM
ejpam-5015	163	10	)	)	PUNCT
ejpam-5015	163	11	(	(	PUNCT
ejpam-5015	163	12	2024	2024	NUM
ejpam-5015	163	13	)	)	PUNCT
ejpam-5015	163	14	,	,	PUNCT
ejpam-5015	163	15	180	180	NUM
ejpam-5015	163	16	-	-	SYM
ejpam-5015	163	17	200	200	NUM
ejpam-5015	163	18	187	187	NUM
ejpam-5015	163	19	and	and	CCONJ
ejpam-5015	163	20	−∞	−∞	X
ejpam-5015	163	21	<	<	X
ejpam-5015	163	22	β1	β1	PROPN
ejpam-5015	163	23	<	<	X
ejpam-5015	163	24	∞	∞	PROPN
ejpam-5015	163	25	(	(	PUNCT
ejpam-5015	163	26	25	25	NUM
ejpam-5015	163	27	)	)	PUNCT
ejpam-5015	163	28	π3(σ	π3(σ	NUM
ejpam-5015	163	29	2	2	X
ejpam-5015	163	30	)	)	PUNCT
ejpam-5015	163	31	=	=	SYM
ejpam-5015	163	32	1	1	NUM
ejpam-5015	163	33	γ(α)(σ2)α+1	γ(α)(σ2)α+1	NOUN
ejpam-5015	163	34	exp{−	exp{−	NUM
ejpam-5015	163	35	1	1	NUM
ejpam-5015	163	36	σ2β	σ2β	NOUN
ejpam-5015	163	37	}	}	PUNCT
ejpam-5015	163	38	(	(	PUNCT
ejpam-5015	163	39	26	26	NUM
ejpam-5015	163	40	)	)	PUNCT
ejpam-5015	163	41	and	and	CCONJ
ejpam-5015	163	42	σ2	σ2	PROPN
ejpam-5015	163	43	>	>	X
ejpam-5015	163	44	0	0	PROPN
ejpam-5015	163	45	.	.	PUNCT
ejpam-5015	164	1	equation	equation	NOUN
ejpam-5015	164	2	22	22	NUM
ejpam-5015	164	3	,	,	PUNCT
ejpam-5015	164	4	24	24	NUM
ejpam-5015	164	5	and	and	CCONJ
ejpam-5015	164	6	26	26	NUM
ejpam-5015	164	7	are	be	AUX
ejpam-5015	164	8	our	our	PRON
ejpam-5015	164	9	prior	prior	ADJ
ejpam-5015	164	10	distributions	distribution	NOUN
ejpam-5015	164	11	of	of	ADP
ejpam-5015	164	12	the	the	DET
ejpam-5015	164	13	three	three	NUM
ejpam-5015	164	14	independent	independent	ADJ
ejpam-5015	164	15	parameters	parameter	NOUN
ejpam-5015	164	16	of	of	ADP
ejpam-5015	164	17	the	the	DET
ejpam-5015	164	18	vector	vector	PROPN
ejpam-5015	164	19	θ	θ	PROPN
ejpam-5015	164	20	.	.	PUNCT
ejpam-5015	165	1	if	if	SCONJ
ejpam-5015	165	2	y	y	PROPN
ejpam-5015	165	3	m	m	VERB
ejpam-5015	165	4	(	(	PUNCT
ejpam-5015	165	5	y1(m	y1(m	PROPN
ejpam-5015	165	6	)	)	PUNCT
ejpam-5015	165	7	,	,	PUNCT
ejpam-5015	165	8	y2(m	y2(m	NOUN
ejpam-5015	165	9	)	)	PUNCT
ejpam-5015	165	10	,	,	PUNCT
ejpam-5015	165	11	....	....	PUNCT
ejpam-5015	165	12	,	,	PUNCT
ejpam-5015	165	13	yr(m	yr(m	X
ejpam-5015	165	14	)	)	PUNCT
ejpam-5015	165	15	,	,	PUNCT
ejpam-5015	165	16	)	)	PUNCT
ejpam-5015	165	17	,	,	PUNCT
ejpam-5015	165	18	then	then	ADV
ejpam-5015	165	19	y	y	PROPN
ejpam-5015	165	20	m	m	VERB
ejpam-5015	165	21	has	have	VERB
ejpam-5015	165	22	the	the	DET
ejpam-5015	165	23	following	follow	VERB
ejpam-5015	165	24	joint	joint	ADJ
ejpam-5015	165	25	pdf	pdf	NOUN
ejpam-5015	165	26	:	:	PUNCT
ejpam-5015	165	27	fy	fy	PROPN
ejpam-5015	165	28	m	m	PROPN
ejpam-5015	165	29	(	(	PUNCT
ejpam-5015	165	30	y	y	PROPN
ejpam-5015	165	31	m	m	PROPN
ejpam-5015	165	32	;	;	PUNCT
ejpam-5015	165	33	θ	θ	X
ejpam-5015	165	34	)	)	PUNCT
ejpam-5015	165	35	=	=	SYM
ejpam-5015	166	1	cr	cr	PROPN
ejpam-5015	166	2	m	m	PROPN
ejpam-5015	166	3	σr	σr	PROPN
ejpam-5015	166	4	r∏	r∏	PROPN
ejpam-5015	166	5	j=1	j=1	PUNCT
ejpam-5015	167	1	[	[	X
ejpam-5015	167	2	φ	φ	X
ejpam-5015	167	3	(	(	PUNCT
ejpam-5015	167	4	yj(m	yj(m	NOUN
ejpam-5015	167	5	)	)	PUNCT
ejpam-5015	167	6	−	−	PROPN
ejpam-5015	168	1	β0	β0	NOUN
ejpam-5015	168	2	−	−	PROPN
ejpam-5015	168	3	β1xj	β1xj	PUNCT
ejpam-5015	168	4	σ	σ	NOUN
ejpam-5015	168	5	)	)	PUNCT
ejpam-5015	168	6	m−1	m−1	PROPN
ejpam-5015	168	7	]	]	X
ejpam-5015	169	1	×	×	NOUN
ejpam-5015	170	1	[	[	X
ejpam-5015	170	2	φ	φ	X
ejpam-5015	170	3	(	(	PUNCT
ejpam-5015	170	4	−yj(m	−yj(m	PROPN
ejpam-5015	170	5	)	)	PUNCT
ejpam-5015	170	6	−	−	PROPN
ejpam-5015	170	7	β0	β0	NOUN
ejpam-5015	170	8	−	−	PROPN
ejpam-5015	170	9	β1xj	β1xj	PUNCT
ejpam-5015	170	10	σ	σ	NOUN
ejpam-5015	170	11	)	)	PUNCT
ejpam-5015	170	12	m−1	m−1	PROPN
ejpam-5015	170	13	×θ	×θ	VERB
ejpam-5015	170	14	(	(	PUNCT
ejpam-5015	170	15	−yj(m	−yj(m	NOUN
ejpam-5015	170	16	)	)	PUNCT
ejpam-5015	170	17	−	−	PROPN
ejpam-5015	170	18	β0	β0	NOUN
ejpam-5015	170	19	−	−	PROPN
ejpam-5015	170	20	β1xj	β1xj	PUNCT
ejpam-5015	170	21	σ	σ	PROPN
ejpam-5015	170	22	)	)	PUNCT
ejpam-5015	170	23	]	]	PUNCT
ejpam-5015	170	24	.	.	PUNCT
ejpam-5015	171	1	(	(	PUNCT
ejpam-5015	171	2	27	27	NUM
ejpam-5015	171	3	)	)	PUNCT
ejpam-5015	171	4	the	the	DET
ejpam-5015	171	5	joint	joint	ADJ
ejpam-5015	171	6	pdf	pdf	NOUN
ejpam-5015	171	7	is	be	AUX
ejpam-5015	171	8	formed	form	VERB
ejpam-5015	171	9	as	as	ADP
ejpam-5015	171	10	a	a	DET
ejpam-5015	171	11	product	product	NOUN
ejpam-5015	171	12	of	of	ADP
ejpam-5015	171	13	individual	individual	ADJ
ejpam-5015	171	14	probabilities	probability	NOUN
ejpam-5015	171	15	because	because	SCONJ
ejpam-5015	171	16	we	we	PRON
ejpam-5015	171	17	have	have	AUX
ejpam-5015	171	18	assumed	assume	VERB
ejpam-5015	171	19	the	the	DET
ejpam-5015	171	20	observations	observation	NOUN
ejpam-5015	171	21	are	be	AUX
ejpam-5015	171	22	independently	independently	ADV
ejpam-5015	171	23	drawn	draw	VERB
ejpam-5015	171	24	from	from	ADP
ejpam-5015	171	25	the	the	DET
ejpam-5015	171	26	underlying	underlie	VERB
ejpam-5015	171	27	distribution	distribution	NOUN
ejpam-5015	171	28	.	.	PUNCT
ejpam-5015	172	1	the	the	DET
ejpam-5015	172	2	term	term	NOUN
ejpam-5015	172	3	inside	inside	ADP
ejpam-5015	172	4	the	the	DET
ejpam-5015	172	5	product	product	NOUN
ejpam-5015	172	6	notation	notation	NOUN
ejpam-5015	172	7	corresponds	correspond	VERB
ejpam-5015	172	8	to	to	ADP
ejpam-5015	172	9	the	the	DET
ejpam-5015	172	10	probability	probability	NOUN
ejpam-5015	172	11	density	density	NOUN
ejpam-5015	172	12	of	of	ADP
ejpam-5015	172	13	each	each	DET
ejpam-5015	172	14	individual	individual	ADJ
ejpam-5015	172	15	observation	observation	NOUN
ejpam-5015	172	16	yj(m	yj(m	NOUN
ejpam-5015	172	17	)	)	PUNCT
ejpam-5015	172	18	.	.	PUNCT
ejpam-5015	173	1	each	each	PRON
ejpam-5015	173	2	of	of	ADP
ejpam-5015	173	3	these	these	PRON
ejpam-5015	173	4	is	be	AUX
ejpam-5015	173	5	distributed	distribute	VERB
ejpam-5015	173	6	according	accord	VERB
ejpam-5015	173	7	to	to	ADP
ejpam-5015	173	8	a	a	DET
ejpam-5015	173	9	modified	modify	VERB
ejpam-5015	173	10	normal	normal	ADJ
ejpam-5015	173	11	distribution	distribution	NOUN
ejpam-5015	173	12	,	,	PUNCT
ejpam-5015	173	13	with	with	ADP
ejpam-5015	173	14	the	the	DET
ejpam-5015	173	15	parameters	parameter	NOUN
ejpam-5015	173	16	of	of	ADP
ejpam-5015	173	17	the	the	DET
ejpam-5015	173	18	distribution	distribution	NOUN
ejpam-5015	173	19	depending	depend	VERB
ejpam-5015	173	20	on	on	ADP
ejpam-5015	173	21	β0	β0	PROPN
ejpam-5015	173	22	,	,	PUNCT
ejpam-5015	173	23	β1	β1	PROPN
ejpam-5015	173	24	,	,	PUNCT
ejpam-5015	173	25	and	and	CCONJ
ejpam-5015	173	26	xj	xj	PROPN
ejpam-5015	173	27	(	(	PUNCT
ejpam-5015	173	28	value	value	NOUN
ejpam-5015	173	29	of	of	ADP
ejpam-5015	173	30	the	the	DET
ejpam-5015	173	31	predictor	predictor	NOUN
ejpam-5015	173	32	variable	variable	NOUN
ejpam-5015	173	33	for	for	ADP
ejpam-5015	173	34	the	the	DET
ejpam-5015	173	35	jth	jth	PROPN
ejpam-5015	173	36	group	group	PROPN
ejpam-5015	173	37	)	)	PUNCT
ejpam-5015	173	38	.	.	PUNCT
ejpam-5015	174	1	the	the	DET
ejpam-5015	174	2	term	term	NOUN
ejpam-5015	174	3	φ	φ	PROPN
ejpam-5015	174	4	(	(	PUNCT
ejpam-5015	174	5	yj(m)−β0−β1xj	yj(m)−β0−β1xj	PROPN
ejpam-5015	174	6	σ	σ	NOUN
ejpam-5015	174	7	)	)	PUNCT
ejpam-5015	174	8	m−1	m−1	PROPN
ejpam-5015	174	9	accounts	account	VERB
ejpam-5015	174	10	for	for	ADP
ejpam-5015	174	11	the	the	DET
ejpam-5015	174	12	cumulative	cumulative	ADJ
ejpam-5015	174	13	likelihood	likelihood	NOUN
ejpam-5015	174	14	of	of	ADP
ejpam-5015	174	15	each	each	DET
ejpam-5015	174	16	residual	residual	ADJ
ejpam-5015	174	17	from	from	ADP
ejpam-5015	174	18	the	the	DET
ejpam-5015	174	19	model	model	NOUN
ejpam-5015	174	20	raised	raise	VERB
ejpam-5015	174	21	to	to	ADP
ejpam-5015	174	22	the	the	DET
ejpam-5015	174	23	power	power	NOUN
ejpam-5015	174	24	of	of	ADP
ejpam-5015	174	25	(	(	PUNCT
ejpam-5015	174	26	m	m	NOUN
ejpam-5015	174	27	−	−	NOUN
ejpam-5015	174	28	1	1	NUM
ejpam-5015	174	29	)	)	PUNCT
ejpam-5015	174	30	.	.	PUNCT
ejpam-5015	175	1	similarly	similarly	ADV
ejpam-5015	175	2	,	,	PUNCT
ejpam-5015	175	3	φ	φ	PROPN
ejpam-5015	175	4	(	(	PUNCT
ejpam-5015	175	5	−yj(m)−β0−β1xj	−yj(m)−β0−β1xj	PROPN
ejpam-5015	175	6	σ	σ	PROPN
ejpam-5015	175	7	)	)	PUNCT
ejpam-5015	175	8	m−1	m−1	PROPN
ejpam-5015	175	9	captures	capture	VERB
ejpam-5015	175	10	the	the	DET
ejpam-5015	175	11	remaining	remain	VERB
ejpam-5015	175	12	part	part	NOUN
ejpam-5015	175	13	of	of	ADP
ejpam-5015	175	14	cumulative	cumulative	ADJ
ejpam-5015	175	15	distribution	distribution	NOUN
ejpam-5015	175	16	from	from	ADP
ejpam-5015	175	17	the	the	DET
ejpam-5015	175	18	observed	observe	VERB
ejpam-5015	175	19	value	value	NOUN
ejpam-5015	175	20	,	,	PUNCT
ejpam-5015	175	21	also	also	ADV
ejpam-5015	175	22	raised	raise	VERB
ejpam-5015	175	23	to	to	ADP
ejpam-5015	175	24	the	the	DET
ejpam-5015	175	25	power	power	NOUN
ejpam-5015	175	26	of	of	ADP
ejpam-5015	175	27	(	(	PUNCT
ejpam-5015	175	28	m	m	NOUN
ejpam-5015	175	29	−	−	NOUN
ejpam-5015	175	30	1	1	NUM
ejpam-5015	175	31	)	)	PUNCT
ejpam-5015	175	32	.	.	PUNCT
ejpam-5015	176	1	θ	θ	X
ejpam-5015	176	2	(	(	PUNCT
ejpam-5015	176	3	−yj(m)−β0−β1xj	−yj(m)−β0−β1xj	PROPN
ejpam-5015	176	4	σ	σ	PROPN
ejpam-5015	176	5	)	)	PUNCT
ejpam-5015	176	6	is	be	AUX
ejpam-5015	176	7	the	the	DET
ejpam-5015	176	8	pdf	pdf	NOUN
ejpam-5015	176	9	of	of	ADP
ejpam-5015	176	10	the	the	DET
ejpam-5015	176	11	standardized	standardized	ADJ
ejpam-5015	176	12	residuals	residual	NOUN
ejpam-5015	176	13	.	.	PUNCT
ejpam-5015	177	1	this	this	DET
ejpam-5015	177	2	term	term	NOUN
ejpam-5015	177	3	models	model	VERB
ejpam-5015	177	4	the	the	DET
ejpam-5015	177	5	density	density	NOUN
ejpam-5015	177	6	of	of	ADP
ejpam-5015	177	7	the	the	DET
ejpam-5015	177	8	residuals	residual	NOUN
ejpam-5015	177	9	around	around	ADP
ejpam-5015	177	10	the	the	DET
ejpam-5015	177	11	model	model	NOUN
ejpam-5015	177	12	fit	fit	PROPN
ejpam-5015	177	13	.	.	PUNCT
ejpam-5015	178	1	the	the	DET
ejpam-5015	178	2	posterior	posterior	ADJ
ejpam-5015	178	3	pdf	pdf	NOUN
ejpam-5015	178	4	of	of	ADP
ejpam-5015	178	5	θ	θ	PROPN
ejpam-5015	178	6	given	give	VERB
ejpam-5015	178	7	ym	ym	PROPN
ejpam-5015	179	1	=	=	SYM
ejpam-5015	180	1	y	y	PROPN
ejpam-5015	181	1	m	m	NOUN
ejpam-5015	181	2	is	be	AUX
ejpam-5015	181	3	proportional	proportional	ADJ
ejpam-5015	181	4	to	to	ADP
ejpam-5015	181	5	the	the	DET
ejpam-5015	181	6	product	product	NOUN
ejpam-5015	181	7	of	of	ADP
ejpam-5015	181	8	the	the	DET
ejpam-5015	181	9	likelihood	likelihood	NOUN
ejpam-5015	181	10	function	function	NOUN
ejpam-5015	181	11	,	,	PUNCT
ejpam-5015	181	12	fym	fym	NOUN
ejpam-5015	181	13	(	(	PUNCT
ejpam-5015	181	14	ym	ym	NOUN
ejpam-5015	181	15	;	;	PUNCT
ejpam-5015	181	16	θ	θ	NOUN
ejpam-5015	181	17	)	)	PUNCT
ejpam-5015	181	18	,	,	PUNCT
ejpam-5015	181	19	and	and	CCONJ
ejpam-5015	181	20	the	the	DET
ejpam-5015	181	21	prior	prior	ADJ
ejpam-5015	181	22	distribution	distribution	NOUN
ejpam-5015	181	23	π(θ	π(θ	NOUN
ejpam-5015	181	24	)	)	PUNCT
ejpam-5015	181	25	.	.	PUNCT
ejpam-5015	182	1	after	after	ADP
ejpam-5015	182	2	some	some	DET
ejpam-5015	182	3	manipulation	manipulation	NOUN
ejpam-5015	182	4	we	we	PRON
ejpam-5015	182	5	can	can	AUX
ejpam-5015	182	6	write	write	VERB
ejpam-5015	182	7	the	the	DET
ejpam-5015	182	8	posterior	posterior	ADJ
ejpam-5015	182	9	pdf	pdf	NOUN
ejpam-5015	182	10	as	as	ADP
ejpam-5015	182	11	below	below	ADV
ejpam-5015	182	12	:	:	PUNCT
ejpam-5015	182	13	π(θ	π(θ	NOUN
ejpam-5015	182	14	|	|	NOUN
ejpam-5015	182	15	ym)α	ym)α	PROPN
ejpam-5015	182	16	fym	fym	NOUN
ejpam-5015	182	17	(	(	PUNCT
ejpam-5015	182	18	ym	ym	NOUN
ejpam-5015	182	19	;	;	PUNCT
ejpam-5015	182	20	θ)π(θ	θ)π(θ	NOUN
ejpam-5015	182	21	)	)	PUNCT
ejpam-5015	182	22	α	α	PROPN
ejpam-5015	182	23	1	1	NUM
ejpam-5015	182	24	σr	σr	PROPN
ejpam-5015	182	25	[	[	PUNCT
ejpam-5015	182	26	r∏	r∏	NOUN
ejpam-5015	182	27	j=1	j=1	NOUN
ejpam-5015	182	28	ej	ej	X
ejpam-5015	182	29	]	]	PUNCT
ejpam-5015	182	30	1	1	NUM
ejpam-5015	182	31	(	(	PUNCT
ejpam-5015	182	32	σ2)α+1	σ2)α+1	NOUN
ejpam-5015	182	33	[	[	X
ejpam-5015	182	34	exp{−	exp{−	VERB
ejpam-5015	182	35	1	1	NUM
ejpam-5015	182	36	2b2	2b2	NUM
ejpam-5015	182	37	(	(	PUNCT
ejpam-5015	182	38	β0	β0	NOUN
ejpam-5015	182	39	−	−	PROPN
ejpam-5015	182	40	a)2	a)2	PROPN
ejpam-5015	182	41	}	}	PUNCT
ejpam-5015	182	42	×exp{−	×exp{−	VERB
ejpam-5015	182	43	1	1	NUM
ejpam-5015	182	44	2g2	2g2	NUM
ejpam-5015	182	45	(	(	PUNCT
ejpam-5015	182	46	β1	β1	PROPN
ejpam-5015	182	47	−	−	PROPN
ejpam-5015	182	48	δ)2	δ)2	PROPN
ejpam-5015	182	49	}	}	PUNCT
ejpam-5015	182	50	×	×	NOUN
ejpam-5015	182	51	exp{−	exp{−	VERB
ejpam-5015	182	52	1	1	NUM
ejpam-5015	182	53	σ2β	σ2β	NOUN
ejpam-5015	182	54	}	}	PUNCT
ejpam-5015	182	55	]	]	PUNCT
ejpam-5015	182	56	,	,	PUNCT
ejpam-5015	182	57	(	(	PUNCT
ejpam-5015	182	58	28	28	NUM
ejpam-5015	182	59	)	)	PUNCT
ejpam-5015	182	60	where	where	SCONJ
ejpam-5015	182	61	ej	ej	ADP
ejpam-5015	182	62	=	=	PRON
ejpam-5015	183	1	[	[	X
ejpam-5015	183	2	φ	φ	X
ejpam-5015	183	3	(	(	PUNCT
ejpam-5015	183	4	yj(m	yj(m	NOUN
ejpam-5015	183	5	)	)	PUNCT
ejpam-5015	183	6	−	−	PROPN
ejpam-5015	183	7	β0	β0	NOUN
ejpam-5015	183	8	−	−	PROPN
ejpam-5015	183	9	β1xj	β1xj	PUNCT
ejpam-5015	183	10	σ	σ	PROPN
ejpam-5015	183	11	)	)	PUNCT
ejpam-5015	183	12	φ×	φ×	PROPN
ejpam-5015	183	13	i.	i.	PROPN
ejpam-5015	183	14	nawajah	nawajah	PROPN
ejpam-5015	183	15	,	,	PUNCT
ejpam-5015	183	16	h.	h.	PROPN
ejpam-5015	183	17	kanj	kanj	PROPN
ejpam-5015	183	18	,	,	PUNCT
ejpam-5015	183	19	y.	y.	PROPN
ejpam-5015	183	20	kotb	kotb	PROPN
ejpam-5015	183	21	,	,	PUNCT
ejpam-5015	183	22	j.	j.	PROPN
ejpam-5015	183	23	hoxha	hoxha	PROPN
ejpam-5015	183	24	,	,	PUNCT
ejpam-5015	183	25	m.	m.	PROPN
ejpam-5015	183	26	alakkoumi	alakkoumi	PROPN
ejpam-5015	183	27	,	,	PUNCT
ejpam-5015	183	28	k.	k.	PROPN
ejpam-5015	184	1	jebreen	jebreen	PROPN
ejpam-5015	184	2	/	/	SYM
ejpam-5015	184	3	eur	eur	PROPN
ejpam-5015	184	4	.	.	PUNCT
ejpam-5015	185	1	j.	j.	PROPN
ejpam-5015	185	2	pure	pure	PROPN
ejpam-5015	185	3	appl	appl	PROPN
ejpam-5015	185	4	.	.	PROPN
ejpam-5015	185	5	math	math	PROPN
ejpam-5015	185	6	,	,	PUNCT
ejpam-5015	185	7	17	17	NUM
ejpam-5015	185	8	(	(	PUNCT
ejpam-5015	185	9	1	1	NUM
ejpam-5015	185	10	)	)	PUNCT
ejpam-5015	185	11	(	(	PUNCT
ejpam-5015	185	12	2024	2024	NUM
ejpam-5015	185	13	)	)	PUNCT
ejpam-5015	185	14	,	,	PUNCT
ejpam-5015	185	15	180	180	NUM
ejpam-5015	185	16	-	-	SYM
ejpam-5015	185	17	200	200	NUM
ejpam-5015	185	18	188	188	NUM
ejpam-5015	185	19	(	(	PUNCT
ejpam-5015	185	20	β0	β0	NOUN
ejpam-5015	185	21	+	+	CCONJ
ejpam-5015	185	22	β1xj	β1xj	NUM
ejpam-5015	185	23	−	−	PRON
ejpam-5015	185	24	yj(m	yj(m	NOUN
ejpam-5015	185	25	)	)	PUNCT
ejpam-5015	185	26	σ	σ	NOUN
ejpam-5015	185	27	)	)	PUNCT
ejpam-5015	186	1	]	]	X
ejpam-5015	186	2	m−1	m−1	PROPN
ejpam-5015	186	3	×	×	PROPN
ejpam-5015	186	4	θ	θ	PROPN
ejpam-5015	186	5	(	(	PUNCT
ejpam-5015	186	6	yj(m	yj(m	NOUN
ejpam-5015	186	7	)	)	PUNCT
ejpam-5015	186	8	−	−	PROPN
ejpam-5015	186	9	β0	β0	NOUN
ejpam-5015	186	10	−	−	PROPN
ejpam-5015	186	11	β1xj	β1xj	PUNCT
ejpam-5015	186	12	σ	σ	PROPN
ejpam-5015	186	13	)	)	PUNCT
ejpam-5015	186	14	(	(	PUNCT
ejpam-5015	186	15	29	29	NUM
ejpam-5015	186	16	)	)	PUNCT
ejpam-5015	186	17	the	the	DET
ejpam-5015	186	18	posterior	posterior	ADJ
ejpam-5015	186	19	pdf	pdf	NOUN
ejpam-5015	186	20	is	be	AUX
ejpam-5015	186	21	then	then	ADV
ejpam-5015	186	22	compactly	compactly	ADV
ejpam-5015	186	23	represented	represent	VERB
ejpam-5015	186	24	as	as	SCONJ
ejpam-5015	186	25	the	the	DET
ejpam-5015	186	26	product	product	NOUN
ejpam-5015	186	27	of	of	ADP
ejpam-5015	186	28	three	three	NUM
ejpam-5015	186	29	components	component	NOUN
ejpam-5015	186	30	give	give	VERB
ejpam-5015	186	31	as	as	ADP
ejpam-5015	186	32	:	:	PUNCT
ejpam-5015	186	33	π(β0	π(β0	PROPN
ejpam-5015	186	34	,	,	PUNCT
ejpam-5015	186	35	β1	β1	PROPN
ejpam-5015	186	36	,	,	PUNCT
ejpam-5015	186	37	σ	σ	PROPN
ejpam-5015	186	38	2	2	NUM
ejpam-5015	187	1	|	|	ADV
ejpam-5015	187	2	y	y	PROPN
ejpam-5015	187	3	m	m	NOUN
ejpam-5015	187	4	)	)	PUNCT
ejpam-5015	188	1	α	α	X
ejpam-5015	188	2	1	1	NUM
ejpam-5015	188	3	(	(	PUNCT
ejpam-5015	188	4	σ2	σ2	NOUN
ejpam-5015	188	5	)	)	PUNCT
ejpam-5015	188	6	r	r	NOUN
ejpam-5015	188	7	2	2	NUM
ejpam-5015	189	1	+	+	NOUN
ejpam-5015	189	2	α+1	α+1	NUM
ejpam-5015	189	3	exp	exp	NOUN
ejpam-5015	189	4	(	(	PUNCT
ejpam-5015	189	5	−	−	PROPN
ejpam-5015	189	6	∑r	∑r	PROPN
ejpam-5015	189	7	j=1(yj(m	j=1(yj(m	NOUN
ejpam-5015	189	8	)	)	PUNCT
ejpam-5015	190	1	−	−	PROPN
ejpam-5015	190	2	β0	β0	ADJ
ejpam-5015	190	3	−	−	PROPN
ejpam-5015	190	4	β1xj	β1xj	PUNCT
ejpam-5015	190	5	)	)	PUNCT
ejpam-5015	190	6	2	2	NUM
ejpam-5015	190	7	2σ2	2σ2	NUM
ejpam-5015	191	1	−	−	NOUN
ejpam-5015	191	2	(	(	PUNCT
ejpam-5015	191	3	β0	β0	NOUN
ejpam-5015	191	4	−	−	PROPN
ejpam-5015	191	5	a)2	a)2	PROPN
ejpam-5015	191	6	2b2	2b2	NUM
ejpam-5015	191	7	−	−	PROPN
ejpam-5015	191	8	(	(	PUNCT
ejpam-5015	191	9	β1	β1	PROPN
ejpam-5015	191	10	−	−	PROPN
ejpam-5015	191	11	δ	δ	PROPN
ejpam-5015	191	12	)	)	PUNCT
ejpam-5015	191	13	2g2	2g2	NUM
ejpam-5015	191	14	−	−	NOUN
ejpam-5015	191	15	1	1	NUM
ejpam-5015	191	16	σ2β	σ2β	NOUN
ejpam-5015	191	17	)	)	PUNCT
ejpam-5015	191	18	x	x	X
ejpam-5015	192	1	r∏	r∏	NOUN
ejpam-5015	192	2	j=1	j=1	PROPN
ejpam-5015	192	3	φ	φ	PROPN
ejpam-5015	192	4	(	(	PUNCT
ejpam-5015	192	5	yj(m	yj(m	NOUN
ejpam-5015	192	6	)	)	PUNCT
ejpam-5015	192	7	−	−	PROPN
ejpam-5015	193	1	β0	β0	NOUN
ejpam-5015	193	2	−	−	PROPN
ejpam-5015	193	3	β1xj	β1xj	PUNCT
ejpam-5015	193	4	σ	σ	NOUN
ejpam-5015	193	5	)	)	PUNCT
ejpam-5015	194	1	m−1	m−1	PROPN
ejpam-5015	194	2	φ	φ	PROPN
ejpam-5015	194	3	(	(	PUNCT
ejpam-5015	194	4	−yj(m	−yj(m	PROPN
ejpam-5015	194	5	)	)	PUNCT
ejpam-5015	194	6	+	+	CCONJ
ejpam-5015	194	7	β0	β0	PROPN
ejpam-5015	194	8	+	+	CCONJ
ejpam-5015	194	9	β1xj	β1xj	PUNCT
ejpam-5015	194	10	σ	σ	NOUN
ejpam-5015	194	11	)	)	PUNCT
ejpam-5015	194	12	m−1	m−1	PROPN
ejpam-5015	194	13	.	.	PUNCT
ejpam-5015	195	1	(	(	PUNCT
ejpam-5015	195	2	30	30	NUM
ejpam-5015	195	3	)	)	PUNCT
ejpam-5015	195	4	were	be	AUX
ejpam-5015	195	5	1	1	NUM
ejpam-5015	195	6	(	(	PUNCT
ejpam-5015	195	7	σ2	σ2	NOUN
ejpam-5015	195	8	)	)	PUNCT
ejpam-5015	195	9	r	r	NOUN
ejpam-5015	195	10	2+α+1	2+α+1	NUM
ejpam-5015	195	11	is	be	AUX
ejpam-5015	195	12	a	a	DET
ejpam-5015	195	13	normalization	normalization	NOUN
ejpam-5015	195	14	term	term	NOUN
ejpam-5015	195	15	,	,	PUNCT
ejpam-5015	195	16	the	the	DET
ejpam-5015	195	17	second	second	ADJ
ejpam-5015	195	18	term	term	NOUN
ejpam-5015	195	19	is	be	AUX
ejpam-5015	195	20	the	the	DET
ejpam-5015	195	21	exponential	exponential	ADJ
ejpam-5015	195	22	function	function	NOUN
ejpam-5015	195	23	which	which	PRON
ejpam-5015	195	24	has	have	VERB
ejpam-5015	195	25	four	four	NUM
ejpam-5015	195	26	components	component	NOUN
ejpam-5015	195	27	in	in	ADP
ejpam-5015	195	28	the	the	DET
ejpam-5015	195	29	exponent	exponent	NOUN
ejpam-5015	195	30	,	,	PUNCT
ejpam-5015	195	31	each	each	PRON
ejpam-5015	195	32	representing	represent	VERB
ejpam-5015	195	33	a	a	DET
ejpam-5015	195	34	component	component	NOUN
ejpam-5015	195	35	of	of	ADP
ejpam-5015	195	36	the	the	DET
ejpam-5015	195	37	prior	prior	ADJ
ejpam-5015	195	38	distributions	distribution	NOUN
ejpam-5015	195	39	.	.	PUNCT
ejpam-5015	196	1	lastly	lastly	ADV
ejpam-5015	196	2	,	,	PUNCT
ejpam-5015	196	3	the	the	DET
ejpam-5015	196	4	third	third	ADJ
ejpam-5015	196	5	term	term	NOUN
ejpam-5015	196	6	is	be	AUX
ejpam-5015	196	7	the	the	DET
ejpam-5015	196	8	product	product	NOUN
ejpam-5015	196	9	over	over	ADP
ejpam-5015	196	10	all	all	DET
ejpam-5015	196	11	residuals	residual	NOUN
ejpam-5015	196	12	of	of	ADP
ejpam-5015	196	13	two	two	NUM
ejpam-5015	196	14	standard	standard	ADJ
ejpam-5015	196	15	normal	normal	ADJ
ejpam-5015	196	16	cumulative	cumulative	ADJ
ejpam-5015	196	17	distribution	distribution	NOUN
ejpam-5015	196	18	functions	function	NOUN
ejpam-5015	196	19	(	(	PUNCT
ejpam-5015	196	20	cdfs	cdfs	PROPN
ejpam-5015	196	21	)	)	PUNCT
ejpam-5015	196	22	evaluated	evaluate	VERB
ejpam-5015	196	23	at	at	ADP
ejpam-5015	196	24	the	the	DET
ejpam-5015	196	25	standardized	standardized	ADJ
ejpam-5015	196	26	residuals	residual	NOUN
ejpam-5015	196	27	,	,	PUNCT
ejpam-5015	196	28	each	each	PRON
ejpam-5015	196	29	raised	raise	VERB
ejpam-5015	196	30	to	to	ADP
ejpam-5015	196	31	the	the	DET
ejpam-5015	196	32	power	power	NOUN
ejpam-5015	196	33	of	of	ADP
ejpam-5015	196	34	(	(	PUNCT
ejpam-5015	196	35	m-1	m-1	NOUN
ejpam-5015	196	36	)	)	PUNCT
ejpam-5015	196	37	.	.	PUNCT
ejpam-5015	197	1	for	for	ADP
ejpam-5015	197	2	facilitating	facilitate	VERB
ejpam-5015	197	3	the	the	DET
ejpam-5015	197	4	derivation	derivation	NOUN
ejpam-5015	197	5	of	of	ADP
ejpam-5015	197	6	posterior	posterior	ADJ
ejpam-5015	197	7	distributions	distribution	NOUN
ejpam-5015	197	8	we	we	PRON
ejpam-5015	197	9	first	first	ADV
ejpam-5015	197	10	reformulate	reformulate	VERB
ejpam-5015	197	11	the	the	DET
ejpam-5015	197	12	sum	sum	NOUN
ejpam-5015	197	13	of	of	ADP
ejpam-5015	197	14	residuals	residual	NOUN
ejpam-5015	197	15	using	use	VERB
ejpam-5015	197	16	some	some	DET
ejpam-5015	197	17	simple	simple	ADJ
ejpam-5015	197	18	algebraic	algebraic	ADJ
ejpam-5015	197	19	manipulations	manipulation	NOUN
ejpam-5015	197	20	as	as	ADP
ejpam-5015	197	21	:	:	PUNCT
ejpam-5015	197	22	r∑	r∑	ADJ
ejpam-5015	197	23	j=1	j=1	NOUN
ejpam-5015	197	24	(	(	PUNCT
ejpam-5015	197	25	yj(m	yj(m	NOUN
ejpam-5015	197	26	)	)	PUNCT
ejpam-5015	197	27	−	−	PROPN
ejpam-5015	197	28	β0	β0	ADJ
ejpam-5015	197	29	−	−	PROPN
ejpam-5015	197	30	β1xj	β1xj	PUNCT
ejpam-5015	197	31	)	)	PUNCT
ejpam-5015	197	32	2	2	NUM
ejpam-5015	197	33	=	=	SYM
ejpam-5015	197	34	r∑	r∑	NOUN
ejpam-5015	197	35	j=1	j=1	NOUN
ejpam-5015	197	36	(	(	PUNCT
ejpam-5015	197	37	yj(m	yj(m	NOUN
ejpam-5015	197	38	)	)	PUNCT
ejpam-5015	197	39	−	−	PROPN
ejpam-5015	197	40	β1xj	β1xj	PUNCT
ejpam-5015	198	1	−	−	PROPN
ejpam-5015	198	2	ȳm	ȳm	PROPN
ejpam-5015	198	3	+	+	SYM
ejpam-5015	198	4	β1x̄	β1x̄	NUM
ejpam-5015	198	5	)	)	PUNCT
ejpam-5015	198	6	2	2	NUM
ejpam-5015	198	7	+	+	NUM
ejpam-5015	198	8	r(ȳ	r(ȳ	PRON
ejpam-5015	198	9	−	−	PRON
ejpam-5015	198	10	β1x̄−	β1x̄−	ADJ
ejpam-5015	198	11	β0	β0	NOUN
ejpam-5015	198	12	)	)	PUNCT
ejpam-5015	198	13	2	2	NUM
ejpam-5015	198	14	(	(	PUNCT
ejpam-5015	198	15	31	31	NUM
ejpam-5015	198	16	)	)	PUNCT
ejpam-5015	198	17	then	then	ADV
ejpam-5015	198	18	the	the	DET
ejpam-5015	198	19	marginal	marginal	ADJ
ejpam-5015	198	20	conditional	conditional	ADJ
ejpam-5015	198	21	distribution	distribution	NOUN
ejpam-5015	198	22	of	of	ADP
ejpam-5015	198	23	β0	β0	NOUN
ejpam-5015	198	24	given	give	VERB
ejpam-5015	198	25	β1	β1	PROPN
ejpam-5015	198	26	,	,	PUNCT
ejpam-5015	198	27	σ	σ	PROPN
ejpam-5015	198	28	2	2	NUM
ejpam-5015	199	1	and	and	CCONJ
ejpam-5015	199	2	ym	ym	PRON
ejpam-5015	199	3	is	be	AUX
ejpam-5015	199	4	:	:	PUNCT
ejpam-5015	199	5	π1(β0	π1(β0	NUM
ejpam-5015	199	6	|	|	ADV
ejpam-5015	199	7	β1	β1	PROPN
ejpam-5015	199	8	,	,	PUNCT
ejpam-5015	199	9	σ2	σ2	PROPN
ejpam-5015	199	10	,	,	PUNCT
ejpam-5015	199	11	y	y	PROPN
ejpam-5015	199	12	m	m	PROPN
ejpam-5015	199	13	)	)	PUNCT
ejpam-5015	200	1	α×	α×	PUNCT
ejpam-5015	201	1	exp{−r(β0	exp{−r(β0	PROPN
ejpam-5015	202	1	−	−	PROPN
ejpam-5015	202	2	ȳ	ȳ	PROPN
ejpam-5015	202	3	+	+	CCONJ
ejpam-5015	202	4	β1x̄	β1x̄	X
ejpam-5015	202	5	)	)	PUNCT
ejpam-5015	202	6	2	2	NUM
ejpam-5015	202	7	2σ2	2σ2	NUM
ejpam-5015	202	8	−	−	NOUN
ejpam-5015	203	1	(	(	PUNCT
ejpam-5015	203	2	β0	β0	NOUN
ejpam-5015	203	3	−	−	PROPN
ejpam-5015	203	4	a)2	a)2	PROPN
ejpam-5015	203	5	2b2	2b2	NUM
ejpam-5015	203	6	×	×	PROPN
ejpam-5015	203	7	r∏	r∏	PROPN
ejpam-5015	204	1	j=1	j=1	PROPN
ejpam-5015	204	2	φ	φ	PROPN
ejpam-5015	204	3	(	(	PUNCT
ejpam-5015	204	4	yj(m	yj(m	NOUN
ejpam-5015	204	5	)	)	PUNCT
ejpam-5015	205	1	−	−	PROPN
ejpam-5015	205	2	β0	β0	NOUN
ejpam-5015	205	3	−	−	PROPN
ejpam-5015	205	4	β1xj	β1xj	PUNCT
ejpam-5015	205	5	σ	σ	NOUN
ejpam-5015	205	6	)	)	PUNCT
ejpam-5015	206	1	m−1	m−1	PROPN
ejpam-5015	206	2	×	×	NOUN
ejpam-5015	206	3	φ	φ	PROPN
ejpam-5015	206	4	(	(	PUNCT
ejpam-5015	206	5	−yj(m	−yj(m	PROPN
ejpam-5015	206	6	)	)	PUNCT
ejpam-5015	206	7	+	+	CCONJ
ejpam-5015	206	8	β0	β0	PROPN
ejpam-5015	206	9	+	+	CCONJ
ejpam-5015	206	10	β1xj	β1xj	PUNCT
ejpam-5015	206	11	σ	σ	NOUN
ejpam-5015	206	12	)	)	PUNCT
ejpam-5015	206	13	m−1	m−1	PROPN
ejpam-5015	206	14	,	,	PUNCT
ejpam-5015	206	15	αexp{−β2	αexp{−β2	ADV
ejpam-5015	206	16	0	0	NUM
ejpam-5015	206	17	2	2	NUM
ejpam-5015	206	18	(	(	PUNCT
ejpam-5015	206	19	r	r	NOUN
ejpam-5015	206	20	σ2	σ2	PROPN
ejpam-5015	206	21	+	+	CCONJ
ejpam-5015	206	22	1	1	NUM
ejpam-5015	206	23	b2	b2	NOUN
ejpam-5015	206	24	)	)	PUNCT
ejpam-5015	206	25	+	+	CCONJ
ejpam-5015	206	26	i.	i.	PROPN
ejpam-5015	206	27	nawajah	nawajah	PROPN
ejpam-5015	206	28	,	,	PUNCT
ejpam-5015	206	29	h.	h.	PROPN
ejpam-5015	206	30	kanj	kanj	PROPN
ejpam-5015	206	31	,	,	PUNCT
ejpam-5015	206	32	y.	y.	PROPN
ejpam-5015	206	33	kotb	kotb	PROPN
ejpam-5015	206	34	,	,	PUNCT
ejpam-5015	206	35	j.	j.	PROPN
ejpam-5015	206	36	hoxha	hoxha	PROPN
ejpam-5015	206	37	,	,	PUNCT
ejpam-5015	206	38	m.	m.	PROPN
ejpam-5015	206	39	alakkoumi	alakkoumi	PROPN
ejpam-5015	206	40	,	,	PUNCT
ejpam-5015	206	41	k.	k.	PROPN
ejpam-5015	206	42	jebreen	jebreen	PROPN
ejpam-5015	206	43	/	/	SYM
ejpam-5015	206	44	eur	eur	PROPN
ejpam-5015	206	45	.	.	PUNCT
ejpam-5015	207	1	j.	j.	PROPN
ejpam-5015	207	2	pure	pure	PROPN
ejpam-5015	207	3	appl	appl	PROPN
ejpam-5015	207	4	.	.	PROPN
ejpam-5015	207	5	math	math	PROPN
ejpam-5015	207	6	,	,	PUNCT
ejpam-5015	207	7	17	17	NUM
ejpam-5015	207	8	(	(	PUNCT
ejpam-5015	207	9	1	1	NUM
ejpam-5015	207	10	)	)	PUNCT
ejpam-5015	207	11	(	(	PUNCT
ejpam-5015	207	12	2024	2024	NUM
ejpam-5015	207	13	)	)	PUNCT
ejpam-5015	207	14	,	,	PUNCT
ejpam-5015	207	15	180	180	NUM
ejpam-5015	207	16	-	-	SYM
ejpam-5015	207	17	200	200	NUM
ejpam-5015	207	18	189	189	NUM
ejpam-5015	207	19	β0(r	β0(r	ADP
ejpam-5015	207	20	β1x̄−	β1x̄−	PROPN
ejpam-5015	207	21	ȳm	ȳm	PROPN
ejpam-5015	207	22	σ2	σ2	PROPN
ejpam-5015	207	23	+	+	CCONJ
ejpam-5015	207	24	a	a	DET
ejpam-5015	207	25	b2	b2	NOUN
ejpam-5015	207	26	)	)	PUNCT
ejpam-5015	207	27	}	}	PUNCT
ejpam-5015	207	28	×	×	NOUN
ejpam-5015	207	29	r∏	r∏	NOUN
ejpam-5015	207	30	j=1	j=1	PROPN
ejpam-5015	207	31	φ	φ	PROPN
ejpam-5015	207	32	(	(	PUNCT
ejpam-5015	207	33	yj(m	yj(m	NOUN
ejpam-5015	207	34	)	)	PUNCT
ejpam-5015	207	35	−	−	PROPN
ejpam-5015	207	36	β0	β0	NOUN
ejpam-5015	207	37	−	−	PROPN
ejpam-5015	207	38	β1xj	β1xj	PUNCT
ejpam-5015	207	39	σ	σ	NOUN
ejpam-5015	207	40	)	)	PUNCT
ejpam-5015	208	1	m−1	m−1	PROPN
ejpam-5015	208	2	×	×	NOUN
ejpam-5015	208	3	φ	φ	PROPN
ejpam-5015	208	4	(	(	PUNCT
ejpam-5015	208	5	−yj(m	−yj(m	PROPN
ejpam-5015	208	6	)	)	PUNCT
ejpam-5015	208	7	+	+	CCONJ
ejpam-5015	208	8	β0	β0	PROPN
ejpam-5015	208	9	+	+	CCONJ
ejpam-5015	208	10	β1xj	β1xj	PUNCT
ejpam-5015	208	11	σ	σ	NOUN
ejpam-5015	208	12	)	)	PUNCT
ejpam-5015	208	13	m−1	m−1	PROPN
ejpam-5015	208	14	,	,	PUNCT
ejpam-5015	208	15	(	(	PUNCT
ejpam-5015	208	16	32	32	NUM
ejpam-5015	208	17	)	)	PUNCT
ejpam-5015	208	18	this	this	DET
ejpam-5015	208	19	marginal	marginal	ADJ
ejpam-5015	208	20	posterior	posterior	ADJ
ejpam-5015	208	21	distribution	distribution	NOUN
ejpam-5015	208	22	represents	represent	VERB
ejpam-5015	208	23	our	our	PRON
ejpam-5015	208	24	updated	update	VERB
ejpam-5015	208	25	beliefs	belief	NOUN
ejpam-5015	208	26	about	about	ADP
ejpam-5015	208	27	the	the	DET
ejpam-5015	208	28	parameter	parameter	NOUN
ejpam-5015	208	29	β0	β0	PROPN
ejpam-5015	208	30	,	,	PUNCT
ejpam-5015	208	31	given	give	VERB
ejpam-5015	208	32	the	the	DET
ejpam-5015	208	33	observed	observe	VERB
ejpam-5015	208	34	data	datum	NOUN
ejpam-5015	208	35	and	and	CCONJ
ejpam-5015	208	36	the	the	DET
ejpam-5015	208	37	specified	specified	ADJ
ejpam-5015	208	38	values	value	NOUN
ejpam-5015	208	39	for	for	ADP
ejpam-5015	208	40	the	the	DET
ejpam-5015	208	41	other	other	ADJ
ejpam-5015	208	42	parameters	parameter	NOUN
ejpam-5015	208	43	.	.	PUNCT
ejpam-5015	209	1	after	after	ADP
ejpam-5015	209	2	some	some	DET
ejpam-5015	209	3	manipulations	manipulation	NOUN
ejpam-5015	209	4	we	we	PRON
ejpam-5015	209	5	compactly	compactly	ADV
ejpam-5015	209	6	write	write	VERB
ejpam-5015	209	7	it	it	PRON
ejpam-5015	209	8	as	as	ADP
ejpam-5015	209	9	:	:	PUNCT
ejpam-5015	209	10	π1(β0	π1(β0	NUM
ejpam-5015	209	11	|	|	ADV
ejpam-5015	209	12	β1	β1	PROPN
ejpam-5015	209	13	,	,	PUNCT
ejpam-5015	209	14	σ2	σ2	PROPN
ejpam-5015	209	15	,	,	PUNCT
ejpam-5015	209	16	y	y	PROPN
ejpam-5015	209	17	m	m	PROPN
ejpam-5015	209	18	)	)	PUNCT
ejpam-5015	209	19	αexp{−	αexp{−	NUM
ejpam-5015	209	20	(	(	PUNCT
ejpam-5015	209	21	r	r	NOUN
ejpam-5015	209	22	σ2	σ2	NOUN
ejpam-5015	209	23	+	+	CCONJ
ejpam-5015	209	24	1	1	NUM
ejpam-5015	209	25	¯	¯	SYM
ejpam-5015	209	26	2	2	NUM
ejpam-5015	209	27	)	)	PUNCT
ejpam-5015	209	28	2	2	NUM
ejpam-5015	209	29	×	×	NOUN
ejpam-5015	209	30	(	(	PUNCT
ejpam-5015	209	31	β0	β0	NOUN
ejpam-5015	209	32	−	−	PROPN
ejpam-5015	209	33	r	r	NOUN
ejpam-5015	209	34	β1x̄−ȳm	β1x̄−ȳm	NUM
ejpam-5015	209	35	σ2	σ2	PROPN
ejpam-5015	209	36	+	+	CCONJ
ejpam-5015	209	37	a	a	DET
ejpam-5015	209	38	b2	b2	NOUN
ejpam-5015	209	39	r	r	NOUN
ejpam-5015	209	40	σ2	σ2	NOUN
ejpam-5015	209	41	+	+	CCONJ
ejpam-5015	209	42	1	1	NUM
ejpam-5015	209	43	b2	b2	NOUN
ejpam-5015	209	44	)	)	PUNCT
ejpam-5015	209	45	2	2	NUM
ejpam-5015	209	46	}	}	PUNCT
ejpam-5015	209	47	×	×	NOUN
ejpam-5015	210	1	r∏	r∏	NOUN
ejpam-5015	210	2	j=1	j=1	PROPN
ejpam-5015	210	3	φ	φ	PROPN
ejpam-5015	210	4	(	(	PUNCT
ejpam-5015	210	5	yj(m	yj(m	NOUN
ejpam-5015	210	6	)	)	PUNCT
ejpam-5015	210	7	−	−	PROPN
ejpam-5015	211	1	β0	β0	NOUN
ejpam-5015	211	2	−	−	PROPN
ejpam-5015	211	3	β1xj	β1xj	PUNCT
ejpam-5015	211	4	σ	σ	NOUN
ejpam-5015	211	5	)	)	PUNCT
ejpam-5015	212	1	m−1	m−1	PROPN
ejpam-5015	212	2	×	×	NOUN
ejpam-5015	212	3	φ	φ	PROPN
ejpam-5015	212	4	(	(	PUNCT
ejpam-5015	212	5	−yj(m	−yj(m	PROPN
ejpam-5015	212	6	)	)	PUNCT
ejpam-5015	212	7	+	+	CCONJ
ejpam-5015	212	8	β0	β0	PROPN
ejpam-5015	212	9	+	+	CCONJ
ejpam-5015	212	10	β1xj	β1xj	PUNCT
ejpam-5015	212	11	σ	σ	NOUN
ejpam-5015	212	12	)	)	PUNCT
ejpam-5015	212	13	m−1	m−1	PROPN
ejpam-5015	212	14	.	.	PUNCT
ejpam-5015	213	1	(	(	PUNCT
ejpam-5015	213	2	33	33	NUM
ejpam-5015	213	3	)	)	PUNCT
ejpam-5015	213	4	we	we	PRON
ejpam-5015	213	5	can	can	AUX
ejpam-5015	213	6	easily	easily	ADV
ejpam-5015	213	7	identify	identify	VERB
ejpam-5015	213	8	two	two	NUM
ejpam-5015	213	9	terms	term	NOUN
ejpam-5015	213	10	;	;	PUNCT
ejpam-5015	213	11	the	the	DET
ejpam-5015	213	12	first	first	ADJ
ejpam-5015	213	13	one	one	NOUN
ejpam-5015	213	14	is	be	AUX
ejpam-5015	213	15	the	the	DET
ejpam-5015	213	16	gaussian	gaussian	ADJ
ejpam-5015	213	17	likelihood	likelihood	NOUN
ejpam-5015	213	18	function	function	NOUN
ejpam-5015	213	19	with	with	ADP
ejpam-5015	213	20	the	the	DET
ejpam-5015	213	21	required	require	VERB
ejpam-5015	213	22	adjustment	adjustment	NOUN
ejpam-5015	213	23	for	for	ADP
ejpam-5015	213	24	the	the	DET
ejpam-5015	213	25	prior	prior	ADJ
ejpam-5015	213	26	belief	belief	NOUN
ejpam-5015	213	27	about	about	ADP
ejpam-5015	213	28	the	the	DET
ejpam-5015	213	29	parameter	parameter	NOUN
ejpam-5015	213	30	β0	β0	PROPN
ejpam-5015	213	31	;	;	PUNCT
ejpam-5015	213	32	second	second	ADJ
ejpam-5015	213	33	term	term	NOUN
ejpam-5015	213	34	used	use	VERB
ejpam-5015	213	35	to	to	PART
ejpam-5015	213	36	capture	capture	VERB
ejpam-5015	213	37	the	the	DET
ejpam-5015	213	38	cumulative	cumulative	ADJ
ejpam-5015	213	39	distribution	distribution	NOUN
ejpam-5015	213	40	of	of	ADP
ejpam-5015	213	41	the	the	DET
ejpam-5015	213	42	residuals	residual	NOUN
ejpam-5015	213	43	.	.	PUNCT
ejpam-5015	214	1	overall	overall	ADV
ejpam-5015	214	2	,	,	PUNCT
ejpam-5015	214	3	this	this	DET
ejpam-5015	214	4	expression	expression	NOUN
ejpam-5015	214	5	models	model	NOUN
ejpam-5015	214	6	how	how	SCONJ
ejpam-5015	214	7	the	the	DET
ejpam-5015	214	8	residuals	residual	NOUN
ejpam-5015	214	9	are	be	AUX
ejpam-5015	214	10	distributed	distribute	VERB
ejpam-5015	214	11	around	around	ADP
ejpam-5015	214	12	the	the	DET
ejpam-5015	214	13	model	model	NOUN
ejpam-5015	214	14	fit	fit	NOUN
ejpam-5015	214	15	and	and	CCONJ
ejpam-5015	214	16	combines	combine	VERB
ejpam-5015	214	17	this	this	PRON
ejpam-5015	214	18	with	with	ADP
ejpam-5015	214	19	prior	prior	ADJ
ejpam-5015	214	20	information	information	NOUN
ejpam-5015	214	21	and	and	CCONJ
ejpam-5015	214	22	likelihood	likelihood	NOUN
ejpam-5015	214	23	derived	derive	VERB
ejpam-5015	214	24	from	from	ADP
ejpam-5015	214	25	the	the	DET
ejpam-5015	214	26	data	datum	NOUN
ejpam-5015	214	27	to	to	PART
ejpam-5015	214	28	give	give	VERB
ejpam-5015	214	29	a	a	DET
ejpam-5015	214	30	posterior	posterior	ADJ
ejpam-5015	214	31	belief	belief	NOUN
ejpam-5015	214	32	about	about	ADP
ejpam-5015	214	33	β0	β0	PROPN
ejpam-5015	214	34	.	.	PUNCT
ejpam-5015	214	35	i.	i.	PROPN
ejpam-5015	214	36	nawajah	nawajah	PROPN
ejpam-5015	214	37	,	,	PUNCT
ejpam-5015	214	38	h.	h.	PROPN
ejpam-5015	214	39	kanj	kanj	PROPN
ejpam-5015	214	40	,	,	PUNCT
ejpam-5015	214	41	y.	y.	PROPN
ejpam-5015	214	42	kotb	kotb	PROPN
ejpam-5015	214	43	,	,	PUNCT
ejpam-5015	214	44	j.	j.	PROPN
ejpam-5015	214	45	hoxha	hoxha	PROPN
ejpam-5015	214	46	,	,	PUNCT
ejpam-5015	214	47	m.	m.	PROPN
ejpam-5015	214	48	alakkoumi	alakkoumi	PROPN
ejpam-5015	214	49	,	,	PUNCT
ejpam-5015	214	50	k.	k.	PROPN
ejpam-5015	214	51	jebreen	jebreen	PROPN
ejpam-5015	214	52	/	/	SYM
ejpam-5015	214	53	eur	eur	PROPN
ejpam-5015	214	54	.	.	PUNCT
ejpam-5015	215	1	j.	j.	PROPN
ejpam-5015	215	2	pure	pure	PROPN
ejpam-5015	215	3	appl	appl	PROPN
ejpam-5015	215	4	.	.	PROPN
ejpam-5015	215	5	math	math	PROPN
ejpam-5015	215	6	,	,	PUNCT
ejpam-5015	215	7	17	17	NUM
ejpam-5015	215	8	(	(	PUNCT
ejpam-5015	215	9	1	1	NUM
ejpam-5015	215	10	)	)	PUNCT
ejpam-5015	215	11	(	(	PUNCT
ejpam-5015	215	12	2024	2024	NUM
ejpam-5015	215	13	)	)	PUNCT
ejpam-5015	215	14	,	,	PUNCT
ejpam-5015	215	15	180	180	NUM
ejpam-5015	215	16	-	-	SYM
ejpam-5015	215	17	200	200	NUM
ejpam-5015	215	18	190	190	NUM
ejpam-5015	215	19	the	the	DET
ejpam-5015	215	20	conditional	conditional	ADJ
ejpam-5015	215	21	distribution	distribution	NOUN
ejpam-5015	215	22	for	for	ADP
ejpam-5015	215	23	β1	β1	PROPN
ejpam-5015	215	24	given	give	VERB
ejpam-5015	215	25	β0	β0	PROPN
ejpam-5015	215	26	,	,	PUNCT
ejpam-5015	215	27	σ	σ	PROPN
ejpam-5015	215	28	2	2	NUM
ejpam-5015	216	1	and	and	CCONJ
ejpam-5015	216	2	ym	ym	PRON
ejpam-5015	216	3	is	be	AUX
ejpam-5015	216	4	:	:	PUNCT
ejpam-5015	216	5	π2(β1	π2(β1	VERB
ejpam-5015	216	6	|	|	ADV
ejpam-5015	216	7	β0	β0	NOUN
ejpam-5015	216	8	,	,	PUNCT
ejpam-5015	216	9	σ2	σ2	PROPN
ejpam-5015	216	10	,	,	PUNCT
ejpam-5015	216	11	y	y	PROPN
ejpam-5015	216	12	m	m	PROPN
ejpam-5015	216	13	)	)	PUNCT
ejpam-5015	217	1	α	α	PROPN
ejpam-5015	217	2	exp	exp	NOUN
ejpam-5015	217	3	{	{	PUNCT
ejpam-5015	217	4	−	−	PROPN
ejpam-5015	217	5	∑r	∑r	PROPN
ejpam-5015	217	6	j=1(yj(m	j=1(yj(m	NOUN
ejpam-5015	217	7	)	)	PUNCT
ejpam-5015	217	8	−	−	PROPN
ejpam-5015	217	9	β0	β0	ADJ
ejpam-5015	217	10	−	−	PROPN
ejpam-5015	217	11	β1xj	β1xj	PUNCT
ejpam-5015	217	12	)	)	PUNCT
ejpam-5015	217	13	2	2	NUM
ejpam-5015	217	14	2σ2	2σ2	NUM
ejpam-5015	217	15	}	}	PUNCT
ejpam-5015	217	16	×	×	NOUN
ejpam-5015	217	17	exp	exp	NOUN
ejpam-5015	217	18	{	{	PUNCT
ejpam-5015	217	19	−(β1	−(β1	NUM
ejpam-5015	217	20	−	−	PRON
ejpam-5015	217	21	δ)2	δ)2	PROPN
ejpam-5015	217	22	2g2	2g2	NUM
ejpam-5015	217	23	}	}	PUNCT
ejpam-5015	217	24	×	×	NOUN
ejpam-5015	217	25	r∏	r∏	NOUN
ejpam-5015	218	1	j=1	j=1	NOUN
ejpam-5015	219	1	[	[	PUNCT
ejpam-5015	219	2	φ	φ	X
ejpam-5015	219	3	(	(	PUNCT
ejpam-5015	219	4	yj(m	yj(m	NOUN
ejpam-5015	219	5	)	)	PUNCT
ejpam-5015	219	6	−	−	PROPN
ejpam-5015	220	1	β0	β0	NOUN
ejpam-5015	220	2	−	−	PROPN
ejpam-5015	220	3	β1xj	β1xj	PUNCT
ejpam-5015	220	4	σ	σ	NOUN
ejpam-5015	220	5	)	)	PUNCT
ejpam-5015	221	1	m−1	m−1	PROPN
ejpam-5015	221	2	×	×	PROPN
ejpam-5015	221	3	φ	φ	PROPN
ejpam-5015	221	4	(	(	PUNCT
ejpam-5015	221	5	−yj(m	−yj(m	PROPN
ejpam-5015	221	6	)	)	PUNCT
ejpam-5015	221	7	+	+	CCONJ
ejpam-5015	221	8	β0	β0	PROPN
ejpam-5015	221	9	+	+	CCONJ
ejpam-5015	221	10	β1xj	β1xj	PUNCT
ejpam-5015	221	11	σ	σ	NOUN
ejpam-5015	221	12	)	)	PUNCT
ejpam-5015	222	1	m−1	m−1	PROPN
ejpam-5015	222	2	]	]	PUNCT
ejpam-5015	222	3	α	α	X
ejpam-5015	222	4	exp	exp	NOUN
ejpam-5015	222	5	{	{	PUNCT
ejpam-5015	222	6	−2	−2	NOUN
ejpam-5015	222	7	∑r	∑r	PROPN
ejpam-5015	222	8	j=1	j=1	PROPN
ejpam-5015	222	9	xj(yj(m	xj(yj(m	PROPN
ejpam-5015	222	10	)	)	PUNCT
ejpam-5015	223	1	−	−	ADP
ejpam-5015	223	2	β0)β1	β0)β1	NOUN
ejpam-5015	223	3	2σ2	2σ2	NUM
ejpam-5015	223	4	}	}	PUNCT
ejpam-5015	223	5	×	×	NOUN
ejpam-5015	223	6	exp	exp	NOUN
ejpam-5015	223	7	{	{	PUNCT
ejpam-5015	223	8	−	−	PROPN
ejpam-5015	224	1	β2	β2	NOUN
ejpam-5015	224	2	1	1	NUM
ejpam-5015	224	3	∑r	∑r	PROPN
ejpam-5015	224	4	j=1	j=1	NOUN
ejpam-5015	224	5	x	x	SYM
ejpam-5015	224	6	2	2	NUM
ejpam-5015	224	7	j	j	NOUN
ejpam-5015	224	8	2σ2	2σ2	NUM
ejpam-5015	224	9	}	}	PUNCT
ejpam-5015	224	10	×	×	NOUN
ejpam-5015	224	11	exp	exp	NOUN
ejpam-5015	224	12	{	{	PUNCT
ejpam-5015	224	13	−	−	PROPN
ejpam-5015	224	14	β2	β2	NOUN
ejpam-5015	224	15	1	1	NUM
ejpam-5015	224	16	2g2	2g2	NUM
ejpam-5015	224	17	+	+	CCONJ
ejpam-5015	224	18	δβ1	δβ1	PROPN
ejpam-5015	224	19	g2	g2	PROPN
ejpam-5015	224	20	}	}	PUNCT
ejpam-5015	224	21	×	×	NOUN
ejpam-5015	225	1	r∏	r∏	NOUN
ejpam-5015	225	2	j=1	j=1	NOUN
ejpam-5015	225	3	[	[	PUNCT
ejpam-5015	225	4	φ	φ	X
ejpam-5015	225	5	(	(	PUNCT
ejpam-5015	225	6	yj(m	yj(m	NOUN
ejpam-5015	225	7	)	)	PUNCT
ejpam-5015	225	8	−	−	PROPN
ejpam-5015	226	1	β0	β0	NOUN
ejpam-5015	226	2	−	−	PROPN
ejpam-5015	226	3	β1xj	β1xj	PUNCT
ejpam-5015	226	4	σ	σ	NOUN
ejpam-5015	226	5	)	)	PUNCT
ejpam-5015	227	1	m−1	m−1	PROPN
ejpam-5015	227	2	×	×	PROPN
ejpam-5015	227	3	φ	φ	PROPN
ejpam-5015	227	4	(	(	PUNCT
ejpam-5015	227	5	−yj(m	−yj(m	PROPN
ejpam-5015	227	6	)	)	PUNCT
ejpam-5015	227	7	+	+	CCONJ
ejpam-5015	227	8	β0	β0	PROPN
ejpam-5015	227	9	+	+	CCONJ
ejpam-5015	227	10	β1xj	β1xj	PUNCT
ejpam-5015	227	11	σ	σ	NOUN
ejpam-5015	227	12	)	)	PUNCT
ejpam-5015	227	13	m−1	m−1	PROPN
ejpam-5015	227	14	]	]	PUNCT
ejpam-5015	227	15	.	.	PUNCT
ejpam-5015	228	1	(	(	PUNCT
ejpam-5015	228	2	34	34	NUM
ejpam-5015	228	3	)	)	PUNCT
ejpam-5015	228	4	i.	i.	PROPN
ejpam-5015	228	5	nawajah	nawajah	PROPN
ejpam-5015	228	6	,	,	PUNCT
ejpam-5015	228	7	h.	h.	PROPN
ejpam-5015	228	8	kanj	kanj	PROPN
ejpam-5015	228	9	,	,	PUNCT
ejpam-5015	228	10	y.	y.	PROPN
ejpam-5015	228	11	kotb	kotb	PROPN
ejpam-5015	228	12	,	,	PUNCT
ejpam-5015	228	13	j.	j.	PROPN
ejpam-5015	228	14	hoxha	hoxha	PROPN
ejpam-5015	228	15	,	,	PUNCT
ejpam-5015	228	16	m.	m.	PROPN
ejpam-5015	228	17	alakkoumi	alakkoumi	PROPN
ejpam-5015	228	18	,	,	PUNCT
ejpam-5015	228	19	k.	k.	PROPN
ejpam-5015	229	1	jebreen	jebreen	PROPN
ejpam-5015	229	2	/	/	SYM
ejpam-5015	229	3	eur	eur	PROPN
ejpam-5015	229	4	.	.	PUNCT
ejpam-5015	230	1	j.	j.	PROPN
ejpam-5015	230	2	pure	pure	PROPN
ejpam-5015	230	3	appl	appl	PROPN
ejpam-5015	230	4	.	.	PROPN
ejpam-5015	230	5	math	math	PROPN
ejpam-5015	230	6	,	,	PUNCT
ejpam-5015	230	7	17	17	NUM
ejpam-5015	230	8	(	(	PUNCT
ejpam-5015	230	9	1	1	NUM
ejpam-5015	230	10	)	)	PUNCT
ejpam-5015	230	11	(	(	PUNCT
ejpam-5015	230	12	2024	2024	NUM
ejpam-5015	230	13	)	)	PUNCT
ejpam-5015	230	14	,	,	PUNCT
ejpam-5015	230	15	180	180	NUM
ejpam-5015	230	16	-	-	SYM
ejpam-5015	230	17	200	200	NUM
ejpam-5015	230	18	191	191	NUM
ejpam-5015	230	19	by	by	ADP
ejpam-5015	230	20	some	some	DET
ejpam-5015	230	21	simplification	simplification	NOUN
ejpam-5015	230	22	,	,	PUNCT
ejpam-5015	230	23	π2(β1	π2(β1	VERB
ejpam-5015	230	24	|	|	ADV
ejpam-5015	230	25	β0	β0	NOUN
ejpam-5015	230	26	,	,	PUNCT
ejpam-5015	230	27	σ2	σ2	PROPN
ejpam-5015	230	28	,	,	PUNCT
ejpam-5015	230	29	y	y	PROPN
ejpam-5015	230	30	m	m	PROPN
ejpam-5015	230	31	)	)	PUNCT
ejpam-5015	231	1	α	α	PROPN
ejpam-5015	231	2	exp	exp	NOUN
ejpam-5015	231	3	{	{	PUNCT
ejpam-5015	231	4	−β2	−β2	PROPN
ejpam-5015	231	5	2	2	NUM
ejpam-5015	231	6	2	2	NUM
ejpam-5015	231	7	(	(	PUNCT
ejpam-5015	231	8	∑r	∑r	NOUN
ejpam-5015	231	9	j=1	j=1	NOUN
ejpam-5015	231	10	x	x	SYM
ejpam-5015	231	11	2	2	NUM
ejpam-5015	231	12	j	j	PROPN
ejpam-5015	231	13	σ2	σ2	PROPN
ejpam-5015	231	14	+	+	CCONJ
ejpam-5015	231	15	1	1	NUM
ejpam-5015	231	16	g2	g2	PROPN
ejpam-5015	231	17	)	)	PUNCT
ejpam-5015	232	1	+	+	CCONJ
ejpam-5015	232	2	(	(	PUNCT
ejpam-5015	232	3	β2	β2	VERB
ejpam-5015	232	4	1	1	NUM
ejpam-5015	232	5	∑r	∑r	PROPN
ejpam-5015	232	6	j=1	j=1	NOUN
ejpam-5015	232	7	x	x	SYM
ejpam-5015	232	8	2	2	NUM
ejpam-5015	232	9	j	j	PROPN
ejpam-5015	232	10	σ2	σ2	PROPN
ejpam-5015	232	11	+	+	PROPN
ejpam-5015	232	12	δ	δ	PROPN
ejpam-5015	232	13	g2	g2	PROPN
ejpam-5015	232	14	)	)	PUNCT
ejpam-5015	233	1	β1	β1	PROPN
ejpam-5015	233	2	}	}	PUNCT
ejpam-5015	234	1	×	×	NOUN
ejpam-5015	234	2	r∏	r∏	NOUN
ejpam-5015	234	3	j=1	j=1	NOUN
ejpam-5015	234	4	[	[	PUNCT
ejpam-5015	234	5	φ	φ	X
ejpam-5015	234	6	(	(	PUNCT
ejpam-5015	234	7	yj(m	yj(m	NOUN
ejpam-5015	234	8	)	)	PUNCT
ejpam-5015	234	9	−	−	PROPN
ejpam-5015	235	1	β0	β0	NOUN
ejpam-5015	235	2	−	−	PROPN
ejpam-5015	235	3	β1xj	β1xj	PUNCT
ejpam-5015	235	4	σ	σ	NOUN
ejpam-5015	235	5	)	)	PUNCT
ejpam-5015	235	6	m−1	m−1	PROPN
ejpam-5015	235	7	×φ	×φ	PROPN
ejpam-5015	235	8	(	(	PUNCT
ejpam-5015	235	9	−yj(m	−yj(m	PROPN
ejpam-5015	235	10	)	)	PUNCT
ejpam-5015	235	11	+	+	CCONJ
ejpam-5015	235	12	β0	β0	PROPN
ejpam-5015	235	13	+	+	CCONJ
ejpam-5015	235	14	β1xj	β1xj	PUNCT
ejpam-5015	235	15	σ	σ	NOUN
ejpam-5015	235	16	)	)	PUNCT
ejpam-5015	235	17	m−1	m−1	PROPN
ejpam-5015	235	18	]	]	PUNCT
ejpam-5015	235	19	α	α	PRON
ejpam-5015	235	20	exp	exp	NOUN
ejpam-5015	235	21	−	−	NOUN
ejpam-5015	235	22	∑r	∑r	PROPN
ejpam-5015	236	1	j=1	j=1	NOUN
ejpam-5015	236	2	x	x	X
ejpam-5015	236	3	2	2	NUM
ejpam-5015	236	4	j	j	PROPN
ejpam-5015	236	5	σ2	σ2	PROPN
ejpam-5015	236	6	+	+	CCONJ
ejpam-5015	236	7	1	1	NUM
ejpam-5015	236	8	g2	g2	PROPN
ejpam-5015	236	9	2	2	NUM
ejpam-5015	236	10	+	+	NOUN
ejpam-5015	236	11	β1	β1	NUM
ejpam-5015	236	12	−	−	PROPN
ejpam-5015	237	1	∑r	∑r	PROPN
ejpam-5015	237	2	j=1	j=1	PROPN
ejpam-5015	237	3	xj(yj(m)−β0	xj(yj(m)−β0	PUNCT
ejpam-5015	237	4	)	)	PUNCT
ejpam-5015	237	5	σ2	σ2	PROPN
ejpam-5015	237	6	+	+	CCONJ
ejpam-5015	237	7	δ	δ	PROPN
ejpam-5015	237	8	g2∑r	g2∑r	VERB
ejpam-5015	237	9	j=1	j=1	NOUN
ejpam-5015	237	10	x	x	SYM
ejpam-5015	237	11	2	2	NUM
ejpam-5015	237	12	j	j	PROPN
ejpam-5015	237	13	σ2	σ2	PROPN
ejpam-5015	237	14	+	+	CCONJ
ejpam-5015	237	15	1	1	NUM
ejpam-5015	237	16	g2	g2	PROPN
ejpam-5015	237	17	2	2	NOUN
ejpam-5015	237	18			PRON
ejpam-5015	237	19	×	×	PROPN
ejpam-5015	238	1	r∏	r∏	PROPN
ejpam-5015	238	2	j=1	j=1	NOUN
ejpam-5015	238	3	[	[	PUNCT
ejpam-5015	238	4	φ	φ	X
ejpam-5015	238	5	(	(	PUNCT
ejpam-5015	238	6	yj(m	yj(m	NOUN
ejpam-5015	238	7	)	)	PUNCT
ejpam-5015	238	8	−	−	PROPN
ejpam-5015	239	1	β0	β0	NOUN
ejpam-5015	239	2	−	−	PROPN
ejpam-5015	239	3	β1xj	β1xj	PUNCT
ejpam-5015	239	4	σ	σ	NOUN
ejpam-5015	239	5	)	)	PUNCT
ejpam-5015	239	6	m−1	m−1	PROPN
ejpam-5015	239	7	×φ	×φ	PROPN
ejpam-5015	239	8	(	(	PUNCT
ejpam-5015	239	9	−yj(m	−yj(m	PROPN
ejpam-5015	239	10	)	)	PUNCT
ejpam-5015	239	11	+	+	CCONJ
ejpam-5015	239	12	β0	β0	PROPN
ejpam-5015	239	13	+	+	CCONJ
ejpam-5015	239	14	β1xj	β1xj	PUNCT
ejpam-5015	239	15	σ	σ	NOUN
ejpam-5015	239	16	)	)	PUNCT
ejpam-5015	239	17	m−1	m−1	PROPN
ejpam-5015	239	18	]	]	PUNCT
ejpam-5015	239	19	.	.	PUNCT
ejpam-5015	240	1	(	(	PUNCT
ejpam-5015	240	2	35	35	NUM
ejpam-5015	240	3	)	)	PUNCT
ejpam-5015	240	4	and	and	CCONJ
ejpam-5015	240	5	finally	finally	ADV
ejpam-5015	240	6	we	we	PRON
ejpam-5015	240	7	have	have	VERB
ejpam-5015	240	8	that	that	PRON
ejpam-5015	240	9	:	:	PUNCT
ejpam-5015	240	10	π2(β1	π2(β1	VERB
ejpam-5015	240	11	|	|	ADV
ejpam-5015	240	12	β0	β0	NOUN
ejpam-5015	240	13	,	,	PUNCT
ejpam-5015	240	14	σ2	σ2	PROPN
ejpam-5015	240	15	,	,	PUNCT
ejpam-5015	240	16	y	y	PROPN
ejpam-5015	240	17	m	m	PROPN
ejpam-5015	240	18	)	)	PUNCT
ejpam-5015	241	1	α	α	PRON
ejpam-5015	241	2	exp	exp	NOUN
ejpam-5015	241	3	−	−	NOUN
ejpam-5015	241	4	∑r	∑r	PROPN
ejpam-5015	242	1	j=1	j=1	NOUN
ejpam-5015	242	2	x	x	X
ejpam-5015	242	3	2	2	NUM
ejpam-5015	242	4	j	j	PROPN
ejpam-5015	242	5	σ2	σ2	PROPN
ejpam-5015	242	6	+	+	CCONJ
ejpam-5015	242	7	1	1	NUM
ejpam-5015	242	8	g2	g2	PROPN
ejpam-5015	242	9	2	2	NUM
ejpam-5015	242	10	+	+	NOUN
ejpam-5015	242	11	β1	β1	NUM
ejpam-5015	242	12	−	−	PROPN
ejpam-5015	243	1	∑r	∑r	PROPN
ejpam-5015	243	2	j=1	j=1	PROPN
ejpam-5015	243	3	xj(yj(m)−β0	xj(yj(m)−β0	PUNCT
ejpam-5015	243	4	)	)	PUNCT
ejpam-5015	243	5	σ2	σ2	NOUN
ejpam-5015	243	6	+	+	CCONJ
ejpam-5015	243	7	σ2δ	σ2δ	PROPN
ejpam-5015	243	8	g2∑r	g2∑r	VERB
ejpam-5015	243	9	j=1	j=1	NOUN
ejpam-5015	243	10	x	x	PUNCT
ejpam-5015	243	11	2	2	NUM
ejpam-5015	243	12	j	j	PROPN
ejpam-5015	243	13	+	+	PROPN
ejpam-5015	243	14	σ2	σ2	PROPN
ejpam-5015	243	15	g2	g2	PROPN
ejpam-5015	243	16	2	2	NUM
ejpam-5015	243	17			ADP
ejpam-5015	244	1	×	×	PROPN
ejpam-5015	245	1	r∏	r∏	PROPN
ejpam-5015	246	1	j=1	j=1	NOUN
ejpam-5015	247	1	[	[	PUNCT
ejpam-5015	247	2	φ	φ	X
ejpam-5015	247	3	(	(	PUNCT
ejpam-5015	247	4	yj(m	yj(m	NOUN
ejpam-5015	247	5	)	)	PUNCT
ejpam-5015	247	6	−	−	PROPN
ejpam-5015	248	1	β0	β0	NOUN
ejpam-5015	248	2	−	−	PROPN
ejpam-5015	248	3	β1xj	β1xj	PUNCT
ejpam-5015	248	4	σ	σ	NOUN
ejpam-5015	248	5	)	)	PUNCT
ejpam-5015	248	6	m−1	m−1	PROPN
ejpam-5015	248	7	×φ	×φ	PROPN
ejpam-5015	248	8	(	(	PUNCT
ejpam-5015	248	9	−yj(m	−yj(m	PROPN
ejpam-5015	248	10	)	)	PUNCT
ejpam-5015	248	11	+	+	CCONJ
ejpam-5015	248	12	β0	β0	PROPN
ejpam-5015	248	13	+	+	CCONJ
ejpam-5015	248	14	β1xj	β1xj	PUNCT
ejpam-5015	248	15	σ	σ	NOUN
ejpam-5015	248	16	)	)	PUNCT
ejpam-5015	248	17	m−1	m−1	PROPN
ejpam-5015	248	18	]	]	PUNCT
ejpam-5015	248	19	.	.	PUNCT
ejpam-5015	249	1	(	(	PUNCT
ejpam-5015	249	2	36	36	NUM
ejpam-5015	249	3	)	)	PUNCT
ejpam-5015	249	4	the	the	DET
ejpam-5015	249	5	conditional	conditional	ADJ
ejpam-5015	249	6	distribution	distribution	NOUN
ejpam-5015	249	7	of	of	ADP
ejpam-5015	249	8	σ2	σ2	NOUN
ejpam-5015	249	9	given	give	VERB
ejpam-5015	249	10	β0	β0	PROPN
ejpam-5015	249	11	,	,	PUNCT
ejpam-5015	249	12	β1	β1	PROPN
ejpam-5015	249	13	and	and	CCONJ
ejpam-5015	249	14	ym	ym	PROPN
ejpam-5015	249	15	is	be	AUX
ejpam-5015	249	16	given	give	VERB
ejpam-5015	249	17	in	in	ADP
ejpam-5015	249	18	the	the	DET
ejpam-5015	249	19	simplified	simplified	ADJ
ejpam-5015	249	20	compact	compact	ADJ
ejpam-5015	249	21	i.	i.	PROPN
ejpam-5015	249	22	nawajah	nawajah	PROPN
ejpam-5015	249	23	,	,	PUNCT
ejpam-5015	249	24	h.	h.	PROPN
ejpam-5015	249	25	kanj	kanj	PROPN
ejpam-5015	249	26	,	,	PUNCT
ejpam-5015	249	27	y.	y.	PROPN
ejpam-5015	249	28	kotb	kotb	PROPN
ejpam-5015	249	29	,	,	PUNCT
ejpam-5015	249	30	j.	j.	PROPN
ejpam-5015	249	31	hoxha	hoxha	PROPN
ejpam-5015	249	32	,	,	PUNCT
ejpam-5015	249	33	m.	m.	PROPN
ejpam-5015	249	34	alakkoumi	alakkoumi	PROPN
ejpam-5015	249	35	,	,	PUNCT
ejpam-5015	249	36	k.	k.	PROPN
ejpam-5015	249	37	jebreen	jebreen	PROPN
ejpam-5015	249	38	/	/	SYM
ejpam-5015	249	39	eur	eur	PROPN
ejpam-5015	249	40	.	.	PUNCT
ejpam-5015	250	1	j.	j.	PROPN
ejpam-5015	250	2	pure	pure	PROPN
ejpam-5015	250	3	appl	appl	PROPN
ejpam-5015	250	4	.	.	PROPN
ejpam-5015	250	5	math	math	PROPN
ejpam-5015	250	6	,	,	PUNCT
ejpam-5015	250	7	17	17	NUM
ejpam-5015	250	8	(	(	PUNCT
ejpam-5015	250	9	1	1	NUM
ejpam-5015	250	10	)	)	PUNCT
ejpam-5015	250	11	(	(	PUNCT
ejpam-5015	250	12	2024	2024	NUM
ejpam-5015	250	13	)	)	PUNCT
ejpam-5015	250	14	,	,	PUNCT
ejpam-5015	250	15	180	180	NUM
ejpam-5015	250	16	-	-	SYM
ejpam-5015	250	17	200	200	NUM
ejpam-5015	250	18	192	192	NUM
ejpam-5015	250	19	form	form	NOUN
ejpam-5015	250	20	as	as	ADP
ejpam-5015	250	21	:	:	PUNCT
ejpam-5015	250	22	π3(σ	π3(σ	NUM
ejpam-5015	250	23	2	2	NUM
ejpam-5015	250	24	|	|	ADV
ejpam-5015	250	25	β0	β0	NOUN
ejpam-5015	250	26	,	,	PUNCT
ejpam-5015	250	27	β1	β1	PROPN
ejpam-5015	250	28	,	,	PUNCT
ejpam-5015	250	29	ym	ym	PROPN
ejpam-5015	250	30	)	)	PUNCT
ejpam-5015	250	31	α	α	PROPN
ejpam-5015	250	32	1	1	NUM
ejpam-5015	250	33	(	(	PUNCT
ejpam-5015	250	34	σ2	σ2	NOUN
ejpam-5015	250	35	)	)	PUNCT
ejpam-5015	250	36	r	r	NOUN
ejpam-5015	250	37	2	2	NUM
ejpam-5015	250	38	+	+	NOUN
ejpam-5015	250	39	α+1	α+1	NUM
ejpam-5015	250	40	×	×	NOUN
ejpam-5015	250	41	exp	exp	NOUN
ejpam-5015	250	42			PUNCT
ejpam-5015	250	43	−	−	PROPN
ejpam-5015	250	44	∑r	∑r	PROPN
ejpam-5015	250	45	j=1(yj(m)−β0−β1xj	j=1(yj(m)−β0−β1xj	NOUN
ejpam-5015	250	46	)	)	PUNCT
ejpam-5015	250	47	2	2	NUM
ejpam-5015	250	48	2	2	NUM
ejpam-5015	250	49	+	+	NUM
ejpam-5015	250	50	1	1	NUM
ejpam-5015	250	51	β	β	NOUN
ejpam-5015	250	52	σ2	σ2	NOUN
ejpam-5015	250	53			PROPN
ejpam-5015	250	54	×	×	PROPN
ejpam-5015	250	55	r∏	r∏	NOUN
ejpam-5015	250	56	j=1	j=1	NOUN
ejpam-5015	251	1	[	[	PUNCT
ejpam-5015	251	2	φ	φ	X
ejpam-5015	251	3	(	(	PUNCT
ejpam-5015	251	4	yj(m	yj(m	NOUN
ejpam-5015	251	5	)	)	PUNCT
ejpam-5015	251	6	−	−	PROPN
ejpam-5015	252	1	β0	β0	NOUN
ejpam-5015	252	2	−	−	PROPN
ejpam-5015	252	3	β1xj	β1xj	PUNCT
ejpam-5015	252	4	σ	σ	NOUN
ejpam-5015	252	5	)	)	PUNCT
ejpam-5015	252	6	m−1	m−1	PROPN
ejpam-5015	252	7	×φ	×φ	PROPN
ejpam-5015	252	8	(	(	PUNCT
ejpam-5015	252	9	−yj(m	−yj(m	PROPN
ejpam-5015	252	10	)	)	PUNCT
ejpam-5015	252	11	+	+	CCONJ
ejpam-5015	252	12	β0	β0	PROPN
ejpam-5015	252	13	+	+	CCONJ
ejpam-5015	252	14	β1xj	β1xj	PUNCT
ejpam-5015	252	15	σ	σ	NOUN
ejpam-5015	252	16	)	)	PUNCT
ejpam-5015	252	17	m−1	m−1	PROPN
ejpam-5015	252	18	]	]	PUNCT
ejpam-5015	252	19	.	.	PUNCT
ejpam-5015	253	1	(	(	PUNCT
ejpam-5015	253	2	37	37	NUM
ejpam-5015	253	3	)	)	PUNCT
ejpam-5015	253	4	5	5	NUM
ejpam-5015	253	5	.	.	X
ejpam-5015	253	6	bayes	bayes	PROPN
ejpam-5015	253	7	factor	factor	NOUN
ejpam-5015	253	8	of	of	ADP
ejpam-5015	253	9	estimators	estimator	NOUN
ejpam-5015	253	10	in	in	ADP
ejpam-5015	253	11	mrss	mrss	ADP
ejpam-5015	253	12	the	the	DET
ejpam-5015	253	13	bayes	bayes	NOUN
ejpam-5015	253	14	factor	factor	NOUN
ejpam-5015	253	15	is	be	AUX
ejpam-5015	253	16	the	the	DET
ejpam-5015	253	17	ratio	ratio	NOUN
ejpam-5015	253	18	of	of	ADP
ejpam-5015	253	19	the	the	DET
ejpam-5015	253	20	marginal	marginal	ADJ
ejpam-5015	253	21	densities	density	NOUN
ejpam-5015	253	22	of	of	ADP
ejpam-5015	253	23	the	the	DET
ejpam-5015	253	24	two	two	NUM
ejpam-5015	253	25	cases	case	NOUN
ejpam-5015	253	26	.	.	PUNCT
ejpam-5015	254	1	the	the	DET
ejpam-5015	254	2	bayes	bayes	PROPN
ejpam-5015	254	3	factor	factor	NOUN
ejpam-5015	254	4	is	be	AUX
ejpam-5015	254	5	given	give	VERB
ejpam-5015	254	6	by	by	ADP
ejpam-5015	254	7	:	:	PUNCT
ejpam-5015	254	8	bji	bji	PROPN
ejpam-5015	254	9	=	=	PRON
ejpam-5015	254	10	mj(y	mj(y	X
ejpam-5015	254	11	)	)	PUNCT
ejpam-5015	254	12	mi(y	mi(y	PUNCT
ejpam-5015	254	13	)	)	PUNCT
ejpam-5015	254	14	=	=	SYM
ejpam-5015	255	1	∫	∫	PROPN
ejpam-5015	255	2	fj(y	fj(y	NUM
ejpam-5015	255	3	|	|	ADV
ejpam-5015	255	4	θ)πj(θ)dθ∫	θ)πj(θ)dθ∫	VERB
ejpam-5015	255	5	fi(y	fi(y	NUM
ejpam-5015	255	6	|	|	ADV
ejpam-5015	255	7	θ)πi(θ)dθ	θ)πi(θ)dθ	ADJ
ejpam-5015	255	8	(	(	PUNCT
ejpam-5015	255	9	38	38	NUM
ejpam-5015	255	10	)	)	PUNCT
ejpam-5015	255	11	here	here	ADV
ejpam-5015	255	12	,	,	PUNCT
ejpam-5015	255	13	this	this	DET
ejpam-5015	255	14	ratio	ratio	NOUN
ejpam-5015	255	15	evaluates	evaluate	VERB
ejpam-5015	255	16	the	the	DET
ejpam-5015	255	17	modification	modification	NOUN
ejpam-5015	255	18	of	of	ADP
ejpam-5015	255	19	the	the	DET
ejpam-5015	255	20	odds	odd	NOUN
ejpam-5015	255	21	of	of	ADP
ejpam-5015	255	22	mj(y	mj(y	NOUN
ejpam-5015	255	23	)	)	PUNCT
ejpam-5015	255	24	against	against	ADP
ejpam-5015	255	25	mi(y	mi(y	NOUN
ejpam-5015	255	26	)	)	PUNCT
ejpam-5015	255	27	due	due	ADP
ejpam-5015	255	28	to	to	ADP
ejpam-5015	255	29	the	the	DET
ejpam-5015	255	30	observation	observation	NOUN
ejpam-5015	255	31	and	and	CCONJ
ejpam-5015	255	32	can	can	AUX
ejpam-5015	255	33	naturally	naturally	ADV
ejpam-5015	255	34	be	be	AUX
ejpam-5015	255	35	compared	compare	VERB
ejpam-5015	255	36	to	to	ADP
ejpam-5015	255	37	1	1	NUM
ejpam-5015	255	38	,	,	PUNCT
ejpam-5015	255	39	although	although	SCONJ
ejpam-5015	255	40	an	an	DET
ejpam-5015	255	41	exact	exact	ADJ
ejpam-5015	255	42	comparison	comparison	NOUN
ejpam-5015	255	43	scale	scale	NOUN
ejpam-5015	255	44	can	can	AUX
ejpam-5015	255	45	only	only	ADV
ejpam-5015	255	46	be	be	AUX
ejpam-5015	255	47	based	base	VERB
ejpam-5015	255	48	upon	upon	SCONJ
ejpam-5015	255	49	a	a	DET
ejpam-5015	255	50	loss	loss	NOUN
ejpam-5015	255	51	function	function	NOUN
ejpam-5015	255	52	.	.	PUNCT
ejpam-5015	256	1	and	and	CCONJ
ejpam-5015	256	2	the	the	DET
ejpam-5015	256	3	bayes	bayes	NOUN
ejpam-5015	256	4	factor	factor	NOUN
ejpam-5015	256	5	depends	depend	VERB
ejpam-5015	256	6	on	on	ADP
ejpam-5015	256	7	prior	prior	ADJ
ejpam-5015	256	8	information	information	NOUN
ejpam-5015	256	9	.	.	PUNCT
ejpam-5015	257	1	it	it	PRON
ejpam-5015	257	2	measures	measure	VERB
ejpam-5015	257	3	the	the	DET
ejpam-5015	257	4	strength	strength	NOUN
ejpam-5015	257	5	of	of	ADP
ejpam-5015	257	6	evidence	evidence	NOUN
ejpam-5015	257	7	for	for	ADP
ejpam-5015	257	8	a	a	DET
ejpam-5015	257	9	model	model	NOUN
ejpam-5015	257	10	in	in	ADP
ejpam-5015	257	11	a	a	DET
ejpam-5015	257	12	way	way	NOUN
ejpam-5015	257	13	that	that	PRON
ejpam-5015	257	14	takes	take	VERB
ejpam-5015	257	15	into	into	ADP
ejpam-5015	257	16	account	account	NOUN
ejpam-5015	257	17	both	both	CCONJ
ejpam-5015	257	18	the	the	DET
ejpam-5015	257	19	goodness	goodness	NOUN
ejpam-5015	257	20	of	of	ADP
ejpam-5015	257	21	fit	fit	NOUN
ejpam-5015	257	22	and	and	CCONJ
ejpam-5015	257	23	the	the	DET
ejpam-5015	257	24	complexity	complexity	NOUN
ejpam-5015	257	25	of	of	ADP
ejpam-5015	257	26	the	the	DET
ejpam-5015	257	27	model	model	NOUN
ejpam-5015	257	28	.	.	PUNCT
ejpam-5015	258	1	however	however	ADV
ejpam-5015	258	2	,	,	PUNCT
ejpam-5015	258	3	it	it	PRON
ejpam-5015	258	4	requires	require	VERB
ejpam-5015	258	5	the	the	DET
ejpam-5015	258	6	computation	computation	NOUN
ejpam-5015	258	7	of	of	ADP
ejpam-5015	258	8	multi	multi	ADJ
ejpam-5015	258	9	-	-	ADJ
ejpam-5015	258	10	dimensional	dimensional	ADJ
ejpam-5015	258	11	integrals	integral	NOUN
ejpam-5015	258	12	,	,	PUNCT
ejpam-5015	258	13	which	which	PRON
ejpam-5015	258	14	can	can	AUX
ejpam-5015	258	15	be	be	AUX
ejpam-5015	258	16	quite	quite	ADV
ejpam-5015	258	17	difficult	difficult	ADJ
ejpam-5015	258	18	in	in	ADP
ejpam-5015	258	19	practice	practice	NOUN
ejpam-5015	258	20	,	,	PUNCT
ejpam-5015	258	21	especially	especially	ADV
ejpam-5015	258	22	for	for	ADP
ejpam-5015	258	23	complex	complex	ADJ
ejpam-5015	258	24	models	model	NOUN
ejpam-5015	258	25	with	with	ADP
ejpam-5015	258	26	many	many	ADJ
ejpam-5015	258	27	parameters	parameter	NOUN
ejpam-5015	258	28	.	.	PUNCT
ejpam-5015	259	1	for	for	ADP
ejpam-5015	259	2	this	this	DET
ejpam-5015	259	3	reason	reason	NOUN
ejpam-5015	259	4	,	,	PUNCT
ejpam-5015	259	5	it	it	PRON
ejpam-5015	259	6	’s	’s	AUX
ejpam-5015	259	7	often	often	ADV
ejpam-5015	259	8	approximated	approximate	VERB
ejpam-5015	259	9	using	use	VERB
ejpam-5015	259	10	techniques	technique	NOUN
ejpam-5015	259	11	like	like	ADP
ejpam-5015	259	12	markov	markov	NOUN
ejpam-5015	259	13	chain	chain	NOUN
ejpam-5015	259	14	monte	monte	PROPN
ejpam-5015	259	15	carlo	carlo	PROPN
ejpam-5015	259	16	(	(	PUNCT
ejpam-5015	259	17	mcmc	mcmc	PROPN
ejpam-5015	259	18	)	)	PUNCT
ejpam-5015	259	19	methods	method	NOUN
ejpam-5015	259	20	.	.	PUNCT
ejpam-5015	260	1	we	we	PRON
ejpam-5015	260	2	can	can	AUX
ejpam-5015	260	3	simplify	simplify	VERB
ejpam-5015	260	4	the	the	DET
ejpam-5015	260	5	bays	bay	NOUN
ejpam-5015	260	6	factor	factor	NOUN
ejpam-5015	260	7	for	for	ADP
ejpam-5015	260	8	the	the	DET
ejpam-5015	260	9	estimator	estimator	NOUN
ejpam-5015	260	10	depending	depend	VERB
ejpam-5015	260	11	on	on	ADP
ejpam-5015	260	12	their	their	PRON
ejpam-5015	260	13	posterior	posterior	ADJ
ejpam-5015	260	14	density	density	NOUN
ejpam-5015	260	15	as	as	ADP
ejpam-5015	260	16	:	:	PUNCT
ejpam-5015	260	17	β̂0b	β̂0b	ADJ
ejpam-5015	260	18	=	=	SYM
ejpam-5015	260	19	∫∞	∫∞	NOUN
ejpam-5015	260	20	−∞	−∞	ADP
ejpam-5015	260	21	∫∞	∫∞	NOUN
ejpam-5015	260	22	−∞	−∞	ADP
ejpam-5015	260	23	∫∞	∫∞	NOUN
ejpam-5015	260	24	−∞	−∞	ADP
ejpam-5015	260	25	β0	β0	PROPN
ejpam-5015	260	26	σr	σr	PROPN
ejpam-5015	260	27	[	[	PUNCT
ejpam-5015	260	28	∏r	∏r	NOUN
ejpam-5015	260	29	j=1em]×	j=1em]×	PROPN
ejpam-5015	260	30	1	1	NUM
ejpam-5015	260	31	(	(	PUNCT
ejpam-5015	260	32	σ2)α+1×∫∞	σ2)α+1×∫∞	X
ejpam-5015	260	33	−∞	−∞	ADP
ejpam-5015	260	34	∫∞	∫∞	NOUN
ejpam-5015	260	35	−∞	−∞	ADP
ejpam-5015	260	36	∫∞	∫∞	NOUN
ejpam-5015	260	37	−∞	−∞	ADP
ejpam-5015	260	38	[	[	PUNCT
ejpam-5015	260	39	∏r	∏r	NOUN
ejpam-5015	260	40	j=1em]dβ0dβ1dσ2	j=1em]dβ0dβ1dσ2	PROPN
ejpam-5015	260	41	×	×	NOUN
ejpam-5015	260	42	[	[	PUNCT
ejpam-5015	260	43	exp	exp	NOUN
ejpam-5015	260	44	(	(	PUNCT
ejpam-5015	260	45	−	−	PROPN
ejpam-5015	260	46	1	1	NUM
ejpam-5015	260	47	2b2	2b2	NUM
ejpam-5015	260	48	(	(	PUNCT
ejpam-5015	260	49	β0	β0	NOUN
ejpam-5015	260	50	−	−	PROPN
ejpam-5015	260	51	a)2	a)2	PROPN
ejpam-5015	260	52	)	)	PUNCT
ejpam-5015	260	53	×	×	NOUN
ejpam-5015	260	54	exp	exp	NOUN
ejpam-5015	260	55	(	(	PUNCT
ejpam-5015	260	56	−	−	PROPN
ejpam-5015	260	57	1	1	NUM
ejpam-5015	260	58	2g2	2g2	NUM
ejpam-5015	260	59	(	(	PUNCT
ejpam-5015	260	60	β1	β1	PROPN
ejpam-5015	260	61	−	−	PROPN
ejpam-5015	260	62	δ)2	δ)2	PROPN
ejpam-5015	260	63	)	)	PUNCT
ejpam-5015	260	64	×	×	NOUN
ejpam-5015	260	65	exp	exp	NOUN
ejpam-5015	260	66	(	(	PUNCT
ejpam-5015	260	67	−	−	PROPN
ejpam-5015	260	68	1	1	NUM
ejpam-5015	260	69	σ2β	σ2β	NOUN
ejpam-5015	260	70	)	)	PUNCT
ejpam-5015	260	71	]	]	PUNCT
ejpam-5015	261	1	dβ0dβ1dσ	dβ0dβ1dσ	PROPN
ejpam-5015	261	2	2	2	NUM
ejpam-5015	261	3	(	(	PUNCT
ejpam-5015	261	4	39	39	NUM
ejpam-5015	261	5	)	)	PUNCT
ejpam-5015	261	6	in	in	ADP
ejpam-5015	261	7	this	this	DET
ejpam-5015	261	8	particular	particular	ADJ
ejpam-5015	261	9	equation	equation	NOUN
ejpam-5015	261	10	,	,	PUNCT
ejpam-5015	261	11	the	the	DET
ejpam-5015	261	12	expectation	expectation	NOUN
ejpam-5015	261	13	of	of	ADP
ejpam-5015	261	14	β0	β0	NOUN
ejpam-5015	261	15	(	(	PUNCT
ejpam-5015	261	16	β̂0b	β̂0b	ADJ
ejpam-5015	261	17	)	)	PUNCT
ejpam-5015	261	18	under	under	ADP
ejpam-5015	261	19	the	the	DET
ejpam-5015	261	20	posterior	posterior	ADJ
ejpam-5015	261	21	distribution	distribution	NOUN
ejpam-5015	261	22	is	be	AUX
ejpam-5015	261	23	being	be	AUX
ejpam-5015	261	24	calculated	calculate	VERB
ejpam-5015	261	25	,	,	PUNCT
ejpam-5015	261	26	which	which	PRON
ejpam-5015	261	27	serves	serve	VERB
ejpam-5015	261	28	as	as	ADP
ejpam-5015	261	29	the	the	DET
ejpam-5015	261	30	bayesian	bayesian	NOUN
ejpam-5015	261	31	point	point	NOUN
ejpam-5015	261	32	estimate	estimate	NOUN
ejpam-5015	261	33	for	for	ADP
ejpam-5015	261	34	this	this	DET
ejpam-5015	261	35	parameter	parameter	NOUN
ejpam-5015	261	36	.	.	PUNCT
ejpam-5015	262	1	this	this	DET
ejpam-5015	262	2	estimate	estimate	NOUN
ejpam-5015	262	3	takes	take	VERB
ejpam-5015	262	4	into	into	ADP
ejpam-5015	262	5	account	account	NOUN
ejpam-5015	262	6	both	both	CCONJ
ejpam-5015	262	7	the	the	DET
ejpam-5015	262	8	likelihood	likelihood	NOUN
ejpam-5015	262	9	of	of	ADP
ejpam-5015	262	10	the	the	DET
ejpam-5015	262	11	data	datum	NOUN
ejpam-5015	262	12	given	give	VERB
ejpam-5015	262	13	the	the	DET
ejpam-5015	262	14	parameters	parameter	NOUN
ejpam-5015	262	15	and	and	CCONJ
ejpam-5015	262	16	the	the	DET
ejpam-5015	262	17	i.	i.	PROPN
ejpam-5015	262	18	nawajah	nawajah	PROPN
ejpam-5015	262	19	,	,	PUNCT
ejpam-5015	262	20	h.	h.	PROPN
ejpam-5015	262	21	kanj	kanj	PROPN
ejpam-5015	262	22	,	,	PUNCT
ejpam-5015	262	23	y.	y.	PROPN
ejpam-5015	262	24	kotb	kotb	PROPN
ejpam-5015	262	25	,	,	PUNCT
ejpam-5015	262	26	j.	j.	PROPN
ejpam-5015	262	27	hoxha	hoxha	PROPN
ejpam-5015	262	28	,	,	PUNCT
ejpam-5015	262	29	m.	m.	PROPN
ejpam-5015	262	30	alakkoumi	alakkoumi	PROPN
ejpam-5015	262	31	,	,	PUNCT
ejpam-5015	262	32	k.	k.	PROPN
ejpam-5015	262	33	jebreen	jebreen	PROPN
ejpam-5015	262	34	/	/	SYM
ejpam-5015	262	35	eur	eur	PROPN
ejpam-5015	262	36	.	.	PUNCT
ejpam-5015	263	1	j.	j.	PROPN
ejpam-5015	263	2	pure	pure	PROPN
ejpam-5015	263	3	appl	appl	PROPN
ejpam-5015	263	4	.	.	PROPN
ejpam-5015	263	5	math	math	PROPN
ejpam-5015	263	6	,	,	PUNCT
ejpam-5015	263	7	17	17	NUM
ejpam-5015	263	8	(	(	PUNCT
ejpam-5015	263	9	1	1	NUM
ejpam-5015	263	10	)	)	PUNCT
ejpam-5015	263	11	(	(	PUNCT
ejpam-5015	263	12	2024	2024	NUM
ejpam-5015	263	13	)	)	PUNCT
ejpam-5015	263	14	,	,	PUNCT
ejpam-5015	263	15	180	180	NUM
ejpam-5015	263	16	-	-	SYM
ejpam-5015	263	17	200	200	NUM
ejpam-5015	263	18	193	193	NUM
ejpam-5015	263	19	prior	prior	ADJ
ejpam-5015	263	20	beliefs	belief	NOUN
ejpam-5015	263	21	about	about	ADP
ejpam-5015	263	22	the	the	DET
ejpam-5015	263	23	parameters	parameter	NOUN
ejpam-5015	263	24	.	.	PUNCT
ejpam-5015	263	25	β̂1b	β̂1b	PUNCT
ejpam-5015	264	1	=	=	PUNCT
ejpam-5015	264	2	∫∞	∫∞	NOUN
ejpam-5015	264	3	−∞	−∞	ADP
ejpam-5015	264	4	∫∞	∫∞	NOUN
ejpam-5015	264	5	−∞	−∞	ADP
ejpam-5015	264	6	∫∞	∫∞	NOUN
ejpam-5015	264	7	−∞	−∞	ADP
ejpam-5015	264	8	β1	β1	PROPN
ejpam-5015	264	9	σr	σr	PROPN
ejpam-5015	264	10	[	[	PUNCT
ejpam-5015	264	11	∏r	∏r	NOUN
ejpam-5015	264	12	j=1em]×	j=1em]×	PROPN
ejpam-5015	264	13	1	1	NUM
ejpam-5015	264	14	(	(	PUNCT
ejpam-5015	264	15	σ2)α+1×∫∞	σ2)α+1×∫∞	X
ejpam-5015	264	16	−∞	−∞	ADP
ejpam-5015	264	17	∫∞	∫∞	NOUN
ejpam-5015	264	18	−∞	−∞	ADP
ejpam-5015	264	19	∫∞	∫∞	NOUN
ejpam-5015	264	20	−∞	−∞	ADP
ejpam-5015	264	21	[	[	PUNCT
ejpam-5015	264	22	∏r	∏r	NOUN
ejpam-5015	264	23	j=1em]dβ0dβ1dσ2	j=1em]dβ0dβ1dσ2	PROPN
ejpam-5015	264	24	×	×	NOUN
ejpam-5015	264	25	[	[	PUNCT
ejpam-5015	264	26	exp	exp	NOUN
ejpam-5015	264	27	(	(	PUNCT
ejpam-5015	264	28	−	−	PROPN
ejpam-5015	264	29	1	1	NUM
ejpam-5015	264	30	2b2	2b2	NUM
ejpam-5015	264	31	(	(	PUNCT
ejpam-5015	264	32	β0	β0	NOUN
ejpam-5015	264	33	−	−	PROPN
ejpam-5015	264	34	a)2	a)2	PROPN
ejpam-5015	264	35	)	)	PUNCT
ejpam-5015	264	36	×	×	NOUN
ejpam-5015	264	37	exp	exp	NOUN
ejpam-5015	264	38	(	(	PUNCT
ejpam-5015	264	39	−	−	PROPN
ejpam-5015	264	40	1	1	NUM
ejpam-5015	264	41	2g2	2g2	NUM
ejpam-5015	264	42	(	(	PUNCT
ejpam-5015	264	43	β1	β1	PROPN
ejpam-5015	264	44	−	−	PROPN
ejpam-5015	264	45	δ)2	δ)2	PROPN
ejpam-5015	264	46	)	)	PUNCT
ejpam-5015	264	47	×	×	NOUN
ejpam-5015	264	48	exp	exp	NOUN
ejpam-5015	264	49	(	(	PUNCT
ejpam-5015	264	50	−	−	PROPN
ejpam-5015	264	51	1	1	NUM
ejpam-5015	264	52	σ2β	σ2β	NOUN
ejpam-5015	264	53	)	)	PUNCT
ejpam-5015	264	54	]	]	PUNCT
ejpam-5015	264	55	dβ0dβ1dσ	dβ0dβ1dσ	PROPN
ejpam-5015	264	56	2	2	NUM
ejpam-5015	264	57	(	(	PUNCT
ejpam-5015	264	58	40	40	NUM
ejpam-5015	264	59	)	)	PUNCT
ejpam-5015	264	60	σ̂2	σ̂2	NOUN
ejpam-5015	264	61	b	b	X
ejpam-5015	265	1	=	=	NOUN
ejpam-5015	266	1	∫∞	∫∞	NOUN
ejpam-5015	266	2	−∞	−∞	ADP
ejpam-5015	266	3	∫∞	∫∞	NOUN
ejpam-5015	266	4	−∞	−∞	ADP
ejpam-5015	266	5	∫∞	∫∞	NOUN
ejpam-5015	266	6	−∞	−∞	ADP
ejpam-5015	266	7	σ2	σ2	PROPN
ejpam-5015	266	8	σr	σr	PROPN
ejpam-5015	266	9	[	[	PUNCT
ejpam-5015	266	10	∏r	∏r	NOUN
ejpam-5015	266	11	j=1em]×	j=1em]×	PROPN
ejpam-5015	266	12	1	1	NUM
ejpam-5015	266	13	(	(	PUNCT
ejpam-5015	266	14	σ2)α+1×∫∞	σ2)α+1×∫∞	X
ejpam-5015	266	15	−∞	−∞	ADP
ejpam-5015	266	16	∫∞	∫∞	NOUN
ejpam-5015	266	17	−∞	−∞	ADP
ejpam-5015	266	18	∫∞	∫∞	NOUN
ejpam-5015	266	19	−∞	−∞	ADP
ejpam-5015	266	20	[	[	PUNCT
ejpam-5015	266	21	∏r	∏r	NOUN
ejpam-5015	266	22	j=1em]dβ0dβ1dσ2	j=1em]dβ0dβ1dσ2	PROPN
ejpam-5015	266	23	×	×	NOUN
ejpam-5015	266	24	[	[	PUNCT
ejpam-5015	266	25	exp	exp	NOUN
ejpam-5015	266	26	(	(	PUNCT
ejpam-5015	266	27	−	−	PROPN
ejpam-5015	266	28	1	1	NUM
ejpam-5015	266	29	2b2	2b2	NUM
ejpam-5015	266	30	(	(	PUNCT
ejpam-5015	266	31	β0	β0	NOUN
ejpam-5015	266	32	−	−	PROPN
ejpam-5015	266	33	a)2	a)2	PROPN
ejpam-5015	266	34	)	)	PUNCT
ejpam-5015	266	35	×	×	NOUN
ejpam-5015	266	36	exp	exp	NOUN
ejpam-5015	266	37	(	(	PUNCT
ejpam-5015	266	38	−	−	PROPN
ejpam-5015	266	39	1	1	NUM
ejpam-5015	266	40	2g2	2g2	NUM
ejpam-5015	266	41	(	(	PUNCT
ejpam-5015	266	42	β1	β1	PROPN
ejpam-5015	266	43	−	−	PROPN
ejpam-5015	266	44	δ)2	δ)2	PROPN
ejpam-5015	266	45	)	)	PUNCT
ejpam-5015	266	46	×	×	NOUN
ejpam-5015	266	47	exp	exp	NOUN
ejpam-5015	266	48	(	(	PUNCT
ejpam-5015	266	49	−	−	PROPN
ejpam-5015	266	50	1	1	NUM
ejpam-5015	266	51	σ2β	σ2β	NOUN
ejpam-5015	266	52	)	)	PUNCT
ejpam-5015	266	53	]	]	PUNCT
ejpam-5015	267	1	dβ0dβ1dσ	dβ0dβ1dσ	PROPN
ejpam-5015	267	2	2	2	NUM
ejpam-5015	267	3	(	(	PUNCT
ejpam-5015	267	4	41	41	NUM
ejpam-5015	267	5	)	)	PUNCT
ejpam-5015	267	6	all	all	DET
ejpam-5015	267	7	the	the	DET
ejpam-5015	267	8	above	above	ADJ
ejpam-5015	267	9	three	three	NUM
ejpam-5015	267	10	equations	equation	NOUN
ejpam-5015	267	11	involve	involve	VERB
ejpam-5015	267	12	a	a	DET
ejpam-5015	267	13	triple	triple	ADJ
ejpam-5015	267	14	integral	integral	ADJ
ejpam-5015	267	15	over	over	ADP
ejpam-5015	267	16	all	all	DET
ejpam-5015	267	17	possible	possible	ADJ
ejpam-5015	267	18	values	value	NOUN
ejpam-5015	267	19	of	of	ADP
ejpam-5015	267	20	β0	β0	NOUN
ejpam-5015	267	21	,	,	PUNCT
ejpam-5015	267	22	β1	β1	PROPN
ejpam-5015	267	23	,	,	PUNCT
ejpam-5015	267	24	and	and	CCONJ
ejpam-5015	267	25	σ2	σ2	PROPN
ejpam-5015	267	26	b	b	PROPN
ejpam-5015	267	27	.	.	PUNCT
ejpam-5015	268	1	in	in	ADP
ejpam-5015	268	2	the	the	DET
ejpam-5015	268	3	bayesian	bayesian	NOUN
ejpam-5015	268	4	context	context	NOUN
ejpam-5015	268	5	,	,	PUNCT
ejpam-5015	268	6	the	the	DET
ejpam-5015	268	7	integral	integral	ADJ
ejpam-5015	268	8	goes	go	VERB
ejpam-5015	268	9	from	from	ADP
ejpam-5015	268	10	(	(	PUNCT
ejpam-5015	268	11	−∞,+∞	−∞,+∞	ADV
ejpam-5015	268	12	)	)	PUNCT
ejpam-5015	268	13	because	because	SCONJ
ejpam-5015	268	14	we	we	PRON
ejpam-5015	268	15	’re	’re	AUX
ejpam-5015	268	16	integrating	integrate	VERB
ejpam-5015	268	17	over	over	ADP
ejpam-5015	268	18	all	all	DET
ejpam-5015	268	19	possible	possible	ADJ
ejpam-5015	268	20	values	value	NOUN
ejpam-5015	268	21	that	that	SCONJ
ejpam-5015	268	22	the	the	DET
ejpam-5015	268	23	parameters	parameter	NOUN
ejpam-5015	268	24	could	could	AUX
ejpam-5015	268	25	take	take	VERB
ejpam-5015	268	26	.	.	PUNCT
ejpam-5015	269	1	in	in	ADP
ejpam-5015	269	2	practice	practice	NOUN
ejpam-5015	269	3	,	,	PUNCT
ejpam-5015	269	4	the	the	DET
ejpam-5015	269	5	values	value	NOUN
ejpam-5015	269	6	are	be	AUX
ejpam-5015	269	7	constrained	constrain	VERB
ejpam-5015	269	8	to	to	PART
ejpam-5015	269	9	make	make	VERB
ejpam-5015	269	10	sense	sense	NOUN
ejpam-5015	269	11	in	in	ADP
ejpam-5015	269	12	the	the	DET
ejpam-5015	269	13	context	context	NOUN
ejpam-5015	269	14	of	of	ADP
ejpam-5015	269	15	the	the	DET
ejpam-5015	269	16	problem	problem	NOUN
ejpam-5015	269	17	in	in	ADP
ejpam-5015	269	18	hand	hand	NOUN
ejpam-5015	269	19	.	.	PUNCT
ejpam-5015	270	1	the	the	DET
ejpam-5015	270	2	equations	equation	NOUN
ejpam-5015	270	3	are	be	AUX
ejpam-5015	270	4	written	write	VERB
ejpam-5015	270	5	in	in	ADP
ejpam-5015	270	6	such	such	DET
ejpam-5015	270	7	a	a	DET
ejpam-5015	270	8	way	way	NOUN
ejpam-5015	270	9	to	to	PART
ejpam-5015	270	10	clearly	clearly	ADV
ejpam-5015	270	11	distinguish	distinguish	VERB
ejpam-5015	270	12	three	three	NUM
ejpam-5015	270	13	common	common	ADJ
ejpam-5015	270	14	terms	term	NOUN
ejpam-5015	270	15	involved	involve	VERB
ejpam-5015	270	16	;	;	PUNCT
ejpam-5015	270	17	in	in	ADP
ejpam-5015	270	18	the	the	DET
ejpam-5015	270	19	numerator	numerator	NOUN
ejpam-5015	270	20	,	,	PUNCT
ejpam-5015	270	21	the	the	DET
ejpam-5015	270	22	terms	term	NOUN
ejpam-5015	270	23	for	for	ADP
ejpam-5015	270	24	each	each	DET
ejpam-5015	270	25	equation	equation	NOUN
ejpam-5015	270	26	β0	β0	PROPN
ejpam-5015	270	27	σr	σr	PROPN
ejpam-5015	270	28	,	,	PUNCT
ejpam-5015	270	29	β1	β1	PROPN
ejpam-5015	270	30	σr	σr	PROPN
ejpam-5015	270	31	and	and	CCONJ
ejpam-5015	270	32	σ2	σ2	PROPN
ejpam-5015	270	33	σr	σr	PROPN
ejpam-5015	270	34	are	be	AUX
ejpam-5015	270	35	part	part	NOUN
ejpam-5015	270	36	of	of	ADP
ejpam-5015	270	37	the	the	DET
ejpam-5015	270	38	function	function	NOUN
ejpam-5015	270	39	we	we	PRON
ejpam-5015	270	40	want	want	VERB
ejpam-5015	270	41	to	to	PART
ejpam-5015	270	42	find	find	VERB
ejpam-5015	270	43	the	the	DET
ejpam-5015	270	44	expected	expect	VERB
ejpam-5015	270	45	value	value	NOUN
ejpam-5015	270	46	of	of	ADP
ejpam-5015	270	47	,	,	PUNCT
ejpam-5015	270	48	where	where	SCONJ
ejpam-5015	270	49	r	r	NOUN
ejpam-5015	270	50	is	be	AUX
ejpam-5015	270	51	the	the	DET
ejpam-5015	270	52	number	number	NOUN
ejpam-5015	270	53	of	of	ADP
ejpam-5015	270	54	data	datum	NOUN
ejpam-5015	270	55	points	point	NOUN
ejpam-5015	270	56	.	.	PUNCT
ejpam-5015	271	1	the	the	DET
ejpam-5015	271	2	product	product	NOUN
ejpam-5015	271	3	∏r	∏r	NOUN
ejpam-5015	271	4	j=1em	j=1em	NOUN
ejpam-5015	271	5	represents	represent	VERB
ejpam-5015	271	6	the	the	DET
ejpam-5015	271	7	likelihood	likelihood	NOUN
ejpam-5015	271	8	function	function	NOUN
ejpam-5015	271	9	for	for	ADP
ejpam-5015	271	10	the	the	DET
ejpam-5015	271	11	model	model	NOUN
ejpam-5015	271	12	.	.	PUNCT
ejpam-5015	272	1	the	the	DET
ejpam-5015	272	2	terms	term	NOUN
ejpam-5015	272	3	involving	involve	VERB
ejpam-5015	272	4	exponential	exponential	ADJ
ejpam-5015	272	5	functions	function	NOUN
ejpam-5015	272	6	are	be	AUX
ejpam-5015	272	7	the	the	DET
ejpam-5015	272	8	prior	prior	ADJ
ejpam-5015	272	9	distributions	distribution	NOUN
ejpam-5015	272	10	of	of	ADP
ejpam-5015	272	11	β0	β0	NOUN
ejpam-5015	272	12	,	,	PUNCT
ejpam-5015	272	13	respectively	respectively	ADV
ejpam-5015	272	14	.	.	PUNCT
ejpam-5015	273	1	we	we	PRON
ejpam-5015	273	2	multiply	multiply	VERB
ejpam-5015	273	3	these	these	DET
ejpam-5015	273	4	three	three	NUM
ejpam-5015	273	5	parts	part	NOUN
ejpam-5015	273	6	together	together	ADV
ejpam-5015	273	7	and	and	CCONJ
ejpam-5015	273	8	integrate	integrate	VERB
ejpam-5015	273	9	over	over	ADP
ejpam-5015	273	10	the	the	DET
ejpam-5015	273	11	parameters	parameter	NOUN
ejpam-5015	273	12	to	to	PART
ejpam-5015	273	13	get	get	VERB
ejpam-5015	273	14	the	the	DET
ejpam-5015	273	15	expected	expect	VERB
ejpam-5015	273	16	value	value	NOUN
ejpam-5015	273	17	of	of	ADP
ejpam-5015	273	18	β0	β0	NOUN
ejpam-5015	273	19	,	,	PUNCT
ejpam-5015	273	20	β1	β1	PROPN
ejpam-5015	273	21	,	,	PUNCT
ejpam-5015	273	22	and	and	CCONJ
ejpam-5015	273	23	σ2	σ2	PROPN
ejpam-5015	273	24	b	b	PROPN
ejpam-5015	273	25	under	under	ADP
ejpam-5015	273	26	the	the	DET
ejpam-5015	273	27	posterior	posterior	ADJ
ejpam-5015	273	28	distribution	distribution	NOUN
ejpam-5015	273	29	.	.	PUNCT
ejpam-5015	274	1	in	in	ADP
ejpam-5015	274	2	the	the	DET
ejpam-5015	274	3	denominator	denominator	NOUN
ejpam-5015	274	4	,	,	PUNCT
ejpam-5015	274	5	the	the	DET
ejpam-5015	274	6	integral	integral	NOUN
ejpam-5015	274	7	of	of	ADP
ejpam-5015	274	8	the	the	DET
ejpam-5015	274	9	likelihood	likelihood	NOUN
ejpam-5015	274	10	over	over	ADP
ejpam-5015	274	11	all	all	DET
ejpam-5015	274	12	possible	possible	ADJ
ejpam-5015	274	13	parameter	parameter	NOUN
ejpam-5015	274	14	values	value	NOUN
ejpam-5015	274	15	,	,	PUNCT
ejpam-5015	274	16	which	which	PRON
ejpam-5015	274	17	serves	serve	VERB
ejpam-5015	274	18	as	as	ADP
ejpam-5015	274	19	a	a	DET
ejpam-5015	274	20	normalization	normalization	NOUN
ejpam-5015	274	21	factor	factor	NOUN
ejpam-5015	274	22	to	to	PART
ejpam-5015	274	23	ensure	ensure	VERB
ejpam-5015	274	24	that	that	SCONJ
ejpam-5015	274	25	the	the	DET
ejpam-5015	274	26	result	result	NOUN
ejpam-5015	274	27	is	be	AUX
ejpam-5015	274	28	a	a	DET
ejpam-5015	274	29	valid	valid	ADJ
ejpam-5015	274	30	probability	probability	NOUN
ejpam-5015	274	31	distribution	distribution	NOUN
ejpam-5015	274	32	.	.	PUNCT
ejpam-5015	275	1	this	this	PRON
ejpam-5015	275	2	is	be	AUX
ejpam-5015	275	3	often	often	ADV
ejpam-5015	275	4	called	call	VERB
ejpam-5015	275	5	the	the	DET
ejpam-5015	275	6	evidence	evidence	NOUN
ejpam-5015	275	7	or	or	CCONJ
ejpam-5015	275	8	marginal	marginal	ADJ
ejpam-5015	275	9	likelihood	likelihood	NOUN
ejpam-5015	275	10	in	in	ADP
ejpam-5015	275	11	bayesian	bayesian	NOUN
ejpam-5015	275	12	statistics	statistic	NOUN
ejpam-5015	275	13	.	.	PUNCT
ejpam-5015	276	1	the	the	DET
ejpam-5015	276	2	ratio	ratio	NOUN
ejpam-5015	276	3	of	of	ADP
ejpam-5015	276	4	the	the	DET
ejpam-5015	276	5	numerator	numerator	NOUN
ejpam-5015	276	6	to	to	ADP
ejpam-5015	276	7	the	the	DET
ejpam-5015	276	8	denominator	denominator	NOUN
ejpam-5015	276	9	gives	give	VERB
ejpam-5015	276	10	the	the	DET
ejpam-5015	276	11	expected	expect	VERB
ejpam-5015	276	12	value	value	NOUN
ejpam-5015	276	13	of	of	ADP
ejpam-5015	276	14	β0	β0	NOUN
ejpam-5015	276	15	,	,	PUNCT
ejpam-5015	276	16	β1	β1	PROPN
ejpam-5015	276	17	,	,	PUNCT
ejpam-5015	276	18	and	and	CCONJ
ejpam-5015	276	19	σ2	σ2	PROPN
ejpam-5015	276	20	b	b	PROPN
ejpam-5015	276	21	which	which	PRON
ejpam-5015	276	22	is	be	AUX
ejpam-5015	276	23	an	an	DET
ejpam-5015	276	24	estimate	estimate	NOUN
ejpam-5015	276	25	for	for	ADP
ejpam-5015	276	26	this	this	DET
ejpam-5015	276	27	parameter	parameter	NOUN
ejpam-5015	276	28	under	under	ADP
ejpam-5015	276	29	the	the	DET
ejpam-5015	276	30	posterior	posterior	ADJ
ejpam-5015	276	31	distribution	distribution	NOUN
ejpam-5015	276	32	.	.	PUNCT
ejpam-5015	277	1	the	the	DET
ejpam-5015	277	2	integrals	integral	NOUN
ejpam-5015	277	3	above	above	ADV
ejpam-5015	277	4	are	be	AUX
ejpam-5015	277	5	typically	typically	ADV
ejpam-5015	277	6	not	not	PART
ejpam-5015	277	7	solvable	solvable	ADJ
ejpam-5015	277	8	analytically	analytically	ADV
ejpam-5015	277	9	,	,	PUNCT
ejpam-5015	277	10	especially	especially	ADV
ejpam-5015	277	11	for	for	ADP
ejpam-5015	277	12	complex	complex	ADJ
ejpam-5015	277	13	models	model	NOUN
ejpam-5015	277	14	.	.	PUNCT
ejpam-5015	278	1	thus	thus	ADV
ejpam-5015	278	2	,	,	PUNCT
ejpam-5015	278	3	numerical	numerical	ADJ
ejpam-5015	278	4	methods	method	NOUN
ejpam-5015	278	5	like	like	ADP
ejpam-5015	278	6	mcmc	mcmc	PROPN
ejpam-5015	278	7	are	be	AUX
ejpam-5015	278	8	often	often	ADV
ejpam-5015	278	9	used	use	VERB
ejpam-5015	278	10	to	to	PART
ejpam-5015	278	11	approximate	approximate	VERB
ejpam-5015	278	12	these	these	DET
ejpam-5015	278	13	integrals	integral	NOUN
ejpam-5015	278	14	.	.	PUNCT
ejpam-5015	279	1	6	6	X
ejpam-5015	279	2	.	.	X
ejpam-5015	279	3	simulation	simulation	NOUN
ejpam-5015	279	4	study	study	NOUN
ejpam-5015	279	5	in	in	ADP
ejpam-5015	279	6	this	this	DET
ejpam-5015	279	7	study	study	NOUN
ejpam-5015	279	8	,	,	PUNCT
ejpam-5015	279	9	the	the	DET
ejpam-5015	279	10	mcmc	mcmc	PROPN
ejpam-5015	279	11	numerical	numerical	PROPN
ejpam-5015	279	12	method	method	PROPN
ejpam-5015	279	13	is	be	AUX
ejpam-5015	279	14	used	use	VERB
ejpam-5015	279	15	to	to	PART
ejpam-5015	279	16	approximate	approximate	VERB
ejpam-5015	279	17	the	the	DET
ejpam-5015	279	18	calculation	calculation	NOUN
ejpam-5015	279	19	of	of	ADP
ejpam-5015	279	20	the	the	DET
ejpam-5015	279	21	posterior	posterior	ADJ
ejpam-5015	279	22	expectation	expectation	NOUN
ejpam-5015	279	23	of	of	ADP
ejpam-5015	279	24	the	the	DET
ejpam-5015	279	25	parameters	parameter	NOUN
ejpam-5015	279	26	β0	β0	PROPN
ejpam-5015	279	27	,	,	PUNCT
ejpam-5015	279	28	β1	β1	PROPN
ejpam-5015	279	29	,	,	PUNCT
ejpam-5015	279	30	and	and	CCONJ
ejpam-5015	279	31	σ2	σ2	PROPN
ejpam-5015	279	32	b	b	PROPN
ejpam-5015	279	33	,	,	PUNCT
ejpam-5015	279	34	derived	derive	VERB
ejpam-5015	279	35	in	in	ADP
ejpam-5015	279	36	section	section	NOUN
ejpam-5015	279	37	5	5	NUM
ejpam-5015	279	38	.	.	PUNCT
ejpam-5015	280	1	this	this	PRON
ejpam-5015	280	2	serves	serve	VERB
ejpam-5015	280	3	as	as	ADP
ejpam-5015	280	4	the	the	DET
ejpam-5015	280	5	bayesian	bayesian	NOUN
ejpam-5015	280	6	point	point	NOUN
ejpam-5015	280	7	estimate	estimate	NOUN
ejpam-5015	280	8	for	for	ADP
ejpam-5015	280	9	this	this	DET
ejpam-5015	280	10	parameters	parameter	NOUN
ejpam-5015	280	11	.	.	PUNCT
ejpam-5015	281	1	we	we	PRON
ejpam-5015	281	2	run	run	VERB
ejpam-5015	281	3	the	the	DET
ejpam-5015	281	4	mcmc	mcmc	PROPN
ejpam-5015	281	5	simulation	simulation	NOUN
ejpam-5015	281	6	for	for	ADP
ejpam-5015	281	7	200,000	200,000	NUM
ejpam-5015	281	8	iterations	iteration	NOUN
ejpam-5015	281	9	.	.	PUNCT
ejpam-5015	282	1	an	an	DET
ejpam-5015	282	2	iteration	iteration	NOUN
ejpam-5015	282	3	here	here	ADV
ejpam-5015	282	4	corresponds	correspond	VERB
ejpam-5015	282	5	to	to	ADP
ejpam-5015	282	6	one	one	NUM
ejpam-5015	282	7	cycle	cycle	NOUN
ejpam-5015	282	8	through	through	ADP
ejpam-5015	282	9	the	the	DET
ejpam-5015	282	10	algorithm	algorithm	NOUN
ejpam-5015	282	11	–	–	PUNCT
ejpam-5015	282	12	proposing	propose	VERB
ejpam-5015	282	13	new	new	ADJ
ejpam-5015	282	14	values	value	NOUN
ejpam-5015	282	15	for	for	ADP
ejpam-5015	282	16	the	the	DET
ejpam-5015	282	17	parameters	parameter	NOUN
ejpam-5015	282	18	,	,	PUNCT
ejpam-5015	282	19	checking	check	VERB
ejpam-5015	282	20	whether	whether	SCONJ
ejpam-5015	282	21	these	these	DET
ejpam-5015	282	22	new	new	ADJ
ejpam-5015	282	23	values	value	NOUN
ejpam-5015	282	24	are	be	AUX
ejpam-5015	282	25	likely	likely	ADJ
ejpam-5015	282	26	i.	i.	PROPN
ejpam-5015	282	27	nawajah	nawajah	PROPN
ejpam-5015	282	28	,	,	PUNCT
ejpam-5015	282	29	h.	h.	PROPN
ejpam-5015	282	30	kanj	kanj	PROPN
ejpam-5015	282	31	,	,	PUNCT
ejpam-5015	282	32	y.	y.	PROPN
ejpam-5015	282	33	kotb	kotb	PROPN
ejpam-5015	282	34	,	,	PUNCT
ejpam-5015	282	35	j.	j.	PROPN
ejpam-5015	282	36	hoxha	hoxha	PROPN
ejpam-5015	282	37	,	,	PUNCT
ejpam-5015	282	38	m.	m.	PROPN
ejpam-5015	282	39	alakkoumi	alakkoumi	PROPN
ejpam-5015	282	40	,	,	PUNCT
ejpam-5015	282	41	k.	k.	PROPN
ejpam-5015	282	42	jebreen	jebreen	PROPN
ejpam-5015	282	43	/	/	SYM
ejpam-5015	282	44	eur	eur	PROPN
ejpam-5015	282	45	.	.	PUNCT
ejpam-5015	283	1	j.	j.	PROPN
ejpam-5015	283	2	pure	pure	PROPN
ejpam-5015	283	3	appl	appl	PROPN
ejpam-5015	283	4	.	.	PROPN
ejpam-5015	283	5	math	math	PROPN
ejpam-5015	283	6	,	,	PUNCT
ejpam-5015	283	7	17	17	NUM
ejpam-5015	283	8	(	(	PUNCT
ejpam-5015	283	9	1	1	NUM
ejpam-5015	283	10	)	)	PUNCT
ejpam-5015	283	11	(	(	PUNCT
ejpam-5015	283	12	2024	2024	NUM
ejpam-5015	283	13	)	)	PUNCT
ejpam-5015	283	14	,	,	PUNCT
ejpam-5015	283	15	180	180	NUM
ejpam-5015	283	16	-	-	SYM
ejpam-5015	283	17	200	200	NUM
ejpam-5015	283	18	194	194	NUM
ejpam-5015	283	19	given	give	VERB
ejpam-5015	283	20	the	the	DET
ejpam-5015	283	21	data	datum	NOUN
ejpam-5015	283	22	(	(	PUNCT
ejpam-5015	283	23	using	use	VERB
ejpam-5015	283	24	the	the	DET
ejpam-5015	283	25	likelihood	likelihood	NOUN
ejpam-5015	283	26	function	function	NOUN
ejpam-5015	283	27	)	)	PUNCT
ejpam-5015	283	28	,	,	PUNCT
ejpam-5015	283	29	and	and	CCONJ
ejpam-5015	283	30	deciding	decide	VERB
ejpam-5015	283	31	whether	whether	SCONJ
ejpam-5015	283	32	to	to	PART
ejpam-5015	283	33	accept	accept	VERB
ejpam-5015	283	34	these	these	DET
ejpam-5015	283	35	new	new	ADJ
ejpam-5015	283	36	values	value	NOUN
ejpam-5015	283	37	or	or	CCONJ
ejpam-5015	283	38	keep	keep	VERB
ejpam-5015	283	39	the	the	DET
ejpam-5015	283	40	old	old	ADJ
ejpam-5015	283	41	ones	one	NOUN
ejpam-5015	283	42	[	[	X
ejpam-5015	283	43	15	15	NUM
ejpam-5015	283	44	]	]	PUNCT
ejpam-5015	283	45	.	.	PUNCT
ejpam-5015	284	1	the	the	DET
ejpam-5015	284	2	first	first	ADJ
ejpam-5015	284	3	5,000	5,000	NUM
ejpam-5015	284	4	iterations	iteration	NOUN
ejpam-5015	284	5	are	be	AUX
ejpam-5015	284	6	discarded	discard	VERB
ejpam-5015	284	7	.	.	PUNCT
ejpam-5015	285	1	this	this	PRON
ejpam-5015	285	2	is	be	AUX
ejpam-5015	285	3	known	know	VERB
ejpam-5015	285	4	as	as	ADP
ejpam-5015	285	5	the	the	DET
ejpam-5015	285	6	”	"	PUNCT
ejpam-5015	285	7	burn	burn	NOUN
ejpam-5015	285	8	-	-	PUNCT
ejpam-5015	285	9	in	in	ADP
ejpam-5015	285	10	”	"	PUNCT
ejpam-5015	285	11	period	period	NOUN
ejpam-5015	285	12	.	.	PUNCT
ejpam-5015	286	1	the	the	DET
ejpam-5015	286	2	idea	idea	NOUN
ejpam-5015	286	3	is	be	AUX
ejpam-5015	286	4	that	that	SCONJ
ejpam-5015	286	5	early	early	ADJ
ejpam-5015	286	6	iterations	iteration	NOUN
ejpam-5015	286	7	are	be	AUX
ejpam-5015	286	8	based	base	VERB
ejpam-5015	286	9	on	on	ADP
ejpam-5015	286	10	our	our	PRON
ejpam-5015	286	11	initial	initial	ADJ
ejpam-5015	286	12	(	(	PUNCT
ejpam-5015	286	13	potentially	potentially	ADV
ejpam-5015	286	14	poor	poor	ADJ
ejpam-5015	286	15	)	)	PUNCT
ejpam-5015	286	16	guess	guess	NOUN
ejpam-5015	286	17	,	,	PUNCT
ejpam-5015	286	18	and	and	CCONJ
ejpam-5015	286	19	so	so	ADV
ejpam-5015	286	20	we	we	PRON
ejpam-5015	286	21	have	have	VERB
ejpam-5015	286	22	to	to	PART
ejpam-5015	286	23	give	give	VERB
ejpam-5015	286	24	the	the	DET
ejpam-5015	286	25	algorithm	algorithm	NOUN
ejpam-5015	286	26	some	some	DET
ejpam-5015	286	27	time	time	NOUN
ejpam-5015	286	28	to	to	PART
ejpam-5015	286	29	converge	converge	VERB
ejpam-5015	286	30	towards	towards	ADP
ejpam-5015	286	31	the	the	DET
ejpam-5015	286	32	true	true	ADJ
ejpam-5015	286	33	values	value	NOUN
ejpam-5015	286	34	before	before	SCONJ
ejpam-5015	286	35	we	we	PRON
ejpam-5015	286	36	start	start	VERB
ejpam-5015	286	37	collecting	collect	VERB
ejpam-5015	286	38	data	datum	NOUN
ejpam-5015	286	39	.	.	PUNCT
ejpam-5015	287	1	after	after	ADP
ejpam-5015	287	2	the	the	DET
ejpam-5015	287	3	burn	burn	NOUN
ejpam-5015	287	4	-	-	PUNCT
ejpam-5015	287	5	in	in	ADP
ejpam-5015	287	6	period	period	NOUN
ejpam-5015	287	7	,	,	PUNCT
ejpam-5015	287	8	we	we	PRON
ejpam-5015	287	9	start	start	VERB
ejpam-5015	287	10	collecting	collect	VERB
ejpam-5015	287	11	data	datum	NOUN
ejpam-5015	287	12	,	,	PUNCT
ejpam-5015	287	13	but	but	CCONJ
ejpam-5015	287	14	not	not	PART
ejpam-5015	287	15	at	at	ADP
ejpam-5015	287	16	every	every	DET
ejpam-5015	287	17	iteration	iteration	NOUN
ejpam-5015	287	18	.	.	PUNCT
ejpam-5015	288	1	instead	instead	ADV
ejpam-5015	288	2	,	,	PUNCT
ejpam-5015	288	3	we	we	PRON
ejpam-5015	288	4	only	only	ADV
ejpam-5015	288	5	keep	keep	VERB
ejpam-5015	288	6	the	the	DET
ejpam-5015	288	7	parameter	parameter	NOUN
ejpam-5015	288	8	values	value	NOUN
ejpam-5015	288	9	every	every	DET
ejpam-5015	288	10	50th	50th	ADJ
ejpam-5015	288	11	iteration	iteration	NOUN
ejpam-5015	288	12	.	.	PUNCT
ejpam-5015	289	1	this	this	PRON
ejpam-5015	289	2	is	be	AUX
ejpam-5015	289	3	known	know	VERB
ejpam-5015	289	4	as	as	ADP
ejpam-5015	289	5	”	"	PUNCT
ejpam-5015	289	6	thinning	thinning	NOUN
ejpam-5015	289	7	”	"	PUNCT
ejpam-5015	289	8	.	.	PUNCT
ejpam-5015	290	1	the	the	DET
ejpam-5015	290	2	purpose	purpose	NOUN
ejpam-5015	290	3	is	be	AUX
ejpam-5015	290	4	to	to	PART
ejpam-5015	290	5	reduce	reduce	VERB
ejpam-5015	290	6	the	the	DET
ejpam-5015	290	7	correlation	correlation	NOUN
ejpam-5015	290	8	between	between	ADP
ejpam-5015	290	9	successive	successive	ADJ
ejpam-5015	290	10	samples	sample	NOUN
ejpam-5015	290	11	,	,	PUNCT
ejpam-5015	290	12	which	which	PRON
ejpam-5015	290	13	can	can	AUX
ejpam-5015	290	14	bias	bias	VERB
ejpam-5015	290	15	the	the	DET
ejpam-5015	290	16	results	result	NOUN
ejpam-5015	290	17	.	.	PUNCT
ejpam-5015	291	1	after	after	ADP
ejpam-5015	291	2	the	the	DET
ejpam-5015	291	3	burn	burn	NOUN
ejpam-5015	291	4	-	-	PUNCT
ejpam-5015	291	5	in	in	ADP
ejpam-5015	291	6	and	and	CCONJ
ejpam-5015	291	7	thinning	thinning	NOUN
ejpam-5015	291	8	,	,	PUNCT
ejpam-5015	291	9	you	you	PRON
ejpam-5015	291	10	are	be	AUX
ejpam-5015	291	11	left	leave	VERB
ejpam-5015	291	12	with	with	ADP
ejpam-5015	291	13	5,000	5,000	NUM
ejpam-5015	291	14	samples	sample	NOUN
ejpam-5015	291	15	.	.	PUNCT
ejpam-5015	292	1	these	these	PRON
ejpam-5015	292	2	are	be	AUX
ejpam-5015	292	3	the	the	DET
ejpam-5015	292	4	values	value	NOUN
ejpam-5015	292	5	of	of	ADP
ejpam-5015	292	6	the	the	DET
ejpam-5015	292	7	parameters	parameter	NOUN
ejpam-5015	292	8	at	at	ADP
ejpam-5015	292	9	different	different	ADJ
ejpam-5015	292	10	points	point	NOUN
ejpam-5015	292	11	in	in	ADP
ejpam-5015	292	12	the	the	DET
ejpam-5015	292	13	mcmc	mcmc	PROPN
ejpam-5015	292	14	simulation	simulation	PROPN
ejpam-5015	292	15	.	.	PUNCT
ejpam-5015	293	1	each	each	DET
ejpam-5015	293	2	sample	sample	NOUN
ejpam-5015	293	3	represents	represent	VERB
ejpam-5015	293	4	a	a	DET
ejpam-5015	293	5	possible	possible	ADJ
ejpam-5015	293	6	set	set	NOUN
ejpam-5015	293	7	of	of	ADP
ejpam-5015	293	8	parameters	parameter	NOUN
ejpam-5015	293	9	that	that	PRON
ejpam-5015	293	10	could	could	AUX
ejpam-5015	293	11	have	have	AUX
ejpam-5015	293	12	generated	generate	VERB
ejpam-5015	293	13	the	the	DET
ejpam-5015	293	14	data	datum	NOUN
ejpam-5015	293	15	.	.	PUNCT
ejpam-5015	294	1	finally	finally	ADV
ejpam-5015	294	2	,	,	PUNCT
ejpam-5015	294	3	we	we	PRON
ejpam-5015	294	4	need	need	VERB
ejpam-5015	294	5	to	to	PART
ejpam-5015	294	6	check	check	VERB
ejpam-5015	294	7	whether	whether	SCONJ
ejpam-5015	294	8	the	the	DET
ejpam-5015	294	9	algorithm	algorithm	NOUN
ejpam-5015	294	10	has	have	AUX
ejpam-5015	294	11	converged	converge	VERB
ejpam-5015	294	12	–	–	PUNCT
ejpam-5015	294	13	that	that	ADV
ejpam-5015	294	14	is	is	ADV
ejpam-5015	294	15	,	,	PUNCT
ejpam-5015	294	16	whether	whether	SCONJ
ejpam-5015	294	17	it	it	PRON
ejpam-5015	294	18	has	have	AUX
ejpam-5015	294	19	found	find	VERB
ejpam-5015	294	20	the	the	DET
ejpam-5015	294	21	true	true	ADJ
ejpam-5015	294	22	posterior	posterior	ADJ
ejpam-5015	294	23	distribution	distribution	NOUN
ejpam-5015	294	24	.	.	PUNCT
ejpam-5015	295	1	this	this	PRON
ejpam-5015	295	2	is	be	AUX
ejpam-5015	295	3	typically	typically	ADV
ejpam-5015	295	4	done	do	VERB
ejpam-5015	295	5	using	use	VERB
ejpam-5015	295	6	various	various	ADJ
ejpam-5015	295	7	statistical	statistical	ADJ
ejpam-5015	295	8	tests	test	NOUN
ejpam-5015	295	9	,	,	PUNCT
ejpam-5015	295	10	such	such	ADJ
ejpam-5015	295	11	as	as	ADP
ejpam-5015	295	12	the	the	DET
ejpam-5015	295	13	geweke	geweke	NOUN
ejpam-5015	295	14	diagnostic	diagnostic	NOUN
ejpam-5015	295	15	,	,	PUNCT
ejpam-5015	295	16	which	which	PRON
ejpam-5015	295	17	compares	compare	VERB
ejpam-5015	295	18	the	the	DET
ejpam-5015	295	19	mean	mean	NOUN
ejpam-5015	295	20	of	of	ADP
ejpam-5015	295	21	the	the	DET
ejpam-5015	295	22	early	early	ADJ
ejpam-5015	295	23	and	and	CCONJ
ejpam-5015	295	24	late	late	ADJ
ejpam-5015	295	25	portions	portion	NOUN
ejpam-5015	295	26	of	of	ADP
ejpam-5015	295	27	the	the	DET
ejpam-5015	295	28	chain	chain	NOUN
ejpam-5015	295	29	,	,	PUNCT
ejpam-5015	295	30	and	and	CCONJ
ejpam-5015	295	31	the	the	DET
ejpam-5015	295	32	heidelberger	heidelberger	NOUN
ejpam-5015	295	33	-	-	PUNCT
ejpam-5015	295	34	welch	welch	NOUN
ejpam-5015	295	35	diagnostics	diagnostic	NOUN
ejpam-5015	295	36	,	,	PUNCT
ejpam-5015	295	37	which	which	PRON
ejpam-5015	295	38	involve	involve	VERB
ejpam-5015	295	39	a	a	DET
ejpam-5015	295	40	stationarity	stationarity	NOUN
ejpam-5015	295	41	test	test	NOUN
ejpam-5015	295	42	(	(	PUNCT
ejpam-5015	295	43	to	to	PART
ejpam-5015	295	44	see	see	VERB
ejpam-5015	295	45	if	if	SCONJ
ejpam-5015	295	46	the	the	DET
ejpam-5015	295	47	chain	chain	NOUN
ejpam-5015	295	48	has	have	AUX
ejpam-5015	295	49	reached	reach	VERB
ejpam-5015	295	50	equilibrium	equilibrium	NOUN
ejpam-5015	295	51	)	)	PUNCT
ejpam-5015	295	52	and	and	CCONJ
ejpam-5015	295	53	a	a	DET
ejpam-5015	295	54	half	half	ADJ
ejpam-5015	295	55	-	-	PUNCT
ejpam-5015	295	56	width	width	NOUN
ejpam-5015	295	57	test	test	NOUN
ejpam-5015	295	58	(	(	PUNCT
ejpam-5015	295	59	to	to	PART
ejpam-5015	295	60	see	see	VERB
ejpam-5015	295	61	if	if	SCONJ
ejpam-5015	295	62	the	the	DET
ejpam-5015	295	63	chain	chain	NOUN
ejpam-5015	295	64	has	have	AUX
ejpam-5015	295	65	run	run	VERB
ejpam-5015	295	66	long	long	ADV
ejpam-5015	295	67	enough	enough	ADV
ejpam-5015	295	68	to	to	PART
ejpam-5015	295	69	achieve	achieve	VERB
ejpam-5015	295	70	a	a	DET
ejpam-5015	295	71	desired	desire	VERB
ejpam-5015	295	72	precision	precision	NOUN
ejpam-5015	295	73	)	)	PUNCT
ejpam-5015	296	1	[	[	X
ejpam-5015	296	2	17	17	NUM
ejpam-5015	296	3	,	,	PUNCT
ejpam-5015	296	4	24	24	NUM
ejpam-5015	296	5	]	]	PUNCT
ejpam-5015	296	6	.	.	PUNCT
ejpam-5015	297	1	through	through	ADP
ejpam-5015	297	2	this	this	DET
ejpam-5015	297	3	process	process	NOUN
ejpam-5015	297	4	,	,	PUNCT
ejpam-5015	297	5	we	we	PRON
ejpam-5015	297	6	have	have	AUX
ejpam-5015	297	7	generated	generate	VERB
ejpam-5015	297	8	many	many	ADJ
ejpam-5015	297	9	different	different	ADJ
ejpam-5015	297	10	samples	sample	NOUN
ejpam-5015	297	11	of	of	ADP
ejpam-5015	297	12	parameter	parameter	NOUN
ejpam-5015	297	13	values	value	NOUN
ejpam-5015	297	14	.	.	PUNCT
ejpam-5015	298	1	the	the	DET
ejpam-5015	298	2	collection	collection	NOUN
ejpam-5015	298	3	of	of	ADP
ejpam-5015	298	4	these	these	DET
ejpam-5015	298	5	samples	sample	NOUN
ejpam-5015	298	6	approximates	approximate	VERB
ejpam-5015	298	7	the	the	DET
ejpam-5015	298	8	posterior	posterior	ADJ
ejpam-5015	298	9	distribution	distribution	NOUN
ejpam-5015	298	10	of	of	ADP
ejpam-5015	298	11	the	the	DET
ejpam-5015	298	12	parameters	parameter	NOUN
ejpam-5015	298	13	and	and	CCONJ
ejpam-5015	298	14	the	the	DET
ejpam-5015	298	15	triple	triple	ADJ
ejpam-5015	298	16	integral	integral	ADJ
ejpam-5015	298	17	in	in	ADP
ejpam-5015	298	18	the	the	DET
ejpam-5015	298	19	formula	formula	NOUN
ejpam-5015	298	20	for	for	ADP
ejpam-5015	298	21	the	the	DET
ejpam-5015	298	22	posterior	posterior	ADJ
ejpam-5015	298	23	mean	mean	NOUN
ejpam-5015	298	24	of	of	ADP
ejpam-5015	298	25	β0	β0	NOUN
ejpam-5015	298	26	can	can	AUX
ejpam-5015	298	27	then	then	ADV
ejpam-5015	298	28	be	be	AUX
ejpam-5015	298	29	approximated	approximate	VERB
ejpam-5015	298	30	by	by	ADP
ejpam-5015	298	31	taking	take	VERB
ejpam-5015	298	32	the	the	DET
ejpam-5015	298	33	average	average	NOUN
ejpam-5015	298	34	of	of	ADP
ejpam-5015	298	35	β0	β0	ADJ
ejpam-5015	298	36	over	over	ADP
ejpam-5015	298	37	these	these	DET
ejpam-5015	298	38	samples	sample	NOUN
ejpam-5015	298	39	.	.	PUNCT
ejpam-5015	299	1	in	in	ADP
ejpam-5015	299	2	order	order	NOUN
ejpam-5015	299	3	to	to	PART
ejpam-5015	299	4	assess	assess	VERB
ejpam-5015	299	5	the	the	DET
ejpam-5015	299	6	performance	performance	NOUN
ejpam-5015	299	7	of	of	ADP
ejpam-5015	299	8	the	the	DET
ejpam-5015	299	9	simulation	simulation	NOUN
ejpam-5015	299	10	and	and	CCONJ
ejpam-5015	299	11	the	the	DET
ejpam-5015	299	12	convergence	convergence	NOUN
ejpam-5015	299	13	of	of	ADP
ejpam-5015	299	14	the	the	DET
ejpam-5015	299	15	chain	chain	NOUN
ejpam-5015	299	16	,	,	PUNCT
ejpam-5015	299	17	in	in	ADP
ejpam-5015	299	18	figure	figure	NOUN
ejpam-5015	299	19	1	1	NUM
ejpam-5015	299	20	we	we	PRON
ejpam-5015	299	21	show	show	VERB
ejpam-5015	299	22	the	the	DET
ejpam-5015	299	23	trace	trace	NOUN
ejpam-5015	299	24	plots	plot	NOUN
ejpam-5015	299	25	for	for	ADP
ejpam-5015	299	26	the	the	DET
ejpam-5015	299	27	three	three	NUM
ejpam-5015	299	28	parameters	parameter	NOUN
ejpam-5015	299	29	of	of	ADP
ejpam-5015	299	30	interest	interest	NOUN
ejpam-5015	299	31	β0,β1	β0,β1	PROPN
ejpam-5015	299	32	and	and	CCONJ
ejpam-5015	299	33	σ2	σ2	PROPN
ejpam-5015	299	34	b	b	PROPN
ejpam-5015	299	35	.	.	PUNCT
ejpam-5015	300	1	the	the	DET
ejpam-5015	300	2	trace	trace	NOUN
ejpam-5015	300	3	plot	plot	NOUN
ejpam-5015	300	4	of	of	ADP
ejpam-5015	300	5	each	each	DET
ejpam-5015	300	6	parameter	parameter	NOUN
ejpam-5015	300	7	displays	display	VERB
ejpam-5015	300	8	the	the	DET
ejpam-5015	300	9	sequence	sequence	NOUN
ejpam-5015	300	10	of	of	ADP
ejpam-5015	300	11	sampled	sample	VERB
ejpam-5015	300	12	values	value	NOUN
ejpam-5015	300	13	(	(	PUNCT
ejpam-5015	300	14	on	on	ADP
ejpam-5015	300	15	the	the	DET
ejpam-5015	300	16	y	y	NOUN
ejpam-5015	300	17	-	-	PUNCT
ejpam-5015	300	18	axis	axis	NOUN
ejpam-5015	300	19	)	)	PUNCT
ejpam-5015	300	20	at	at	ADP
ejpam-5015	300	21	each	each	DET
ejpam-5015	300	22	step	step	NOUN
ejpam-5015	300	23	in	in	ADP
ejpam-5015	300	24	the	the	DET
ejpam-5015	300	25	mcmc	mcmc	PROPN
ejpam-5015	300	26	chain	chain	NOUN
ejpam-5015	300	27	(	(	PUNCT
ejpam-5015	300	28	on	on	ADP
ejpam-5015	300	29	the	the	DET
ejpam-5015	300	30	x	x	NOUN
ejpam-5015	300	31	-	-	NOUN
ejpam-5015	300	32	axis	axis	ADJ
ejpam-5015	300	33	)	)	PUNCT
ejpam-5015	300	34	.	.	PUNCT
ejpam-5015	301	1	it	it	PRON
ejpam-5015	301	2	enables	enable	VERB
ejpam-5015	301	3	us	we	PRON
ejpam-5015	301	4	to	to	PART
ejpam-5015	301	5	visualize	visualize	VERB
ejpam-5015	301	6	the	the	DET
ejpam-5015	301	7	path	path	NOUN
ejpam-5015	301	8	taken	take	VERB
ejpam-5015	301	9	by	by	ADP
ejpam-5015	301	10	the	the	DET
ejpam-5015	301	11	markov	markov	NOUN
ejpam-5015	301	12	chain	chain	NOUN
ejpam-5015	301	13	over	over	ADP
ejpam-5015	301	14	the	the	DET
ejpam-5015	301	15	iterations	iteration	NOUN
ejpam-5015	301	16	.	.	PUNCT
ejpam-5015	302	1	by	by	ADP
ejpam-5015	302	2	looking	look	VERB
ejpam-5015	302	3	at	at	ADP
ejpam-5015	302	4	the	the	DET
ejpam-5015	302	5	trace	trace	NOUN
ejpam-5015	302	6	plot	plot	NOUN
ejpam-5015	302	7	,	,	PUNCT
ejpam-5015	302	8	we	we	PRON
ejpam-5015	302	9	can	can	AUX
ejpam-5015	302	10	assess	assess	VERB
ejpam-5015	302	11	whether	whether	SCONJ
ejpam-5015	302	12	the	the	DET
ejpam-5015	302	13	chain	chain	NOUN
ejpam-5015	302	14	has	have	AUX
ejpam-5015	302	15	converged	converge	VERB
ejpam-5015	302	16	to	to	ADP
ejpam-5015	302	17	the	the	DET
ejpam-5015	302	18	target	target	NOUN
ejpam-5015	302	19	distribution	distribution	NOUN
ejpam-5015	302	20	.	.	PUNCT
ejpam-5015	303	1	ideally	ideally	ADV
ejpam-5015	303	2	,	,	PUNCT
ejpam-5015	303	3	the	the	DET
ejpam-5015	303	4	plot	plot	NOUN
ejpam-5015	303	5	should	should	AUX
ejpam-5015	303	6	look	look	VERB
ejpam-5015	303	7	like	like	ADP
ejpam-5015	303	8	a	a	DET
ejpam-5015	303	9	’	'	PUNCT
ejpam-5015	303	10	hairy	hairy	ADJ
ejpam-5015	303	11	caterpillar	caterpillar	NOUN
ejpam-5015	303	12	’	'	PUNCT
ejpam-5015	303	13	–	–	PUNCT
ejpam-5015	303	14	it	it	PRON
ejpam-5015	303	15	should	should	AUX
ejpam-5015	303	16	oscillate	oscillate	VERB
ejpam-5015	303	17	around	around	ADP
ejpam-5015	303	18	a	a	DET
ejpam-5015	303	19	constant	constant	ADJ
ejpam-5015	303	20	mean	mean	NOUN
ejpam-5015	303	21	without	without	ADP
ejpam-5015	303	22	any	any	DET
ejpam-5015	303	23	trend	trend	NOUN
ejpam-5015	303	24	,	,	PUNCT
ejpam-5015	303	25	and	and	CCONJ
ejpam-5015	303	26	it	it	PRON
ejpam-5015	303	27	should	should	AUX
ejpam-5015	303	28	cover	cover	VERB
ejpam-5015	303	29	the	the	DET
ejpam-5015	303	30	entire	entire	ADJ
ejpam-5015	303	31	range	range	NOUN
ejpam-5015	303	32	of	of	ADP
ejpam-5015	303	33	plausible	plausible	ADJ
ejpam-5015	303	34	values	value	NOUN
ejpam-5015	303	35	for	for	ADP
ejpam-5015	303	36	the	the	DET
ejpam-5015	303	37	parameter	parameter	NOUN
ejpam-5015	303	38	,	,	PUNCT
ejpam-5015	303	39	meaning	mean	VERB
ejpam-5015	303	40	it	it	PRON
ejpam-5015	303	41	mixes	mix	VERB
ejpam-5015	303	42	well	well	ADV
ejpam-5015	303	43	.	.	PUNCT
ejpam-5015	304	1	figure	figure	NOUN
ejpam-5015	304	2	1	1	NUM
ejpam-5015	304	3	show	show	VERB
ejpam-5015	304	4	the	the	DET
ejpam-5015	304	5	values	value	NOUN
ejpam-5015	304	6	of	of	ADP
ejpam-5015	304	7	β0	β0	NOUN
ejpam-5015	304	8	,	,	PUNCT
ejpam-5015	304	9	β1	β1	PROPN
ejpam-5015	304	10	and	and	CCONJ
ejpam-5015	304	11	σ2	σ2	PROPN
ejpam-5015	304	12	b	b	PROPN
ejpam-5015	304	13	within	within	ADP
ejpam-5015	304	14	a	a	DET
ejpam-5015	304	15	stable	stable	ADJ
ejpam-5015	304	16	range	range	NOUN
ejpam-5015	304	17	after	after	ADP
ejpam-5015	304	18	a	a	DET
ejpam-5015	304	19	certain	certain	ADJ
ejpam-5015	304	20	number	number	NOUN
ejpam-5015	304	21	of	of	ADP
ejpam-5015	304	22	iterations	iteration	NOUN
ejpam-5015	304	23	.	.	PUNCT
ejpam-5015	305	1	this	this	PRON
ejpam-5015	305	2	indicates	indicate	VERB
ejpam-5015	305	3	that	that	SCONJ
ejpam-5015	305	4	the	the	DET
ejpam-5015	305	5	mcmc	mcmc	PROPN
ejpam-5015	305	6	simulation	simulation	PROPN
ejpam-5015	305	7	has	have	AUX
ejpam-5015	305	8	”	"	PUNCT
ejpam-5015	305	9	converged	converge	VERB
ejpam-5015	305	10	”	"	PUNCT
ejpam-5015	305	11	on	on	ADP
ejpam-5015	305	12	an	an	DET
ejpam-5015	305	13	estimate	estimate	NOUN
ejpam-5015	305	14	for	for	ADP
ejpam-5015	305	15	β0	β0	NOUN
ejpam-5015	305	16	,	,	PUNCT
ejpam-5015	305	17	β1	β1	PROPN
ejpam-5015	305	18	and	and	CCONJ
ejpam-5015	305	19	σ2	σ2	PROPN
ejpam-5015	305	20	b	b	PROPN
ejpam-5015	305	21	.	.	PUNCT
ejpam-5015	306	1	it	it	PRON
ejpam-5015	306	2	also	also	ADV
ejpam-5015	306	3	show	show	VERB
ejpam-5015	306	4	that	that	SCONJ
ejpam-5015	306	5	these	these	DET
ejpam-5015	306	6	three	three	NUM
ejpam-5015	306	7	parameters	parameter	NOUN
ejpam-5015	306	8	values	value	NOUN
ejpam-5015	306	9	are	be	AUX
ejpam-5015	306	10	”	"	PUNCT
ejpam-5015	306	11	mixing	mix	VERB
ejpam-5015	306	12	”	"	PUNCT
ejpam-5015	306	13	well	well	ADV
ejpam-5015	306	14	,	,	PUNCT
ejpam-5015	306	15	meaning	mean	VERB
ejpam-5015	306	16	they	they	PRON
ejpam-5015	306	17	move	move	VERB
ejpam-5015	306	18	freely	freely	ADV
ejpam-5015	306	19	and	and	CCONJ
ejpam-5015	306	20	explore	explore	VERB
ejpam-5015	306	21	the	the	DET
ejpam-5015	306	22	entire	entire	ADJ
ejpam-5015	306	23	range	range	NOUN
ejpam-5015	306	24	of	of	ADP
ejpam-5015	306	25	plausible	plausible	ADJ
ejpam-5015	306	26	values	value	NOUN
ejpam-5015	306	27	rather	rather	ADV
ejpam-5015	306	28	than	than	ADP
ejpam-5015	306	29	getting	getting	AUX
ejpam-5015	306	30	stuck	stick	VERB
ejpam-5015	306	31	in	in	ADP
ejpam-5015	306	32	particular	particular	ADJ
ejpam-5015	306	33	regions	region	NOUN
ejpam-5015	306	34	[	[	X
ejpam-5015	306	35	18	18	NUM
ejpam-5015	306	36	]	]	PUNCT
ejpam-5015	306	37	.	.	PUNCT
ejpam-5015	307	1	this	this	PRON
ejpam-5015	307	2	indicates	indicate	VERB
ejpam-5015	307	3	that	that	SCONJ
ejpam-5015	307	4	the	the	DET
ejpam-5015	307	5	mcmc	mcmc	PROPN
ejpam-5015	307	6	simulation	simulation	PROPN
ejpam-5015	307	7	is	be	AUX
ejpam-5015	307	8	effectively	effectively	ADV
ejpam-5015	307	9	exploring	explore	VERB
ejpam-5015	307	10	the	the	DET
ejpam-5015	307	11	full	full	ADJ
ejpam-5015	307	12	range	range	NOUN
ejpam-5015	307	13	of	of	ADP
ejpam-5015	307	14	possible	possible	ADJ
ejpam-5015	307	15	values	value	NOUN
ejpam-5015	307	16	for	for	ADP
ejpam-5015	307	17	β0	β0	NOUN
ejpam-5015	307	18	,	,	PUNCT
ejpam-5015	307	19	β1	β1	PROPN
ejpam-5015	307	20	and	and	CCONJ
ejpam-5015	307	21	σ2	σ2	PROPN
ejpam-5015	307	22	b	b	PROPN
ejpam-5015	307	23	.	.	PUNCT
ejpam-5015	308	1	we	we	PRON
ejpam-5015	308	2	conclude	conclude	VERB
ejpam-5015	308	3	from	from	ADP
ejpam-5015	308	4	figure	figure	NOUN
ejpam-5015	308	5	1	1	NUM
ejpam-5015	308	6	that	that	SCONJ
ejpam-5015	308	7	the	the	DET
ejpam-5015	308	8	mcmc	mcmc	PROPN
ejpam-5015	308	9	simulation	simulation	PROPN
ejpam-5015	308	10	is	be	AUX
ejpam-5015	308	11	likely	likely	ADJ
ejpam-5015	308	12	to	to	PART
ejpam-5015	308	13	provide	provide	VERB
ejpam-5015	308	14	a	a	DET
ejpam-5015	308	15	very	very	ADV
ejpam-5015	308	16	good	good	ADJ
ejpam-5015	308	17	estimate	estimate	NOUN
ejpam-5015	308	18	for	for	ADP
ejpam-5015	308	19	this	this	DET
ejpam-5015	308	20	three	three	NUM
ejpam-5015	308	21	parameter	parameter	NOUN
ejpam-5015	308	22	.	.	PUNCT
ejpam-5015	309	1	in	in	ADP
ejpam-5015	309	2	this	this	DET
ejpam-5015	309	3	study	study	NOUN
ejpam-5015	309	4	,	,	PUNCT
ejpam-5015	309	5	the	the	DET
ejpam-5015	309	6	benefits	benefit	NOUN
ejpam-5015	309	7	of	of	ADP
ejpam-5015	309	8	bayesian	bayesian	NOUN
ejpam-5015	309	9	estimates	estimate	NOUN
ejpam-5015	309	10	based	base	VERB
ejpam-5015	309	11	on	on	ADP
ejpam-5015	309	12	the	the	DET
ejpam-5015	309	13	median	median	NOUN
ejpam-5015	309	14	ranked	rank	VERB
ejpam-5015	309	15	set	set	ADJ
ejpam-5015	309	16	samples	sample	NOUN
ejpam-5015	309	17	(	(	PUNCT
ejpam-5015	309	18	mrss	mrss	ADV
ejpam-5015	309	19	)	)	PUNCT
ejpam-5015	309	20	have	have	AUX
ejpam-5015	309	21	been	be	AUX
ejpam-5015	309	22	explored	explore	VERB
ejpam-5015	309	23	.	.	PUNCT
ejpam-5015	310	1	this	this	DET
ejpam-5015	310	2	exploration	exploration	NOUN
ejpam-5015	310	3	is	be	AUX
ejpam-5015	310	4	carried	carry	VERB
ejpam-5015	310	5	out	out	ADP
ejpam-5015	310	6	via	via	ADP
ejpam-5015	310	7	mcmc	mcmc	PROPN
ejpam-5015	310	8	numerical	numerical	PROPN
ejpam-5015	310	9	simulations	simulation	NOUN
ejpam-5015	310	10	following	follow	VERB
ejpam-5015	310	11	the	the	DET
ejpam-5015	310	12	steps	step	NOUN
ejpam-5015	310	13	outlined	outline	VERB
ejpam-5015	310	14	below	below	ADV
ejpam-5015	310	15	:	:	PUNCT
ejpam-5015	310	16	•	•	NUM
ejpam-5015	310	17	generate	generate	NOUN
ejpam-5015	310	18	ranked	rank	VERB
ejpam-5015	310	19	set	set	VERB
ejpam-5015	310	20	samples	sample	NOUN
ejpam-5015	310	21	(	(	PUNCT
ejpam-5015	310	22	rss	rss	NOUN
ejpam-5015	310	23	)	)	PUNCT
ejpam-5015	310	24	of	of	ADP
ejpam-5015	310	25	size	size	NOUN
ejpam-5015	310	26	’	'	PUNCT
ejpam-5015	310	27	n	n	CCONJ
ejpam-5015	310	28	’	'	PUNCT
ejpam-5015	310	29	from	from	ADP
ejpam-5015	310	30	the	the	DET
ejpam-5015	310	31	full	full	ADJ
ejpam-5015	310	32	posterior	posterior	ADJ
ejpam-5015	310	33	distribution	distribution	NOUN
ejpam-5015	310	34	for	for	ADP
ejpam-5015	310	35	the	the	DET
ejpam-5015	310	36	case	case	NOUN
ejpam-5015	310	37	when	when	SCONJ
ejpam-5015	310	38	m	m	VERB
ejpam-5015	310	39	=	=	SYM
ejpam-5015	311	1	1	1	X
ejpam-5015	311	2	.	.	PUNCT
ejpam-5015	312	1	here	here	ADV
ejpam-5015	312	2	,	,	PUNCT
ejpam-5015	312	3	’	'	PUNCT
ejpam-5015	312	4	m	m	PRON
ejpam-5015	312	5	’	'	PUNCT
ejpam-5015	312	6	refers	refer	VERB
ejpam-5015	312	7	to	to	ADP
ejpam-5015	312	8	the	the	DET
ejpam-5015	312	9	number	number	NOUN
ejpam-5015	312	10	of	of	ADP
ejpam-5015	312	11	cycles	cycle	NOUN
ejpam-5015	312	12	used	use	VERB
ejpam-5015	312	13	in	in	ADP
ejpam-5015	312	14	the	the	DET
ejpam-5015	312	15	sampling	sampling	NOUN
ejpam-5015	312	16	process	process	NOUN
ejpam-5015	312	17	.	.	PUNCT
ejpam-5015	313	1	in	in	ADP
ejpam-5015	313	2	many	many	ADJ
ejpam-5015	313	3	practical	practical	ADJ
ejpam-5015	313	4	applications	application	NOUN
ejpam-5015	313	5	,	,	PUNCT
ejpam-5015	313	6	one	one	NUM
ejpam-5015	313	7	cycle	cycle	NOUN
ejpam-5015	313	8	(	(	PUNCT
ejpam-5015	313	9	m	m	NOUN
ejpam-5015	313	10	=	=	NOUN
ejpam-5015	313	11	1	1	NUM
ejpam-5015	313	12	)	)	PUNCT
ejpam-5015	313	13	is	be	AUX
ejpam-5015	313	14	commonly	commonly	ADV
ejpam-5015	313	15	used	use	VERB
ejpam-5015	313	16	.	.	PUNCT
ejpam-5015	314	1	i.	i.	PROPN
ejpam-5015	314	2	nawajah	nawajah	PROPN
ejpam-5015	314	3	,	,	PUNCT
ejpam-5015	314	4	h.	h.	PROPN
ejpam-5015	314	5	kanj	kanj	PROPN
ejpam-5015	314	6	,	,	PUNCT
ejpam-5015	314	7	y.	y.	PROPN
ejpam-5015	314	8	kotb	kotb	PROPN
ejpam-5015	314	9	,	,	PUNCT
ejpam-5015	314	10	j.	j.	PROPN
ejpam-5015	314	11	hoxha	hoxha	PROPN
ejpam-5015	314	12	,	,	PUNCT
ejpam-5015	314	13	m.	m.	PROPN
ejpam-5015	314	14	alakkoumi	alakkoumi	PROPN
ejpam-5015	314	15	,	,	PUNCT
ejpam-5015	314	16	k.	k.	PROPN
ejpam-5015	314	17	jebreen	jebreen	PROPN
ejpam-5015	314	18	/	/	SYM
ejpam-5015	314	19	eur	eur	PROPN
ejpam-5015	314	20	.	.	PUNCT
ejpam-5015	315	1	j.	j.	PROPN
ejpam-5015	315	2	pure	pure	PROPN
ejpam-5015	315	3	appl	appl	PROPN
ejpam-5015	315	4	.	.	PROPN
ejpam-5015	315	5	math	math	PROPN
ejpam-5015	315	6	,	,	PUNCT
ejpam-5015	315	7	17	17	NUM
ejpam-5015	315	8	(	(	PUNCT
ejpam-5015	315	9	1	1	NUM
ejpam-5015	315	10	)	)	PUNCT
ejpam-5015	315	11	(	(	PUNCT
ejpam-5015	315	12	2024	2024	NUM
ejpam-5015	315	13	)	)	PUNCT
ejpam-5015	315	14	,	,	PUNCT
ejpam-5015	315	15	180	180	NUM
ejpam-5015	315	16	-	-	SYM
ejpam-5015	315	17	200	200	NUM
ejpam-5015	315	18	195	195	NUM
ejpam-5015	315	19	β0	β0	NOUN
ejpam-5015	315	20	β1	β1	PROPN
ejpam-5015	315	21	σ2	σ2	PROPN
ejpam-5015	315	22	figure	figure	NOUN
ejpam-5015	315	23	1	1	NUM
ejpam-5015	315	24	:	:	PUNCT
ejpam-5015	315	25	trace	trace	NOUN
ejpam-5015	315	26	plot	plot	NOUN
ejpam-5015	315	27	of	of	ADP
ejpam-5015	315	28	the	the	DET
ejpam-5015	315	29	parameters	parameter	NOUN
ejpam-5015	315	30	β0	β0	PROPN
ejpam-5015	315	31	,	,	PUNCT
ejpam-5015	315	32	β1	β1	PROPN
ejpam-5015	315	33	,	,	PUNCT
ejpam-5015	315	34	and	and	CCONJ
ejpam-5015	315	35	σ2	σ2	NOUN
ejpam-5015	315	36	•	•	NUM
ejpam-5015	315	37	use	use	VERB
ejpam-5015	315	38	these	these	DET
ejpam-5015	315	39	rss	rss	NOUN
ejpam-5015	315	40	samples	sample	NOUN
ejpam-5015	315	41	to	to	PART
ejpam-5015	315	42	calculate	calculate	VERB
ejpam-5015	315	43	the	the	DET
ejpam-5015	315	44	bayesian	bayesian	NOUN
ejpam-5015	315	45	estimates	estimate	NOUN
ejpam-5015	315	46	as	as	SCONJ
ejpam-5015	315	47	described	describe	VERB
ejpam-5015	315	48	in	in	ADP
ejpam-5015	315	49	section	section	NOUN
ejpam-5015	315	50	5	5	NUM
ejpam-5015	315	51	.	.	PUNCT
ejpam-5015	316	1	these	these	DET
ejpam-5015	316	2	estimates	estimate	NOUN
ejpam-5015	316	3	rely	rely	VERB
ejpam-5015	316	4	on	on	ADP
ejpam-5015	316	5	the	the	DET
ejpam-5015	316	6	mrss	mrss	NOUN
ejpam-5015	316	7	samples	sample	NOUN
ejpam-5015	316	8	.	.	PUNCT
ejpam-5015	317	1	the	the	DET
ejpam-5015	317	2	estimates	estimate	NOUN
ejpam-5015	317	3	are	be	AUX
ejpam-5015	317	4	then	then	ADV
ejpam-5015	317	5	analyzed	analyze	VERB
ejpam-5015	317	6	in	in	ADP
ejpam-5015	317	7	two	two	NUM
ejpam-5015	317	8	ways	way	NOUN
ejpam-5015	317	9	:	:	PUNCT
ejpam-5015	317	10	•	•	NUM
ejpam-5015	317	11	point	point	NOUN
ejpam-5015	317	12	estimation	estimation	NOUN
ejpam-5015	317	13	:	:	PUNCT
ejpam-5015	317	14	the	the	DET
ejpam-5015	317	15	posterior	posterior	ADJ
ejpam-5015	317	16	mean	mean	NOUN
ejpam-5015	317	17	and	and	CCONJ
ejpam-5015	317	18	standard	standard	ADJ
ejpam-5015	317	19	error	error	NOUN
ejpam-5015	317	20	(	(	PUNCT
ejpam-5015	317	21	se	se	X
ejpam-5015	317	22	)	)	PUNCT
ejpam-5015	317	23	for	for	ADP
ejpam-5015	317	24	each	each	DET
ejpam-5015	317	25	parameter	parameter	NOUN
ejpam-5015	317	26	is	be	AUX
ejpam-5015	317	27	computed	compute	VERB
ejpam-5015	317	28	for	for	ADP
ejpam-5015	317	29	different	different	ADJ
ejpam-5015	317	30	values	value	NOUN
ejpam-5015	317	31	of	of	ADP
ejpam-5015	317	32	’	'	PUNCT
ejpam-5015	317	33	m	m	NOUN
ejpam-5015	317	34	’	'	PUNCT
ejpam-5015	317	35	.	.	PUNCT
ejpam-5015	318	1	these	these	DET
ejpam-5015	318	2	values	value	NOUN
ejpam-5015	318	3	are	be	AUX
ejpam-5015	318	4	presented	present	VERB
ejpam-5015	318	5	in	in	ADP
ejpam-5015	318	6	table	table	NOUN
ejpam-5015	318	7	1	1	NUM
ejpam-5015	318	8	.	.	PUNCT
ejpam-5015	319	1	this	this	DET
ejpam-5015	319	2	table	table	NOUN
ejpam-5015	319	3	includes	include	VERB
ejpam-5015	319	4	the	the	DET
ejpam-5015	319	5	mean	mean	NOUN
ejpam-5015	319	6	and	and	CCONJ
ejpam-5015	319	7	se	se	X
ejpam-5015	319	8	for	for	ADP
ejpam-5015	319	9	parameters	parameter	NOUN
ejpam-5015	319	10	β0	β0	PROPN
ejpam-5015	319	11	,	,	PUNCT
ejpam-5015	319	12	β1	β1	PROPN
ejpam-5015	319	13	and	and	CCONJ
ejpam-5015	319	14	σ2	σ2	PROPN
ejpam-5015	319	15	b	b	PROPN
ejpam-5015	319	16	,	,	PUNCT
ejpam-5015	319	17	under	under	ADP
ejpam-5015	319	18	different	different	ADJ
ejpam-5015	319	19	’	'	PUNCT
ejpam-5015	319	20	m	m	NOUN
ejpam-5015	319	21	’	'	PUNCT
ejpam-5015	319	22	values	value	NOUN
ejpam-5015	319	23	.	.	PUNCT
ejpam-5015	320	1	the	the	DET
ejpam-5015	320	2	’	'	PUNCT
ejpam-5015	320	3	m	m	NOUN
ejpam-5015	320	4	’	'	PUNCT
ejpam-5015	320	5	values	value	NOUN
ejpam-5015	320	6	are	be	AUX
ejpam-5015	320	7	increased	increase	VERB
ejpam-5015	320	8	from	from	ADP
ejpam-5015	320	9	3	3	NUM
ejpam-5015	320	10	to	to	ADP
ejpam-5015	320	11	7	7	NUM
ejpam-5015	320	12	.	.	PUNCT
ejpam-5015	321	1	a	a	DET
ejpam-5015	321	2	key	key	ADJ
ejpam-5015	321	3	observation	observation	NOUN
ejpam-5015	321	4	from	from	ADP
ejpam-5015	321	5	this	this	DET
ejpam-5015	321	6	table	table	NOUN
ejpam-5015	321	7	is	be	AUX
ejpam-5015	321	8	that	that	SCONJ
ejpam-5015	321	9	as	as	ADP
ejpam-5015	321	10	the	the	DET
ejpam-5015	321	11	value	value	NOUN
ejpam-5015	321	12	of	of	ADP
ejpam-5015	321	13	’	'	PUNCT
ejpam-5015	321	14	m	m	NOUN
ejpam-5015	321	15	’	'	PUNCT
ejpam-5015	321	16	increases	increase	NOUN
ejpam-5015	321	17	,	,	PUNCT
ejpam-5015	321	18	the	the	DET
ejpam-5015	321	19	bayesian	bayesian	NOUN
ejpam-5015	321	20	standard	standard	ADJ
ejpam-5015	321	21	error	error	NOUN
ejpam-5015	321	22	for	for	ADP
ejpam-5015	321	23	all	all	DET
ejpam-5015	321	24	parameters	parameter	NOUN
ejpam-5015	321	25	decreases	decrease	VERB
ejpam-5015	321	26	.	.	PUNCT
ejpam-5015	322	1	this	this	PRON
ejpam-5015	322	2	indicates	indicate	VERB
ejpam-5015	322	3	that	that	SCONJ
ejpam-5015	322	4	as	as	ADP
ejpam-5015	322	5	the	the	DET
ejpam-5015	322	6	cycle	cycle	NOUN
ejpam-5015	322	7	of	of	ADP
ejpam-5015	322	8	sampling	sample	VERB
ejpam-5015	322	9	increases	increase	NOUN
ejpam-5015	322	10	,	,	PUNCT
ejpam-5015	322	11	the	the	DET
ejpam-5015	322	12	accuracy	accuracy	NOUN
ejpam-5015	322	13	of	of	ADP
ejpam-5015	322	14	the	the	DET
ejpam-5015	322	15	estimates	estimate	NOUN
ejpam-5015	322	16	also	also	ADV
ejpam-5015	322	17	increases	increase	VERB
ejpam-5015	322	18	.	.	PUNCT
ejpam-5015	323	1	•	•	NUM
ejpam-5015	323	2	interval	interval	NOUN
ejpam-5015	323	3	estimation	estimation	NOUN
ejpam-5015	323	4	:	:	PUNCT
ejpam-5015	323	5	95	95	NUM
ejpam-5015	323	6	%	%	NOUN
ejpam-5015	323	7	credible	credible	ADJ
ejpam-5015	323	8	intervals	interval	NOUN
ejpam-5015	323	9	for	for	ADP
ejpam-5015	323	10	the	the	DET
ejpam-5015	323	11	mean	mean	ADJ
ejpam-5015	323	12	posterior	posterior	NOUN
ejpam-5015	323	13	of	of	ADP
ejpam-5015	323	14	the	the	DET
ejpam-5015	323	15	parameters	parameter	NOUN
ejpam-5015	323	16	are	be	AUX
ejpam-5015	323	17	also	also	ADV
ejpam-5015	323	18	calculated	calculate	VERB
ejpam-5015	323	19	.	.	PUNCT
ejpam-5015	324	1	these	these	DET
ejpam-5015	324	2	intervals	interval	NOUN
ejpam-5015	324	3	,	,	PUNCT
ejpam-5015	324	4	representing	represent	VERB
ejpam-5015	324	5	a	a	DET
ejpam-5015	324	6	range	range	NOUN
ejpam-5015	324	7	of	of	ADP
ejpam-5015	324	8	values	value	NOUN
ejpam-5015	324	9	within	within	ADP
ejpam-5015	324	10	which	which	PRON
ejpam-5015	324	11	the	the	DET
ejpam-5015	324	12	true	true	ADJ
ejpam-5015	324	13	parameter	parameter	NOUN
ejpam-5015	324	14	value	value	NOUN
ejpam-5015	324	15	lies	lie	VERB
ejpam-5015	324	16	with	with	ADP
ejpam-5015	324	17	95	95	NUM
ejpam-5015	324	18	%	%	NOUN
ejpam-5015	324	19	certainty	certainty	NOUN
ejpam-5015	324	20	,	,	PUNCT
ejpam-5015	324	21	are	be	AUX
ejpam-5015	324	22	presented	present	VERB
ejpam-5015	324	23	in	in	ADP
ejpam-5015	324	24	table	table	NOUN
ejpam-5015	324	25	2	2	NUM
ejpam-5015	324	26	.	.	PUNCT
ejpam-5015	325	1	here	here	ADV
ejpam-5015	325	2	,	,	PUNCT
ejpam-5015	325	3	for	for	ADP
ejpam-5015	325	4	each	each	DET
ejpam-5015	325	5	parameter	parameter	NOUN
ejpam-5015	325	6	and	and	CCONJ
ejpam-5015	325	7	for	for	ADP
ejpam-5015	325	8	different	different	ADJ
ejpam-5015	325	9	’	'	PUNCT
ejpam-5015	325	10	m	m	NOUN
ejpam-5015	325	11	’	'	PUNCT
ejpam-5015	325	12	values	value	NOUN
ejpam-5015	325	13	,	,	PUNCT
ejpam-5015	325	14	the	the	DET
ejpam-5015	325	15	2.5th	2.5th	PROPN
ejpam-5015	325	16	percentile	percentile	NOUN
ejpam-5015	325	17	and	and	CCONJ
ejpam-5015	325	18	the	the	DET
ejpam-5015	325	19	97.5th	97.5th	ADJ
ejpam-5015	325	20	percentile	percentile	ADJ
ejpam-5015	325	21	values	value	NOUN
ejpam-5015	325	22	are	be	AUX
ejpam-5015	325	23	reported	report	VERB
ejpam-5015	325	24	.	.	PUNCT
ejpam-5015	326	1	the	the	DET
ejpam-5015	326	2	range	range	NOUN
ejpam-5015	326	3	between	between	ADP
ejpam-5015	326	4	these	these	DET
ejpam-5015	326	5	two	two	NUM
ejpam-5015	326	6	percentile	percentile	ADJ
ejpam-5015	326	7	values	value	NOUN
ejpam-5015	326	8	forms	form	VERB
ejpam-5015	326	9	the	the	DET
ejpam-5015	326	10	95	95	NUM
ejpam-5015	326	11	%	%	NOUN
ejpam-5015	326	12	credible	credible	ADJ
ejpam-5015	326	13	interval	interval	NOUN
ejpam-5015	326	14	.	.	PUNCT
ejpam-5015	327	1	the	the	DET
ejpam-5015	327	2	tables	table	NOUN
ejpam-5015	327	3	illustrate	illustrate	VERB
ejpam-5015	327	4	that	that	SCONJ
ejpam-5015	327	5	as	as	ADP
ejpam-5015	327	6	the	the	DET
ejpam-5015	327	7	number	number	NOUN
ejpam-5015	327	8	of	of	ADP
ejpam-5015	327	9	cycles	cycle	NOUN
ejpam-5015	327	10	’	'	PUNCT
ejpam-5015	327	11	m	m	NOUN
ejpam-5015	327	12	’	'	PUNCT
ejpam-5015	327	13	increases	increase	NOUN
ejpam-5015	327	14	,	,	PUNCT
ejpam-5015	327	15	the	the	DET
ejpam-5015	327	16	posterior	posterior	ADJ
ejpam-5015	327	17	means	mean	VERB
ejpam-5015	327	18	become	become	VERB
ejpam-5015	327	19	more	more	ADV
ejpam-5015	327	20	accurate	accurate	ADJ
ejpam-5015	327	21	(	(	PUNCT
ejpam-5015	327	22	se	se	INTJ
ejpam-5015	327	23	decreases	decrease	NOUN
ejpam-5015	327	24	)	)	PUNCT
ejpam-5015	327	25	and	and	CCONJ
ejpam-5015	327	26	the	the	DET
ejpam-5015	327	27	credible	credible	ADJ
ejpam-5015	327	28	intervals	interval	NOUN
ejpam-5015	327	29	become	become	VERB
ejpam-5015	327	30	narrower	narrow	ADJ
ejpam-5015	327	31	.	.	PUNCT
ejpam-5015	328	1	these	these	DET
ejpam-5015	328	2	outcomes	outcome	NOUN
ejpam-5015	328	3	suggest	suggest	VERB
ejpam-5015	328	4	that	that	SCONJ
ejpam-5015	328	5	by	by	ADP
ejpam-5015	328	6	using	use	VERB
ejpam-5015	328	7	more	more	ADJ
ejpam-5015	328	8	cycles	cycle	NOUN
ejpam-5015	328	9	in	in	ADP
ejpam-5015	328	10	the	the	DET
ejpam-5015	328	11	mrss	mrss	NOUN
ejpam-5015	328	12	sampling	sampling	NOUN
ejpam-5015	328	13	,	,	PUNCT
ejpam-5015	328	14	we	we	PRON
ejpam-5015	328	15	can	can	AUX
ejpam-5015	328	16	achieve	achieve	VERB
ejpam-5015	328	17	more	more	ADV
ejpam-5015	328	18	precise	precise	ADJ
ejpam-5015	328	19	estimates	estimate	NOUN
ejpam-5015	328	20	and	and	CCONJ
ejpam-5015	328	21	more	more	ADJ
ejpam-5015	328	22	confidence	confidence	NOUN
ejpam-5015	328	23	about	about	ADP
ejpam-5015	328	24	where	where	SCONJ
ejpam-5015	328	25	the	the	DET
ejpam-5015	328	26	true	true	ADJ
ejpam-5015	328	27	parameter	parameter	NOUN
ejpam-5015	328	28	values	value	NOUN
ejpam-5015	328	29	lie	lie	VERB
ejpam-5015	328	30	.	.	PUNCT
ejpam-5015	329	1	from	from	ADP
ejpam-5015	329	2	the	the	DET
ejpam-5015	329	3	tables	table	NOUN
ejpam-5015	329	4	provided	provide	VERB
ejpam-5015	329	5	,	,	PUNCT
ejpam-5015	329	6	we	we	PRON
ejpam-5015	329	7	can	can	AUX
ejpam-5015	329	8	also	also	ADV
ejpam-5015	329	9	infer	infer	VERB
ejpam-5015	329	10	that	that	SCONJ
ejpam-5015	329	11	as	as	SCONJ
ejpam-5015	329	12	the	the	DET
ejpam-5015	329	13	number	number	NOUN
ejpam-5015	329	14	of	of	ADP
ejpam-5015	329	15	cycles	cycle	NOUN
ejpam-5015	329	16	(	(	PUNCT
ejpam-5015	329	17	m	m	NOUN
ejpam-5015	329	18	)	)	PUNCT
ejpam-5015	329	19	increases	increase	NOUN
ejpam-5015	329	20	,	,	PUNCT
ejpam-5015	329	21	not	not	PART
ejpam-5015	329	22	only	only	ADV
ejpam-5015	329	23	does	do	AUX
ejpam-5015	329	24	the	the	DET
ejpam-5015	329	25	precision	precision	NOUN
ejpam-5015	329	26	of	of	ADP
ejpam-5015	329	27	our	our	PRON
ejpam-5015	329	28	estimates	estimate	NOUN
ejpam-5015	329	29	improve	improve	AUX
ejpam-5015	329	30	(	(	PUNCT
ejpam-5015	329	31	seen	see	VERB
ejpam-5015	329	32	by	by	ADP
ejpam-5015	329	33	decreasing	decrease	VERB
ejpam-5015	329	34	standard	standard	ADJ
ejpam-5015	329	35	error	error	NOUN
ejpam-5015	329	36	)	)	PUNCT
ejpam-5015	329	37	,	,	PUNCT
ejpam-5015	329	38	but	but	CCONJ
ejpam-5015	329	39	our	our	PRON
ejpam-5015	329	40	credible	credible	ADJ
ejpam-5015	329	41	intervals	interval	NOUN
ejpam-5015	329	42	become	become	VERB
ejpam-5015	329	43	narrower	narrow	ADJ
ejpam-5015	329	44	.	.	PUNCT
ejpam-5015	330	1	this	this	PRON
ejpam-5015	330	2	indicates	indicate	VERB
ejpam-5015	330	3	that	that	SCONJ
ejpam-5015	330	4	our	our	PRON
ejpam-5015	330	5	certainty	certainty	NOUN
ejpam-5015	330	6	about	about	ADP
ejpam-5015	330	7	the	the	DET
ejpam-5015	330	8	true	true	ADJ
ejpam-5015	330	9	values	value	NOUN
ejpam-5015	330	10	of	of	ADP
ejpam-5015	330	11	the	the	DET
ejpam-5015	330	12	parameters	parameter	NOUN
ejpam-5015	330	13	increases	increase	VERB
ejpam-5015	330	14	.	.	PUNCT
ejpam-5015	331	1	the	the	DET
ejpam-5015	331	2	findings	finding	NOUN
ejpam-5015	331	3	support	support	VERB
ejpam-5015	331	4	the	the	DET
ejpam-5015	331	5	use	use	NOUN
ejpam-5015	331	6	of	of	ADP
ejpam-5015	331	7	larger	large	ADJ
ejpam-5015	331	8	’	'	PUNCT
ejpam-5015	331	9	m	m	NOUN
ejpam-5015	331	10	’	'	PUNCT
ejpam-5015	331	11	values	value	NOUN
ejpam-5015	331	12	in	in	ADP
ejpam-5015	331	13	applications	application	NOUN
ejpam-5015	331	14	where	where	SCONJ
ejpam-5015	331	15	precision	precision	NOUN
ejpam-5015	331	16	is	be	AUX
ejpam-5015	331	17	critical	critical	ADJ
ejpam-5015	331	18	.	.	PUNCT
ejpam-5015	332	1	however	however	ADV
ejpam-5015	332	2	,	,	PUNCT
ejpam-5015	332	3	larger	large	ADJ
ejpam-5015	332	4	’	'	PUNCT
ejpam-5015	332	5	m	m	NOUN
ejpam-5015	332	6	’	'	PUNCT
ejpam-5015	332	7	values	value	NOUN
ejpam-5015	332	8	may	may	AUX
ejpam-5015	332	9	involve	involve	VERB
ejpam-5015	332	10	more	more	ADJ
ejpam-5015	332	11	i.	i.	PROPN
ejpam-5015	332	12	nawajah	nawajah	PROPN
ejpam-5015	332	13	,	,	PUNCT
ejpam-5015	332	14	h.	h.	PROPN
ejpam-5015	332	15	kanj	kanj	PROPN
ejpam-5015	332	16	,	,	PUNCT
ejpam-5015	332	17	y.	y.	PROPN
ejpam-5015	332	18	kotb	kotb	PROPN
ejpam-5015	332	19	,	,	PUNCT
ejpam-5015	332	20	j.	j.	PROPN
ejpam-5015	332	21	hoxha	hoxha	PROPN
ejpam-5015	332	22	,	,	PUNCT
ejpam-5015	332	23	m.	m.	PROPN
ejpam-5015	332	24	alakkoumi	alakkoumi	PROPN
ejpam-5015	332	25	,	,	PUNCT
ejpam-5015	332	26	k.	k.	PROPN
ejpam-5015	332	27	jebreen	jebreen	PROPN
ejpam-5015	332	28	/	/	SYM
ejpam-5015	332	29	eur	eur	PROPN
ejpam-5015	332	30	.	.	PUNCT
ejpam-5015	333	1	j.	j.	PROPN
ejpam-5015	333	2	pure	pure	PROPN
ejpam-5015	333	3	appl	appl	PROPN
ejpam-5015	333	4	.	.	PROPN
ejpam-5015	333	5	math	math	PROPN
ejpam-5015	333	6	,	,	PUNCT
ejpam-5015	333	7	17	17	NUM
ejpam-5015	333	8	(	(	PUNCT
ejpam-5015	333	9	1	1	NUM
ejpam-5015	333	10	)	)	PUNCT
ejpam-5015	333	11	(	(	PUNCT
ejpam-5015	333	12	2024	2024	NUM
ejpam-5015	333	13	)	)	PUNCT
ejpam-5015	333	14	,	,	PUNCT
ejpam-5015	333	15	180	180	NUM
ejpam-5015	333	16	-	-	SYM
ejpam-5015	333	17	200	200	NUM
ejpam-5015	333	18	196	196	NUM
ejpam-5015	333	19	complex	complex	ADJ
ejpam-5015	333	20	computations	computation	NOUN
ejpam-5015	333	21	or	or	CCONJ
ejpam-5015	333	22	more	more	ADV
ejpam-5015	333	23	extensive	extensive	ADJ
ejpam-5015	333	24	data	datum	NOUN
ejpam-5015	333	25	collection	collection	NOUN
ejpam-5015	333	26	.	.	PUNCT
ejpam-5015	334	1	the	the	DET
ejpam-5015	334	2	fact	fact	NOUN
ejpam-5015	334	3	that	that	SCONJ
ejpam-5015	334	4	standard	standard	ADJ
ejpam-5015	334	5	errors	error	NOUN
ejpam-5015	334	6	decrease	decrease	VERB
ejpam-5015	334	7	as	as	ADP
ejpam-5015	334	8	’	'	PUNCT
ejpam-5015	334	9	m	m	PART
ejpam-5015	334	10	’	'	PUNCT
ejpam-5015	334	11	increases	increase	NOUN
ejpam-5015	334	12	suggests	suggest	VERB
ejpam-5015	334	13	that	that	SCONJ
ejpam-5015	334	14	the	the	DET
ejpam-5015	334	15	estimator	estimator	NOUN
ejpam-5015	334	16	becomes	become	VERB
ejpam-5015	334	17	more	more	ADV
ejpam-5015	334	18	efficient	efficient	ADJ
ejpam-5015	334	19	with	with	ADP
ejpam-5015	334	20	more	more	ADJ
ejpam-5015	334	21	cycles	cycle	NOUN
ejpam-5015	334	22	,	,	PUNCT
ejpam-5015	334	23	which	which	PRON
ejpam-5015	334	24	is	be	AUX
ejpam-5015	334	25	advantageous	advantageous	ADJ
ejpam-5015	334	26	in	in	ADP
ejpam-5015	334	27	providing	provide	VERB
ejpam-5015	334	28	more	more	ADV
ejpam-5015	334	29	reliable	reliable	ADJ
ejpam-5015	334	30	estimates	estimate	NOUN
ejpam-5015	334	31	.	.	PUNCT
ejpam-5015	335	1	table	table	NOUN
ejpam-5015	335	2	1	1	NUM
ejpam-5015	335	3	:	:	PUNCT
ejpam-5015	335	4	the	the	DET
ejpam-5015	335	5	posterior	posterior	ADJ
ejpam-5015	335	6	mean	mean	NOUN
ejpam-5015	335	7	and	and	CCONJ
ejpam-5015	335	8	the	the	DET
ejpam-5015	335	9	standard	standard	ADJ
ejpam-5015	335	10	error	error	NOUN
ejpam-5015	335	11	(	(	PUNCT
ejpam-5015	335	12	se	se	X
ejpam-5015	335	13	)	)	PUNCT
ejpam-5015	335	14	for	for	ADP
ejpam-5015	335	15	the	the	DET
ejpam-5015	335	16	parameters	parameter	NOUN
ejpam-5015	335	17	at	at	ADP
ejpam-5015	335	18	different	different	ADJ
ejpam-5015	335	19	m.	m.	NOUN
ejpam-5015	335	20	β̂0	β̂0	X
ejpam-5015	336	1	β̂1	β̂1	PUNCT
ejpam-5015	336	2	σ̂2	σ̂2	NOUN
ejpam-5015	336	3	mean	mean	INTJ
ejpam-5015	336	4	se	se	INTJ
ejpam-5015	336	5	mean	mean	PROPN
ejpam-5015	336	6	se	se	PROPN
ejpam-5015	336	7	mean	mean	PROPN
ejpam-5015	336	8	se	se	PROPN
ejpam-5015	337	1	m=3	m=3	PROPN
ejpam-5015	337	2	1.5	1.5	NUM
ejpam-5015	337	3	0.65	0.65	NUM
ejpam-5015	337	4	2.24	2.24	NUM
ejpam-5015	337	5	0.54	0.54	NUM
ejpam-5015	337	6	0.17	0.17	NUM
ejpam-5015	337	7	0.057	0.057	NUM
ejpam-5015	337	8	m=5	m=5	NUM
ejpam-5015	337	9	1.24	1.24	NUM
ejpam-5015	337	10	0.55	0.55	NUM
ejpam-5015	337	11	2.13	2.13	NUM
ejpam-5015	337	12	0.41	0.41	NUM
ejpam-5015	337	13	0.09	0.09	NUM
ejpam-5015	337	14	0.0096	0.0096	NUM
ejpam-5015	337	15	m=7	m=7	NOUN
ejpam-5015	338	1	1.12	1.12	NUM
ejpam-5015	338	2	0.34	0.34	NUM
ejpam-5015	338	3	2.03	2.03	NUM
ejpam-5015	338	4	0.30	0.30	NUM
ejpam-5015	338	5	0.07	0.07	NUM
ejpam-5015	338	6	0.0067	0.0067	NUM
ejpam-5015	338	7	the	the	DET
ejpam-5015	338	8	95	95	NUM
ejpam-5015	338	9	%	%	NOUN
ejpam-5015	338	10	credible	credible	ADJ
ejpam-5015	338	11	intervals	interval	NOUN
ejpam-5015	338	12	for	for	ADP
ejpam-5015	338	13	the	the	DET
ejpam-5015	338	14	parameters	parameter	NOUN
ejpam-5015	338	15	at	at	ADP
ejpam-5015	338	16	different	different	ADJ
ejpam-5015	338	17	m.	m.	NOUN
ejpam-5015	338	18	β̂0	β̂0	X
ejpam-5015	339	1	β̂1	β̂1	PUNCT
ejpam-5015	339	2	σ̂2	σ̂2	NOUN
ejpam-5015	339	3	2.5	2.5	NUM
ejpam-5015	339	4	%	%	NOUN
ejpam-5015	339	5	97.5	97.5	NUM
ejpam-5015	339	6	%	%	NOUN
ejpam-5015	339	7	2.5	2.5	NUM
ejpam-5015	339	8	%	%	NOUN
ejpam-5015	339	9	97.5	97.5	NUM
ejpam-5015	339	10	%	%	NOUN
ejpam-5015	339	11	2.5	2.5	NUM
ejpam-5015	339	12	%	%	NOUN
ejpam-5015	339	13	97.5	97.5	NUM
ejpam-5015	339	14	%	%	NOUN
ejpam-5015	339	15	m=3	m=3	PROPN
ejpam-5015	339	16	1.22	1.22	NUM
ejpam-5015	339	17	2.87	2.87	NUM
ejpam-5015	339	18	2.04	2.04	NUM
ejpam-5015	339	19	3.55	3.55	NUM
ejpam-5015	339	20	0.05	0.05	NUM
ejpam-5015	339	21	0.18	0.18	NUM
ejpam-5015	339	22	m=5	m=5	PROPN
ejpam-5015	339	23	1.12	1.12	NUM
ejpam-5015	339	24	2.06	2.06	NUM
ejpam-5015	339	25	1.85	1.85	NUM
ejpam-5015	339	26	2.34	2.34	NUM
ejpam-5015	339	27	0.06	0.06	NUM
ejpam-5015	339	28	0.11	0.11	NUM
ejpam-5015	339	29	m=7	m=7	NOUN
ejpam-5015	339	30	0.97	0.97	NUM
ejpam-5015	339	31	1.76	1.76	NUM
ejpam-5015	339	32	1.67	1.67	NUM
ejpam-5015	339	33	2.65	2.65	NUM
ejpam-5015	339	34	0.05	0.05	NUM
ejpam-5015	339	35	0.10	0.10	NUM
ejpam-5015	339	36	table	table	NOUN
ejpam-5015	339	37	3	3	NUM
ejpam-5015	339	38	compare	compare	VERB
ejpam-5015	339	39	the	the	DET
ejpam-5015	339	40	efficiency	efficiency	NOUN
ejpam-5015	339	41	of	of	ADP
ejpam-5015	339	42	bayesian	bayesian	NOUN
ejpam-5015	339	43	and	and	CCONJ
ejpam-5015	339	44	frequentist	frequentist	NOUN
ejpam-5015	339	45	mean	mean	VERB
ejpam-5015	339	46	rank	rank	NOUN
ejpam-5015	339	47	set	set	NOUN
ejpam-5015	339	48	sampling	sample	VERB
ejpam-5015	339	49	(	(	PUNCT
ejpam-5015	339	50	mrss	mrss	ADJ
ejpam-5015	339	51	)	)	PUNCT
ejpam-5015	339	52	methods	method	NOUN
ejpam-5015	339	53	for	for	ADP
ejpam-5015	339	54	estimating	estimate	VERB
ejpam-5015	339	55	the	the	DET
ejpam-5015	339	56	parameters	parameter	NOUN
ejpam-5015	339	57	of	of	ADP
ejpam-5015	339	58	a	a	DET
ejpam-5015	339	59	simple	simple	ADJ
ejpam-5015	339	60	regression	regression	NOUN
ejpam-5015	339	61	model	model	NOUN
ejpam-5015	339	62	.	.	PUNCT
ejpam-5015	340	1	the	the	DET
ejpam-5015	340	2	efficiency	efficiency	NOUN
ejpam-5015	340	3	is	be	AUX
ejpam-5015	340	4	calculated	calculate	VERB
ejpam-5015	340	5	as	as	ADP
ejpam-5015	340	6	the	the	DET
ejpam-5015	340	7	ratio	ratio	NOUN
ejpam-5015	340	8	of	of	ADP
ejpam-5015	340	9	the	the	DET
ejpam-5015	340	10	mean	mean	ADJ
ejpam-5015	340	11	squared	square	VERB
ejpam-5015	340	12	errors	error	NOUN
ejpam-5015	340	13	(	(	PUNCT
ejpam-5015	340	14	mses	ms	NOUN
ejpam-5015	340	15	)	)	PUNCT
ejpam-5015	340	16	of	of	ADP
ejpam-5015	340	17	the	the	DET
ejpam-5015	340	18	parameter	parameter	NOUN
ejpam-5015	340	19	estimates	estimate	NOUN
ejpam-5015	340	20	from	from	ADP
ejpam-5015	340	21	the	the	DET
ejpam-5015	340	22	two	two	NUM
ejpam-5015	340	23	methods	method	NOUN
ejpam-5015	340	24	.	.	PUNCT
ejpam-5015	341	1	specifically	specifically	ADV
ejpam-5015	341	2	,	,	PUNCT
ejpam-5015	341	3	the	the	DET
ejpam-5015	341	4	mse	mse	NOUN
ejpam-5015	341	5	of	of	ADP
ejpam-5015	341	6	a	a	DET
ejpam-5015	341	7	parameter	parameter	NOUN
ejpam-5015	341	8	estimate	estimate	NOUN
ejpam-5015	341	9	using	use	VERB
ejpam-5015	341	10	the	the	DET
ejpam-5015	341	11	frequentist	frequentist	NOUN
ejpam-5015	341	12	mrss	mrss	NOUN
ejpam-5015	341	13	method	method	NOUN
ejpam-5015	341	14	(	(	PUNCT
ejpam-5015	341	15	denoted	denote	VERB
ejpam-5015	341	16	by	by	ADP
ejpam-5015	341	17	θ̂2	θ̂2	NOUN
ejpam-5015	341	18	)	)	PUNCT
ejpam-5015	341	19	is	be	AUX
ejpam-5015	341	20	divided	divide	VERB
ejpam-5015	341	21	by	by	ADP
ejpam-5015	341	22	the	the	DET
ejpam-5015	341	23	mse	mse	NOUN
ejpam-5015	341	24	of	of	ADP
ejpam-5015	341	25	the	the	DET
ejpam-5015	341	26	same	same	ADJ
ejpam-5015	341	27	parameter	parameter	NOUN
ejpam-5015	341	28	estimate	estimate	NOUN
ejpam-5015	341	29	using	use	VERB
ejpam-5015	341	30	the	the	DET
ejpam-5015	341	31	bayesian	bayesian	NOUN
ejpam-5015	341	32	mrss	mrss	NOUN
ejpam-5015	341	33	method	method	NOUN
ejpam-5015	341	34	(	(	PUNCT
ejpam-5015	341	35	denoted	denote	VERB
ejpam-5015	341	36	by	by	ADP
ejpam-5015	341	37	θ̂1	θ̂1	NOUN
ejpam-5015	341	38	)	)	PUNCT
ejpam-5015	341	39	.	.	PUNCT
ejpam-5015	342	1	the	the	DET
ejpam-5015	342	2	table	table	NOUN
ejpam-5015	342	3	lists	list	VERB
ejpam-5015	342	4	the	the	DET
ejpam-5015	342	5	efficiency	efficiency	NOUN
ejpam-5015	342	6	ratios	ratio	NOUN
ejpam-5015	342	7	for	for	ADP
ejpam-5015	342	8	the	the	DET
ejpam-5015	342	9	three	three	NUM
ejpam-5015	342	10	parameters	parameter	NOUN
ejpam-5015	342	11	of	of	ADP
ejpam-5015	342	12	interest	interest	NOUN
ejpam-5015	342	13	:	:	PUNCT
ejpam-5015	342	14	β0	β0	ADJ
ejpam-5015	342	15	,	,	PUNCT
ejpam-5015	342	16	β1	β1	PROPN
ejpam-5015	342	17	and	and	CCONJ
ejpam-5015	342	18	σ2	σ2	PROPN
ejpam-5015	342	19	b	b	PROPN
ejpam-5015	342	20	.	.	PUNCT
ejpam-5015	343	1	each	each	DET
ejpam-5015	343	2	row	row	NOUN
ejpam-5015	343	3	in	in	ADP
ejpam-5015	343	4	the	the	DET
ejpam-5015	343	5	table	table	NOUN
ejpam-5015	343	6	corresponds	correspond	VERB
ejpam-5015	343	7	to	to	ADP
ejpam-5015	343	8	a	a	DET
ejpam-5015	343	9	different	different	ADJ
ejpam-5015	343	10	value	value	NOUN
ejpam-5015	343	11	of	of	ADP
ejpam-5015	343	12	’	'	PUNCT
ejpam-5015	343	13	m	m	NOUN
ejpam-5015	343	14	’	'	PUNCT
ejpam-5015	343	15	,	,	PUNCT
ejpam-5015	343	16	the	the	DET
ejpam-5015	343	17	size	size	NOUN
ejpam-5015	343	18	of	of	ADP
ejpam-5015	343	19	the	the	DET
ejpam-5015	343	20	cycle	cycle	NOUN
ejpam-5015	343	21	in	in	ADP
ejpam-5015	343	22	mrss	mrss	NOUN
ejpam-5015	343	23	.	.	PUNCT
ejpam-5015	344	1	each	each	DET
ejpam-5015	344	2	efficiency	efficiency	NOUN
ejpam-5015	344	3	value	value	NOUN
ejpam-5015	344	4	in	in	ADP
ejpam-5015	344	5	the	the	DET
ejpam-5015	344	6	table	table	NOUN
ejpam-5015	344	7	(	(	PUNCT
ejpam-5015	344	8	like	like	ADP
ejpam-5015	344	9	1.29	1.29	NUM
ejpam-5015	344	10	,	,	PUNCT
ejpam-5015	344	11	1.76	1.76	NUM
ejpam-5015	344	12	,	,	PUNCT
ejpam-5015	344	13	etc	etc	X
ejpam-5015	344	14	.	.	X
ejpam-5015	344	15	)	)	PUNCT
ejpam-5015	344	16	is	be	AUX
ejpam-5015	344	17	calculated	calculate	VERB
ejpam-5015	344	18	as	as	ADP
ejpam-5015	344	19	the	the	DET
ejpam-5015	344	20	mse	mse	NOUN
ejpam-5015	344	21	of	of	ADP
ejpam-5015	344	22	the	the	DET
ejpam-5015	344	23	frequentist	frequentist	NOUN
ejpam-5015	344	24	mrss	mrss	NOUN
ejpam-5015	344	25	estimate	estimate	NOUN
ejpam-5015	344	26	divided	divide	VERB
ejpam-5015	344	27	by	by	ADP
ejpam-5015	344	28	the	the	DET
ejpam-5015	344	29	mse	mse	NOUN
ejpam-5015	344	30	of	of	ADP
ejpam-5015	344	31	the	the	DET
ejpam-5015	344	32	bayesian	bayesian	NOUN
ejpam-5015	344	33	mrss	mrss	NOUN
ejpam-5015	344	34	estimate	estimate	NOUN
ejpam-5015	344	35	for	for	ADP
ejpam-5015	344	36	a	a	DET
ejpam-5015	344	37	given	give	VERB
ejpam-5015	344	38	parameter	parameter	NOUN
ejpam-5015	344	39	and	and	CCONJ
ejpam-5015	344	40	’	'	PUNCT
ejpam-5015	344	41	m	m	NOUN
ejpam-5015	344	42	’	'	PUNCT
ejpam-5015	344	43	value	value	NOUN
ejpam-5015	344	44	.	.	PUNCT
ejpam-5015	345	1	this	this	DET
ejpam-5015	345	2	efficiency	efficiency	NOUN
ejpam-5015	345	3	ratio	ratio	NOUN
ejpam-5015	345	4	measures	measure	NOUN
ejpam-5015	345	5	how	how	SCONJ
ejpam-5015	345	6	well	well	ADV
ejpam-5015	345	7	the	the	DET
ejpam-5015	345	8	bayesian	bayesian	NOUN
ejpam-5015	345	9	method	method	NOUN
ejpam-5015	345	10	performs	perform	VERB
ejpam-5015	345	11	in	in	ADP
ejpam-5015	345	12	comparison	comparison	NOUN
ejpam-5015	345	13	to	to	ADP
ejpam-5015	345	14	the	the	DET
ejpam-5015	345	15	frequentist	frequentist	NOUN
ejpam-5015	345	16	method	method	NOUN
ejpam-5015	345	17	.	.	PUNCT
ejpam-5015	346	1	the	the	DET
ejpam-5015	346	2	mse	mse	PROPN
ejpam-5015	346	3	is	be	AUX
ejpam-5015	346	4	a	a	DET
ejpam-5015	346	5	common	common	ADJ
ejpam-5015	346	6	measure	measure	NOUN
ejpam-5015	346	7	of	of	ADP
ejpam-5015	346	8	an	an	DET
ejpam-5015	346	9	estimator	estimator	NOUN
ejpam-5015	346	10	’s	’s	PART
ejpam-5015	346	11	quality	quality	NOUN
ejpam-5015	346	12	:	:	PUNCT
ejpam-5015	346	13	the	the	PRON
ejpam-5015	346	14	smaller	small	ADJ
ejpam-5015	346	15	the	the	DET
ejpam-5015	346	16	mse	mse	NOUN
ejpam-5015	346	17	,	,	PUNCT
ejpam-5015	346	18	the	the	DET
ejpam-5015	346	19	better	well	ADJ
ejpam-5015	346	20	the	the	DET
ejpam-5015	346	21	estimator	estimator	NOUN
ejpam-5015	346	22	.	.	PUNCT
ejpam-5015	347	1	the	the	DET
ejpam-5015	347	2	efficiencies	efficiency	NOUN
ejpam-5015	347	3	are	be	AUX
ejpam-5015	347	4	all	all	ADV
ejpam-5015	347	5	greater	great	ADJ
ejpam-5015	347	6	than	than	ADP
ejpam-5015	347	7	one	one	NUM
ejpam-5015	347	8	,	,	PUNCT
ejpam-5015	347	9	indicating	indicate	VERB
ejpam-5015	347	10	that	that	SCONJ
ejpam-5015	347	11	the	the	DET
ejpam-5015	347	12	bayesian	bayesian	NOUN
ejpam-5015	347	13	mrss	mrss	NOUN
ejpam-5015	347	14	method	method	NOUN
ejpam-5015	347	15	is	be	AUX
ejpam-5015	347	16	more	more	ADV
ejpam-5015	347	17	efficient	efficient	ADJ
ejpam-5015	347	18	than	than	ADP
ejpam-5015	347	19	the	the	DET
ejpam-5015	347	20	frequentist	frequentist	NOUN
ejpam-5015	347	21	mrss	mrss	NOUN
ejpam-5015	347	22	method	method	NOUN
ejpam-5015	347	23	for	for	ADP
ejpam-5015	347	24	all	all	DET
ejpam-5015	347	25	parameter	parameter	NOUN
ejpam-5015	347	26	estimates	estimate	NOUN
ejpam-5015	347	27	and	and	CCONJ
ejpam-5015	347	28	all	all	DET
ejpam-5015	347	29	values	value	NOUN
ejpam-5015	347	30	of	of	ADP
ejpam-5015	347	31	’	'	PUNCT
ejpam-5015	347	32	m	m	NOUN
ejpam-5015	347	33	’	'	PUNCT
ejpam-5015	347	34	.	.	PUNCT
ejpam-5015	348	1	this	this	PRON
ejpam-5015	348	2	is	be	AUX
ejpam-5015	348	3	because	because	SCONJ
ejpam-5015	348	4	a	a	DET
ejpam-5015	348	5	smaller	small	ADJ
ejpam-5015	348	6	mse	mse	NOUN
ejpam-5015	348	7	(	(	PUNCT
ejpam-5015	348	8	which	which	PRON
ejpam-5015	348	9	implies	imply	VERB
ejpam-5015	348	10	better	well	ADJ
ejpam-5015	348	11	performance	performance	NOUN
ejpam-5015	348	12	)	)	PUNCT
ejpam-5015	348	13	for	for	ADP
ejpam-5015	348	14	the	the	DET
ejpam-5015	348	15	bayesian	bayesian	NOUN
ejpam-5015	348	16	method	method	NOUN
ejpam-5015	348	17	results	result	NOUN
ejpam-5015	348	18	in	in	ADP
ejpam-5015	348	19	a	a	DET
ejpam-5015	348	20	larger	large	ADJ
ejpam-5015	348	21	efficiency	efficiency	NOUN
ejpam-5015	348	22	ratio	ratio	NOUN
ejpam-5015	348	23	.	.	PUNCT
ejpam-5015	349	1	as	as	ADP
ejpam-5015	349	2	’	'	PUNCT
ejpam-5015	349	3	m	m	NOUN
ejpam-5015	349	4	’	'	PUNCT
ejpam-5015	349	5	increases	increase	NOUN
ejpam-5015	349	6	from	from	ADP
ejpam-5015	349	7	3	3	NUM
ejpam-5015	349	8	to	to	ADP
ejpam-5015	349	9	7	7	NUM
ejpam-5015	349	10	,	,	PUNCT
ejpam-5015	349	11	the	the	DET
ejpam-5015	349	12	efficiencies	efficiency	NOUN
ejpam-5015	349	13	also	also	ADV
ejpam-5015	349	14	increase	increase	VERB
ejpam-5015	349	15	.	.	PUNCT
ejpam-5015	350	1	this	this	PRON
ejpam-5015	350	2	shows	show	VERB
ejpam-5015	350	3	that	that	SCONJ
ejpam-5015	350	4	the	the	DET
ejpam-5015	350	5	advantage	advantage	NOUN
ejpam-5015	350	6	of	of	ADP
ejpam-5015	350	7	the	the	DET
ejpam-5015	350	8	bayesian	bayesian	NOUN
ejpam-5015	350	9	mrss	mrss	NOUN
ejpam-5015	350	10	method	method	NOUN
ejpam-5015	350	11	over	over	ADP
ejpam-5015	350	12	the	the	DET
ejpam-5015	350	13	frequentist	frequentist	NOUN
ejpam-5015	350	14	mrss	mrss	NOUN
ejpam-5015	350	15	method	method	NOUN
ejpam-5015	350	16	becomes	become	VERB
ejpam-5015	350	17	more	more	ADV
ejpam-5015	350	18	pronounced	pronounced	ADJ
ejpam-5015	350	19	as	as	ADP
ejpam-5015	350	20	’	'	PUNCT
ejpam-5015	350	21	m	m	NOUN
ejpam-5015	350	22	’	'	PUNCT
ejpam-5015	350	23	increases	increase	NOUN
ejpam-5015	350	24	.	.	PUNCT
ejpam-5015	351	1	in	in	ADP
ejpam-5015	351	2	summary	summary	NOUN
ejpam-5015	351	3	from	from	ADP
ejpam-5015	351	4	table	table	NOUN
ejpam-5015	351	5	3	3	NUM
ejpam-5015	351	6	,	,	PUNCT
ejpam-5015	351	7	we	we	PRON
ejpam-5015	351	8	conclude	conclude	VERB
ejpam-5015	351	9	that	that	SCONJ
ejpam-5015	351	10	in	in	ADP
ejpam-5015	351	11	this	this	DET
ejpam-5015	351	12	particular	particular	ADJ
ejpam-5015	351	13	application	application	NOUN
ejpam-5015	351	14	,	,	PUNCT
ejpam-5015	351	15	the	the	DET
ejpam-5015	351	16	bayesian	bayesian	NOUN
ejpam-5015	351	17	mrss	mrss	NOUN
ejpam-5015	351	18	method	method	NOUN
ejpam-5015	351	19	provides	provide	VERB
ejpam-5015	351	20	more	more	ADV
ejpam-5015	351	21	efficient	efficient	ADJ
ejpam-5015	351	22	(	(	PUNCT
ejpam-5015	351	23	lower	lower	X
ejpam-5015	351	24	mse	mse	NOUN
ejpam-5015	351	25	)	)	PUNCT
ejpam-5015	351	26	estimates	estimate	NOUN
ejpam-5015	351	27	of	of	ADP
ejpam-5015	351	28	the	the	DET
ejpam-5015	351	29	regression	regression	NOUN
ejpam-5015	351	30	parameters	parameter	NOUN
ejpam-5015	351	31	than	than	ADP
ejpam-5015	351	32	the	the	DET
ejpam-5015	351	33	frequentist	frequentist	NOUN
ejpam-5015	351	34	mrss	mrss	NOUN
ejpam-5015	351	35	method	method	NOUN
ejpam-5015	351	36	,	,	PUNCT
ejpam-5015	351	37	and	and	CCONJ
ejpam-5015	351	38	this	this	DET
ejpam-5015	351	39	advantage	advantage	NOUN
ejpam-5015	351	40	increases	increase	NOUN
ejpam-5015	351	41	as	as	ADP
ejpam-5015	351	42	the	the	DET
ejpam-5015	351	43	size	size	NOUN
ejpam-5015	351	44	of	of	ADP
ejpam-5015	351	45	the	the	DET
ejpam-5015	351	46	mrss	mrss	ADJ
ejpam-5015	351	47	cycle	cycle	NOUN
ejpam-5015	351	48	(	(	PUNCT
ejpam-5015	351	49	’	'	PUNCT
ejpam-5015	351	50	m	m	NUM
ejpam-5015	351	51	’	'	PUNCT
ejpam-5015	351	52	)	)	PUNCT
ejpam-5015	351	53	increases	increase	NOUN
ejpam-5015	351	54	.	.	PUNCT
ejpam-5015	352	1	i.	i.	PROPN
ejpam-5015	352	2	nawajah	nawajah	PROPN
ejpam-5015	352	3	,	,	PUNCT
ejpam-5015	352	4	h.	h.	PROPN
ejpam-5015	352	5	kanj	kanj	PROPN
ejpam-5015	352	6	,	,	PUNCT
ejpam-5015	352	7	y.	y.	PROPN
ejpam-5015	352	8	kotb	kotb	PROPN
ejpam-5015	352	9	,	,	PUNCT
ejpam-5015	352	10	j.	j.	PROPN
ejpam-5015	352	11	hoxha	hoxha	PROPN
ejpam-5015	352	12	,	,	PUNCT
ejpam-5015	352	13	m.	m.	PROPN
ejpam-5015	352	14	alakkoumi	alakkoumi	PROPN
ejpam-5015	352	15	,	,	PUNCT
ejpam-5015	352	16	k.	k.	PROPN
ejpam-5015	352	17	jebreen	jebreen	PROPN
ejpam-5015	352	18	/	/	SYM
ejpam-5015	352	19	eur	eur	PROPN
ejpam-5015	352	20	.	.	PUNCT
ejpam-5015	353	1	j.	j.	PROPN
ejpam-5015	353	2	pure	pure	PROPN
ejpam-5015	353	3	appl	appl	PROPN
ejpam-5015	353	4	.	.	PROPN
ejpam-5015	353	5	math	math	PROPN
ejpam-5015	353	6	,	,	PUNCT
ejpam-5015	353	7	17	17	NUM
ejpam-5015	353	8	(	(	PUNCT
ejpam-5015	353	9	1	1	NUM
ejpam-5015	353	10	)	)	PUNCT
ejpam-5015	353	11	(	(	PUNCT
ejpam-5015	353	12	2024	2024	NUM
ejpam-5015	353	13	)	)	PUNCT
ejpam-5015	353	14	,	,	PUNCT
ejpam-5015	353	15	180	180	NUM
ejpam-5015	353	16	-	-	SYM
ejpam-5015	353	17	200	200	NUM
ejpam-5015	353	18	197	197	NUM
ejpam-5015	353	19	table	table	NOUN
ejpam-5015	353	20	3	3	NUM
ejpam-5015	353	21	:	:	PUNCT
ejpam-5015	353	22	the	the	DET
ejpam-5015	353	23	efficiency	efficiency	NOUN
ejpam-5015	353	24	of	of	ADP
ejpam-5015	353	25	bayesian	bayesian	NOUN
ejpam-5015	353	26	regression	regression	NOUN
ejpam-5015	353	27	parameters	parameter	NOUN
ejpam-5015	353	28	using	use	VERB
ejpam-5015	353	29	mrss	mrss	NOUN
ejpam-5015	353	30	concerning	concern	VERB
ejpam-5015	353	31	mrss	mrss	NOUN
ejpam-5015	353	32	with	with	ADP
ejpam-5015	353	33	different	different	ADJ
ejpam-5015	353	34	m.	m.	NOUN
ejpam-5015	353	35	efficiency	efficiency	NOUN
ejpam-5015	353	36	(	(	PUNCT
ejpam-5015	353	37	θ̂1	θ̂1	X
ejpam-5015	353	38	,	,	PUNCT
ejpam-5015	353	39	θ̂2)=	θ̂2)=	NOUN
ejpam-5015	353	40	mse(θ̂1)/mse(θ̂2	mse(θ̂1)/mse(θ̂2	NOUN
ejpam-5015	353	41	)	)	PUNCT
ejpam-5015	353	42	efficiency	efficiency	NOUN
ejpam-5015	353	43	(	(	PUNCT
ejpam-5015	353	44	β̂0	β̂0	X
ejpam-5015	353	45	,	,	PUNCT
ejpam-5015	353	46	ˆβ0	ˆβ0	PROPN
ejpam-5015	353	47	m	m	NOUN
ejpam-5015	353	48	)	)	PUNCT
ejpam-5015	353	49	efficiency	efficiency	NOUN
ejpam-5015	353	50	(	(	PUNCT
ejpam-5015	353	51	β̂1	β̂1	X
ejpam-5015	353	52	,	,	PUNCT
ejpam-5015	353	53	ˆβ1	ˆβ1	PROPN
ejpam-5015	353	54	m	m	NOUN
ejpam-5015	353	55	)	)	PUNCT
ejpam-5015	353	56	efficiency	efficiency	NOUN
ejpam-5015	353	57	(	(	PUNCT
ejpam-5015	353	58	σ̂2	σ̂2	PROPN
ejpam-5015	353	59	,	,	PUNCT
ejpam-5015	353	60	σ̂2	σ̂2	PROPN
ejpam-5015	353	61	m	m	PROPN
ejpam-5015	353	62	)	)	PUNCT
ejpam-5015	354	1	m=3	m=3	PROPN
ejpam-5015	354	2	1.29	1.29	NUM
ejpam-5015	354	3	1.76	1.76	NUM
ejpam-5015	354	4	1.01	1.01	NUM
ejpam-5015	354	5	m=5	m=5	SYM
ejpam-5015	354	6	1.78	1.78	NUM
ejpam-5015	354	7	2.88	2.88	NUM
ejpam-5015	354	8	1.98	1.98	NUM
ejpam-5015	354	9	m=7	m=7	NOUN
ejpam-5015	354	10	2.21	2.21	NUM
ejpam-5015	354	11	3.07	3.07	NUM
ejpam-5015	354	12	2.34	2.34	NUM
ejpam-5015	354	13	7	7	NUM
ejpam-5015	354	14	.	.	PUNCT
ejpam-5015	355	1	discussion	discussion	NOUN
ejpam-5015	355	2	in	in	ADP
ejpam-5015	355	3	the	the	DET
ejpam-5015	355	4	present	present	ADJ
ejpam-5015	355	5	study	study	NOUN
ejpam-5015	356	1	,	,	PUNCT
ejpam-5015	356	2	we	we	PRON
ejpam-5015	356	3	developed	develop	VERB
ejpam-5015	356	4	a	a	DET
ejpam-5015	356	5	bayesian	bayesian	NOUN
ejpam-5015	356	6	model	model	NOUN
ejpam-5015	356	7	for	for	ADP
ejpam-5015	356	8	estimating	estimate	VERB
ejpam-5015	356	9	the	the	DET
ejpam-5015	356	10	parameters	parameter	NOUN
ejpam-5015	356	11	of	of	ADP
ejpam-5015	356	12	a	a	DET
ejpam-5015	356	13	simple	simple	ADJ
ejpam-5015	356	14	linear	linear	NOUN
ejpam-5015	356	15	regression	regression	NOUN
ejpam-5015	356	16	model	model	NOUN
ejpam-5015	356	17	through	through	ADP
ejpam-5015	356	18	median	median	NOUN
ejpam-5015	356	19	ranked	rank	VERB
ejpam-5015	356	20	set	set	ADJ
ejpam-5015	356	21	sampling	sampling	NOUN
ejpam-5015	356	22	(	(	PUNCT
ejpam-5015	356	23	mrss	mrss	NOUN
ejpam-5015	356	24	)	)	PUNCT
ejpam-5015	356	25	.	.	PUNCT
ejpam-5015	357	1	our	our	PRON
ejpam-5015	357	2	results	result	NOUN
ejpam-5015	357	3	demonstrate	demonstrate	VERB
ejpam-5015	357	4	that	that	SCONJ
ejpam-5015	357	5	bayesian	bayesian	NOUN
ejpam-5015	357	6	estimators	estimator	NOUN
ejpam-5015	357	7	derived	derive	VERB
ejpam-5015	357	8	from	from	ADP
ejpam-5015	357	9	this	this	DET
ejpam-5015	357	10	approach	approach	NOUN
ejpam-5015	357	11	are	be	AUX
ejpam-5015	357	12	more	more	ADV
ejpam-5015	357	13	efficient	efficient	ADJ
ejpam-5015	357	14	than	than	ADP
ejpam-5015	357	15	those	those	PRON
ejpam-5015	357	16	from	from	ADP
ejpam-5015	357	17	the	the	DET
ejpam-5015	357	18	frequentist	frequentist	NOUN
ejpam-5015	357	19	mrss	mrss	PROPN
ejpam-5015	357	20	method	method	NOUN
ejpam-5015	357	21	detailed	detail	VERB
ejpam-5015	357	22	in	in	ADP
ejpam-5015	357	23	[	[	X
ejpam-5015	357	24	6	6	NUM
ejpam-5015	357	25	]	]	PUNCT
ejpam-5015	357	26	.	.	PUNCT
ejpam-5015	358	1	this	this	DET
ejpam-5015	358	2	study	study	NOUN
ejpam-5015	358	3	marks	mark	VERB
ejpam-5015	358	4	the	the	DET
ejpam-5015	358	5	first	first	ADJ
ejpam-5015	358	6	exploration	exploration	NOUN
ejpam-5015	358	7	of	of	ADP
ejpam-5015	358	8	a	a	DET
ejpam-5015	358	9	bayesian	bayesian	NOUN
ejpam-5015	358	10	model	model	NOUN
ejpam-5015	358	11	for	for	ADP
ejpam-5015	358	12	estimating	estimate	VERB
ejpam-5015	358	13	coefficients	coefficient	NOUN
ejpam-5015	358	14	of	of	ADP
ejpam-5015	358	15	a	a	DET
ejpam-5015	358	16	simple	simple	ADJ
ejpam-5015	358	17	linear	linear	ADJ
ejpam-5015	358	18	regression	regression	NOUN
ejpam-5015	358	19	model	model	NOUN
ejpam-5015	358	20	via	via	ADP
ejpam-5015	358	21	mrss	mrss	NOUN
ejpam-5015	358	22	.	.	PUNCT
ejpam-5015	359	1	the	the	DET
ejpam-5015	359	2	primary	primary	ADJ
ejpam-5015	359	3	goal	goal	NOUN
ejpam-5015	359	4	was	be	AUX
ejpam-5015	359	5	to	to	PART
ejpam-5015	359	6	investigate	investigate	VERB
ejpam-5015	359	7	the	the	DET
ejpam-5015	359	8	potential	potential	NOUN
ejpam-5015	359	9	of	of	ADP
ejpam-5015	359	10	bayesian	bayesian	NOUN
ejpam-5015	359	11	statistical	statistical	ADJ
ejpam-5015	359	12	analysis	analysis	NOUN
ejpam-5015	359	13	for	for	ADP
ejpam-5015	359	14	a	a	DET
ejpam-5015	359	15	straightforward	straightforward	ADJ
ejpam-5015	359	16	and	and	CCONJ
ejpam-5015	359	17	efficient	efficient	ADJ
ejpam-5015	359	18	estimation	estimation	NOUN
ejpam-5015	359	19	of	of	ADP
ejpam-5015	359	20	the	the	DET
ejpam-5015	359	21	simple	simple	ADJ
ejpam-5015	359	22	linear	linear	ADJ
ejpam-5015	359	23	regression	regression	NOUN
ejpam-5015	359	24	model	model	NOUN
ejpam-5015	359	25	via	via	ADP
ejpam-5015	359	26	mrss	mrss	NOUN
ejpam-5015	359	27	,	,	PUNCT
ejpam-5015	359	28	especially	especially	ADV
ejpam-5015	359	29	when	when	SCONJ
ejpam-5015	359	30	compared	compare	VERB
ejpam-5015	359	31	with	with	ADP
ejpam-5015	359	32	the	the	DET
ejpam-5015	359	33	traditional	traditional	ADJ
ejpam-5015	359	34	frequentist	frequentist	NOUN
ejpam-5015	359	35	mrss	mrss	NOUN
ejpam-5015	359	36	approach	approach	NOUN
ejpam-5015	359	37	.	.	PUNCT
ejpam-5015	360	1	the	the	DET
ejpam-5015	360	2	paper	paper	NOUN
ejpam-5015	360	3	aligns	align	VERB
ejpam-5015	360	4	with	with	ADP
ejpam-5015	360	5	the	the	DET
ejpam-5015	360	6	results	result	NOUN
ejpam-5015	360	7	of	of	ADP
ejpam-5015	360	8	alodat	alodat	NOUN
ejpam-5015	360	9	et	et	PROPN
ejpam-5015	360	10	al	al	PROPN
ejpam-5015	360	11	.	.	PROPN
ejpam-5015	360	12	,	,	PUNCT
ejpam-5015	361	1	[	[	X
ejpam-5015	361	2	6	6	NUM
ejpam-5015	361	3	]	]	PUNCT
ejpam-5015	361	4	and	and	CCONJ
ejpam-5015	361	5	alsaleh	alsaleh	NOUN
ejpam-5015	361	6	and	and	CCONJ
ejpam-5015	361	7	alsharafat	alsharafat	NOUN
ejpam-5015	362	1	[	[	X
ejpam-5015	362	2	3	3	NUM
ejpam-5015	362	3	]	]	PUNCT
ejpam-5015	362	4	,	,	PUNCT
ejpam-5015	362	5	emphasizing	emphasize	VERB
ejpam-5015	362	6	that	that	SCONJ
ejpam-5015	362	7	bayesian	bayesian	NOUN
ejpam-5015	362	8	estimators	estimator	NOUN
ejpam-5015	362	9	prove	prove	VERB
ejpam-5015	362	10	to	to	PART
ejpam-5015	362	11	be	be	AUX
ejpam-5015	362	12	more	more	ADV
ejpam-5015	362	13	efficient	efficient	ADJ
ejpam-5015	362	14	than	than	ADP
ejpam-5015	362	15	those	those	PRON
ejpam-5015	362	16	derived	derive	VERB
ejpam-5015	362	17	from	from	ADP
ejpam-5015	362	18	simple	simple	ADJ
ejpam-5015	362	19	random	random	ADJ
ejpam-5015	362	20	sampling	sampling	NOUN
ejpam-5015	362	21	.	.	PUNCT
ejpam-5015	363	1	we	we	PRON
ejpam-5015	363	2	also	also	ADV
ejpam-5015	363	3	noticed	notice	VERB
ejpam-5015	363	4	a	a	DET
ejpam-5015	363	5	decrease	decrease	NOUN
ejpam-5015	363	6	in	in	ADP
ejpam-5015	363	7	the	the	DET
ejpam-5015	363	8	standard	standard	ADJ
ejpam-5015	363	9	error	error	NOUN
ejpam-5015	363	10	(	(	PUNCT
ejpam-5015	363	11	se	se	X
ejpam-5015	363	12	)	)	PUNCT
ejpam-5015	363	13	of	of	ADP
ejpam-5015	363	14	bayesian	bayesian	NOUN
ejpam-5015	363	15	estimates	estimate	NOUN
ejpam-5015	363	16	based	base	VERB
ejpam-5015	363	17	on	on	ADP
ejpam-5015	363	18	mrss	mrss	NOUN
ejpam-5015	363	19	as	as	ADP
ejpam-5015	363	20	the	the	DET
ejpam-5015	363	21	sample	sample	NOUN
ejpam-5015	363	22	size	size	NOUN
ejpam-5015	363	23	m	m	NOUN
ejpam-5015	363	24	increases	increase	NOUN
ejpam-5015	363	25	,	,	PUNCT
ejpam-5015	363	26	reinforcing	reinforce	VERB
ejpam-5015	363	27	findings	finding	NOUN
ejpam-5015	363	28	by	by	ADP
ejpam-5015	363	29	de	de	X
ejpam-5015	363	30	iorio	iorio	PROPN
ejpam-5015	363	31	et	et	PROPN
ejpam-5015	363	32	al	al	PROPN
ejpam-5015	363	33	.	.	PUNCT
ejpam-5015	364	1	[	[	X
ejpam-5015	364	2	10	10	NUM
ejpam-5015	364	3	]	]	PUNCT
ejpam-5015	364	4	and	and	CCONJ
ejpam-5015	364	5	helo	helo	PROPN
ejpam-5015	364	6	et	et	PROPN
ejpam-5015	364	7	al	al	PROPN
ejpam-5015	364	8	.	.	PROPN
ejpam-5015	364	9	,	,	PUNCT
ejpam-5015	365	1	[	[	X
ejpam-5015	365	2	14	14	NUM
ejpam-5015	365	3	]	]	X
ejpam-5015	365	4	,	,	PUNCT
ejpam-5015	365	5	both	both	PRON
ejpam-5015	365	6	of	of	ADP
ejpam-5015	365	7	whom	whom	PRON
ejpam-5015	365	8	demonstrated	demonstrate	VERB
ejpam-5015	365	9	a	a	DET
ejpam-5015	365	10	similar	similar	ADJ
ejpam-5015	365	11	trend	trend	NOUN
ejpam-5015	365	12	in	in	ADP
ejpam-5015	365	13	ranked	rank	VERB
ejpam-5015	365	14	set	set	ADJ
ejpam-5015	365	15	sampling	sampling	NOUN
ejpam-5015	365	16	and	and	CCONJ
ejpam-5015	365	17	the	the	DET
ejpam-5015	365	18	bayesian	bayesian	NOUN
ejpam-5015	365	19	estimation	estimation	NOUN
ejpam-5015	365	20	of	of	ADP
ejpam-5015	365	21	weibull	weibull	PROPN
ejpam-5015	365	22	parameters	parameter	NOUN
ejpam-5015	365	23	respectively	respectively	ADV
ejpam-5015	365	24	.	.	PUNCT
ejpam-5015	366	1	this	this	DET
ejpam-5015	366	2	study	study	NOUN
ejpam-5015	366	3	assumes	assume	VERB
ejpam-5015	366	4	a	a	DET
ejpam-5015	366	5	symmetric	symmetric	ADJ
ejpam-5015	366	6	distribution	distribution	NOUN
ejpam-5015	366	7	for	for	ADP
ejpam-5015	366	8	random	random	ADJ
ejpam-5015	366	9	errors	error	NOUN
ejpam-5015	366	10	.	.	PUNCT
ejpam-5015	367	1	when	when	SCONJ
ejpam-5015	367	2	compared	compare	VERB
ejpam-5015	367	3	to	to	ADP
ejpam-5015	367	4	the	the	DET
ejpam-5015	367	5	frequentist	frequentist	NOUN
ejpam-5015	367	6	model	model	NOUN
ejpam-5015	367	7	in	in	ADP
ejpam-5015	367	8	alodat	alodat	PROPN
ejpam-5015	367	9	et	et	PROPN
ejpam-5015	367	10	al	al	PROPN
ejpam-5015	367	11	.	.	PUNCT
ejpam-5015	368	1	[	[	X
ejpam-5015	368	2	6	6	NUM
ejpam-5015	368	3	]	]	PUNCT
ejpam-5015	368	4	,	,	PUNCT
ejpam-5015	368	5	our	our	PRON
ejpam-5015	368	6	bayesian	bayesian	NOUN
ejpam-5015	368	7	model	model	NOUN
ejpam-5015	368	8	’s	’s	PART
ejpam-5015	368	9	estimates	estimate	NOUN
ejpam-5015	368	10	exhibit	exhibit	VERB
ejpam-5015	368	11	a	a	DET
ejpam-5015	368	12	noticeable	noticeable	ADJ
ejpam-5015	368	13	advantage	advantage	NOUN
ejpam-5015	368	14	:	:	PUNCT
ejpam-5015	368	15	they	they	PRON
ejpam-5015	368	16	are	be	AUX
ejpam-5015	368	17	simpler	simple	ADJ
ejpam-5015	368	18	both	both	CCONJ
ejpam-5015	368	19	in	in	ADP
ejpam-5015	368	20	mathematical	mathematical	ADJ
ejpam-5015	368	21	formulation	formulation	NOUN
ejpam-5015	368	22	and	and	CCONJ
ejpam-5015	368	23	calculation	calculation	NOUN
ejpam-5015	368	24	.	.	PUNCT
ejpam-5015	369	1	this	this	DET
ejpam-5015	369	2	ease	ease	NOUN
ejpam-5015	369	3	and	and	CCONJ
ejpam-5015	369	4	efficiency	efficiency	NOUN
ejpam-5015	369	5	in	in	ADP
ejpam-5015	369	6	handling	handle	VERB
ejpam-5015	369	7	underline	underline	ADJ
ejpam-5015	369	8	the	the	DET
ejpam-5015	369	9	potential	potential	ADJ
ejpam-5015	369	10	advantages	advantage	NOUN
ejpam-5015	369	11	of	of	ADP
ejpam-5015	369	12	bayesian	bayesian	NOUN
ejpam-5015	369	13	estimation	estimation	NOUN
ejpam-5015	369	14	when	when	SCONJ
ejpam-5015	369	15	dealing	deal	VERB
ejpam-5015	369	16	with	with	ADP
ejpam-5015	369	17	mrss	mrss	NOUN
ejpam-5015	369	18	in	in	ADP
ejpam-5015	369	19	simple	simple	ADJ
ejpam-5015	369	20	linear	linear	ADJ
ejpam-5015	369	21	regression	regression	NOUN
ejpam-5015	369	22	models	model	NOUN
ejpam-5015	369	23	.	.	PUNCT
ejpam-5015	370	1	the	the	DET
ejpam-5015	370	2	findings	finding	NOUN
ejpam-5015	370	3	of	of	ADP
ejpam-5015	370	4	this	this	DET
ejpam-5015	370	5	study	study	NOUN
ejpam-5015	370	6	bear	bear	VERB
ejpam-5015	370	7	significant	significant	ADJ
ejpam-5015	370	8	implications	implication	NOUN
ejpam-5015	370	9	for	for	ADP
ejpam-5015	370	10	statistical	statistical	ADJ
ejpam-5015	370	11	modeling	modeling	NOUN
ejpam-5015	370	12	and	and	CCONJ
ejpam-5015	370	13	inferential	inferential	ADJ
ejpam-5015	370	14	analysis	analysis	NOUN
ejpam-5015	370	15	.	.	PUNCT
ejpam-5015	371	1	they	they	PRON
ejpam-5015	371	2	establish	establish	VERB
ejpam-5015	371	3	the	the	DET
ejpam-5015	371	4	value	value	NOUN
ejpam-5015	371	5	of	of	ADP
ejpam-5015	371	6	bayesian	bayesian	NOUN
ejpam-5015	371	7	approaches	approach	NOUN
ejpam-5015	371	8	in	in	ADP
ejpam-5015	371	9	providing	provide	VERB
ejpam-5015	371	10	robust	robust	ADJ
ejpam-5015	371	11	and	and	CCONJ
ejpam-5015	371	12	efficient	efficient	ADJ
ejpam-5015	371	13	estimates	estimate	NOUN
ejpam-5015	371	14	in	in	ADP
ejpam-5015	371	15	the	the	DET
ejpam-5015	371	16	context	context	NOUN
ejpam-5015	371	17	of	of	ADP
ejpam-5015	371	18	a	a	DET
ejpam-5015	371	19	simple	simple	ADJ
ejpam-5015	371	20	linear	linear	NOUN
ejpam-5015	371	21	regression	regression	NOUN
ejpam-5015	371	22	model	model	NOUN
ejpam-5015	371	23	,	,	PUNCT
ejpam-5015	371	24	using	use	VERB
ejpam-5015	371	25	median	median	NOUN
ejpam-5015	371	26	ranked	rank	VERB
ejpam-5015	371	27	set	set	ADJ
ejpam-5015	371	28	sampling	sampling	NOUN
ejpam-5015	371	29	(	(	PUNCT
ejpam-5015	371	30	mrss	mrss	ADJ
ejpam-5015	371	31	)	)	PUNCT
ejpam-5015	371	32	.	.	PUNCT
ejpam-5015	372	1	one	one	NUM
ejpam-5015	372	2	key	key	ADJ
ejpam-5015	372	3	implication	implication	NOUN
ejpam-5015	372	4	of	of	ADP
ejpam-5015	372	5	the	the	DET
ejpam-5015	372	6	study	study	NOUN
ejpam-5015	372	7	is	be	AUX
ejpam-5015	372	8	that	that	SCONJ
ejpam-5015	372	9	it	it	PRON
ejpam-5015	372	10	demonstrates	demonstrate	VERB
ejpam-5015	372	11	the	the	DET
ejpam-5015	372	12	efficiency	efficiency	NOUN
ejpam-5015	372	13	of	of	ADP
ejpam-5015	372	14	bayesian	bayesian	NOUN
ejpam-5015	372	15	estimators	estimator	NOUN
ejpam-5015	372	16	in	in	ADP
ejpam-5015	372	17	comparison	comparison	NOUN
ejpam-5015	372	18	to	to	ADP
ejpam-5015	372	19	their	their	PRON
ejpam-5015	372	20	frequentist	frequentist	NOUN
ejpam-5015	372	21	mrss	mrss	PROPN
ejpam-5015	372	22	counterparts	counterpart	NOUN
ejpam-5015	372	23	.	.	PUNCT
ejpam-5015	373	1	this	this	PRON
ejpam-5015	373	2	points	point	VERB
ejpam-5015	373	3	to	to	ADP
ejpam-5015	373	4	the	the	DET
ejpam-5015	373	5	potential	potential	NOUN
ejpam-5015	373	6	of	of	ADP
ejpam-5015	373	7	bayesian	bayesian	NOUN
ejpam-5015	373	8	approaches	approach	NOUN
ejpam-5015	373	9	to	to	PART
ejpam-5015	373	10	be	be	AUX
ejpam-5015	373	11	more	more	ADV
ejpam-5015	373	12	widely	widely	ADV
ejpam-5015	373	13	applied	apply	VERB
ejpam-5015	373	14	in	in	ADP
ejpam-5015	373	15	statistical	statistical	ADJ
ejpam-5015	373	16	modeling	modeling	NOUN
ejpam-5015	373	17	and	and	CCONJ
ejpam-5015	373	18	inferential	inferential	ADJ
ejpam-5015	373	19	analysis	analysis	NOUN
ejpam-5015	373	20	,	,	PUNCT
ejpam-5015	373	21	providing	provide	VERB
ejpam-5015	373	22	researchers	researcher	NOUN
ejpam-5015	373	23	with	with	ADP
ejpam-5015	373	24	more	more	ADV
ejpam-5015	373	25	robust	robust	ADJ
ejpam-5015	373	26	and	and	CCONJ
ejpam-5015	373	27	precise	precise	ADJ
ejpam-5015	373	28	tools	tool	NOUN
ejpam-5015	373	29	to	to	PART
ejpam-5015	373	30	analyze	analyze	VERB
ejpam-5015	373	31	their	their	PRON
ejpam-5015	373	32	data	datum	NOUN
ejpam-5015	373	33	.	.	PUNCT
ejpam-5015	374	1	in	in	ADP
ejpam-5015	374	2	addition	addition	NOUN
ejpam-5015	374	3	,	,	PUNCT
ejpam-5015	374	4	this	this	DET
ejpam-5015	374	5	study	study	NOUN
ejpam-5015	374	6	suggests	suggest	VERB
ejpam-5015	374	7	that	that	SCONJ
ejpam-5015	374	8	as	as	ADP
ejpam-5015	374	9	the	the	DET
ejpam-5015	374	10	sample	sample	NOUN
ejpam-5015	374	11	size	size	NOUN
ejpam-5015	374	12	(	(	PUNCT
ejpam-5015	374	13	m	m	NOUN
ejpam-5015	374	14	)	)	PUNCT
ejpam-5015	374	15	increases	increase	NOUN
ejpam-5015	374	16	,	,	PUNCT
ejpam-5015	374	17	the	the	DET
ejpam-5015	374	18	standard	standard	ADJ
ejpam-5015	374	19	error	error	NOUN
ejpam-5015	374	20	(	(	PUNCT
ejpam-5015	374	21	se	se	X
ejpam-5015	374	22	)	)	PUNCT
ejpam-5015	374	23	of	of	ADP
ejpam-5015	374	24	bayesian	bayesian	NOUN
ejpam-5015	374	25	estimates	estimate	NOUN
ejpam-5015	374	26	based	base	VERB
ejpam-5015	374	27	on	on	ADP
ejpam-5015	374	28	mrss	mrss	ADJ
ejpam-5015	374	29	decreases	decrease	NOUN
ejpam-5015	374	30	.	.	PUNCT
ejpam-5015	375	1	this	this	DET
ejpam-5015	375	2	trend	trend	NOUN
ejpam-5015	375	3	could	could	AUX
ejpam-5015	375	4	inform	inform	VERB
ejpam-5015	375	5	future	future	ADJ
ejpam-5015	375	6	data	datum	NOUN
ejpam-5015	375	7	collection	collection	NOUN
ejpam-5015	375	8	strategies	strategy	NOUN
ejpam-5015	375	9	,	,	PUNCT
ejpam-5015	375	10	by	by	ADP
ejpam-5015	375	11	encouraging	encourage	VERB
ejpam-5015	375	12	the	the	DET
ejpam-5015	375	13	collection	collection	NOUN
ejpam-5015	375	14	of	of	ADP
ejpam-5015	375	15	larger	large	ADJ
ejpam-5015	375	16	sample	sample	NOUN
ejpam-5015	375	17	sizes	size	NOUN
ejpam-5015	375	18	to	to	PART
ejpam-5015	375	19	improve	improve	VERB
ejpam-5015	375	20	the	the	DET
ejpam-5015	375	21	precision	precision	NOUN
ejpam-5015	375	22	of	of	ADP
ejpam-5015	375	23	bayesian	bayesian	NOUN
ejpam-5015	375	24	estimates	estimate	NOUN
ejpam-5015	375	25	.	.	PUNCT
ejpam-5015	376	1	references	reference	NOUN
ejpam-5015	376	2	198	198	NUM
ejpam-5015	376	3	8	8	NUM
ejpam-5015	376	4	.	.	PUNCT
ejpam-5015	377	1	conclusion	conclusion	NOUN
ejpam-5015	377	2	related	relate	VERB
ejpam-5015	377	3	to	to	ADP
ejpam-5015	377	4	our	our	PRON
ejpam-5015	377	5	knowledge	knowledge	NOUN
ejpam-5015	377	6	,	,	PUNCT
ejpam-5015	377	7	in	in	ADP
ejpam-5015	377	8	the	the	DET
ejpam-5015	377	9	literature	literature	NOUN
ejpam-5015	377	10	,	,	PUNCT
ejpam-5015	377	11	there	there	PRON
ejpam-5015	377	12	are	be	VERB
ejpam-5015	377	13	no	no	DET
ejpam-5015	377	14	previous	previous	ADJ
ejpam-5015	377	15	studies	study	NOUN
ejpam-5015	377	16	on	on	ADP
ejpam-5015	377	17	bayesian	bayesian	NOUN
ejpam-5015	377	18	estimating	estimating	NOUN
ejpam-5015	377	19	of	of	ADP
ejpam-5015	377	20	the	the	DET
ejpam-5015	377	21	linear	linear	ADJ
ejpam-5015	377	22	regression	regression	NOUN
ejpam-5015	377	23	parameters	parameter	NOUN
ejpam-5015	377	24	using	use	VERB
ejpam-5015	377	25	mrss	mrss	NOUN
ejpam-5015	377	26	.	.	PUNCT
ejpam-5015	378	1	thus	thus	ADV
ejpam-5015	378	2	,	,	PUNCT
ejpam-5015	378	3	the	the	DET
ejpam-5015	378	4	emphasis	emphasis	NOUN
ejpam-5015	378	5	of	of	ADP
ejpam-5015	378	6	this	this	DET
ejpam-5015	378	7	paper	paper	NOUN
ejpam-5015	378	8	is	be	AUX
ejpam-5015	378	9	to	to	PART
ejpam-5015	378	10	estimate	estimate	VERB
ejpam-5015	378	11	the	the	DET
ejpam-5015	378	12	simple	simple	ADJ
ejpam-5015	378	13	linear	linear	ADJ
ejpam-5015	378	14	regression	regression	NOUN
ejpam-5015	378	15	parameters	parameter	NOUN
ejpam-5015	378	16	via	via	ADP
ejpam-5015	378	17	mrss	mrss	NOUN
ejpam-5015	378	18	in	in	ADP
ejpam-5015	378	19	bayesian	bayesian	NOUN
ejpam-5015	378	20	approach	approach	NOUN
ejpam-5015	378	21	.	.	PUNCT
ejpam-5015	379	1	this	this	DET
ejpam-5015	379	2	study	study	NOUN
ejpam-5015	379	3	investigated	investigate	VERB
ejpam-5015	379	4	the	the	DET
ejpam-5015	379	5	bayesian	bayesian	NOUN
ejpam-5015	379	6	estimation	estimation	NOUN
ejpam-5015	379	7	of	of	ADP
ejpam-5015	379	8	parameters	parameter	NOUN
ejpam-5015	379	9	in	in	ADP
ejpam-5015	379	10	a	a	DET
ejpam-5015	379	11	simple	simple	ADJ
ejpam-5015	379	12	linear	linear	NOUN
ejpam-5015	379	13	regression	regression	NOUN
ejpam-5015	379	14	model	model	NOUN
ejpam-5015	379	15	,	,	PUNCT
ejpam-5015	379	16	employing	employ	VERB
ejpam-5015	379	17	mrss	mrss	NOUN
ejpam-5015	379	18	.	.	PUNCT
ejpam-5015	380	1	using	use	VERB
ejpam-5015	380	2	markov	markov	PROPN
ejpam-5015	380	3	chain	chain	NOUN
ejpam-5015	380	4	monte	monte	PROPN
ejpam-5015	380	5	carlo	carlo	PROPN
ejpam-5015	380	6	(	(	PUNCT
ejpam-5015	380	7	mcmc	mcmc	PROPN
ejpam-5015	380	8	)	)	PUNCT
ejpam-5015	380	9	numerical	numerical	ADJ
ejpam-5015	380	10	simulations	simulation	NOUN
ejpam-5015	380	11	,	,	PUNCT
ejpam-5015	380	12	bayesian	bayesian	NOUN
ejpam-5015	380	13	estimates	estimate	NOUN
ejpam-5015	380	14	were	be	AUX
ejpam-5015	380	15	obtained	obtain	VERB
ejpam-5015	380	16	and	and	CCONJ
ejpam-5015	380	17	analyzed	analyze	VERB
ejpam-5015	380	18	.	.	PUNCT
ejpam-5015	381	1	the	the	DET
ejpam-5015	381	2	findings	finding	NOUN
ejpam-5015	381	3	underscored	underscore	VERB
ejpam-5015	381	4	the	the	DET
ejpam-5015	381	5	efficiency	efficiency	NOUN
ejpam-5015	381	6	of	of	ADP
ejpam-5015	381	7	bayesian	bayesian	NOUN
ejpam-5015	381	8	estimators	estimator	NOUN
ejpam-5015	381	9	obtained	obtain	VERB
ejpam-5015	381	10	through	through	ADP
ejpam-5015	381	11	mrss	mrss	NOUN
ejpam-5015	381	12	,	,	PUNCT
ejpam-5015	381	13	surpassing	surpass	VERB
ejpam-5015	381	14	their	their	PRON
ejpam-5015	381	15	frequentist	frequentist	NOUN
ejpam-5015	381	16	counterparts	counterpart	NOUN
ejpam-5015	381	17	using	use	VERB
ejpam-5015	381	18	the	the	DET
ejpam-5015	381	19	same	same	ADJ
ejpam-5015	381	20	mrss	mrss	NOUN
ejpam-5015	381	21	methodology	methodology	NOUN
ejpam-5015	381	22	,	,	PUNCT
ejpam-5015	381	23	at	at	ADP
ejpam-5015	381	24	least	least	ADJ
ejpam-5015	381	25	for	for	ADP
ejpam-5015	381	26	one	one	NUM
ejpam-5015	381	27	mrss	mrss	NOUN
ejpam-5015	381	28	design	design	NOUN
ejpam-5015	381	29	.	.	PUNCT
ejpam-5015	382	1	additionally	additionally	ADV
ejpam-5015	382	2	,	,	PUNCT
ejpam-5015	382	3	it	it	PRON
ejpam-5015	382	4	was	be	AUX
ejpam-5015	382	5	observed	observe	VERB
ejpam-5015	382	6	that	that	SCONJ
ejpam-5015	382	7	the	the	DET
ejpam-5015	382	8	bayesian	bayesian	NOUN
ejpam-5015	382	9	standard	standard	ADJ
ejpam-5015	382	10	error	error	NOUN
ejpam-5015	382	11	for	for	ADP
ejpam-5015	382	12	all	all	DET
ejpam-5015	382	13	parameters	parameter	NOUN
ejpam-5015	382	14	diminished	diminish	VERB
ejpam-5015	382	15	as	as	ADP
ejpam-5015	382	16	the	the	DET
ejpam-5015	382	17	values	value	NOUN
ejpam-5015	382	18	of	of	ADP
ejpam-5015	382	19	m	m	PRON
ejpam-5015	382	20	increased	increase	VERB
ejpam-5015	382	21	.	.	PUNCT
ejpam-5015	383	1	however	however	ADV
ejpam-5015	383	2	,	,	PUNCT
ejpam-5015	383	3	this	this	DET
ejpam-5015	383	4	study	study	NOUN
ejpam-5015	383	5	is	be	AUX
ejpam-5015	383	6	not	not	PART
ejpam-5015	383	7	without	without	ADP
ejpam-5015	383	8	its	its	PRON
ejpam-5015	383	9	limitations	limitation	NOUN
ejpam-5015	383	10	.	.	PUNCT
ejpam-5015	384	1	the	the	DET
ejpam-5015	384	2	efficiency	efficiency	NOUN
ejpam-5015	384	3	of	of	ADP
ejpam-5015	384	4	the	the	DET
ejpam-5015	384	5	bayesian	bayesian	NOUN
ejpam-5015	384	6	estimators	estimator	NOUN
ejpam-5015	384	7	was	be	AUX
ejpam-5015	384	8	established	establish	VERB
ejpam-5015	384	9	in	in	ADP
ejpam-5015	384	10	the	the	DET
ejpam-5015	384	11	context	context	NOUN
ejpam-5015	384	12	of	of	ADP
ejpam-5015	384	13	one	one	NUM
ejpam-5015	384	14	mrss	mrss	ADJ
ejpam-5015	384	15	specific	specific	ADJ
ejpam-5015	384	16	design	design	NOUN
ejpam-5015	384	17	and	and	CCONJ
ejpam-5015	384	18	this	this	PRON
ejpam-5015	384	19	may	may	AUX
ejpam-5015	384	20	not	not	PART
ejpam-5015	384	21	hold	hold	VERB
ejpam-5015	384	22	true	true	ADJ
ejpam-5015	384	23	for	for	ADP
ejpam-5015	384	24	all	all	DET
ejpam-5015	384	25	mrss	mrss	ADJ
ejpam-5015	384	26	design	design	NOUN
ejpam-5015	384	27	.	.	PUNCT
ejpam-5015	385	1	mrss	mrss	PROPN
ejpam-5015	385	2	is	be	AUX
ejpam-5015	385	3	a	a	DET
ejpam-5015	385	4	specific	specific	ADJ
ejpam-5015	385	5	type	type	NOUN
ejpam-5015	385	6	of	of	ADP
ejpam-5015	385	7	rss	rss	NOUN
ejpam-5015	385	8	where	where	SCONJ
ejpam-5015	385	9	the	the	DET
ejpam-5015	385	10	median	median	ADJ
ejpam-5015	385	11	item	item	NOUN
ejpam-5015	385	12	from	from	ADP
ejpam-5015	385	13	each	each	DET
ejpam-5015	385	14	subset	subset	NOUN
ejpam-5015	385	15	is	be	AUX
ejpam-5015	385	16	chosen	choose	VERB
ejpam-5015	385	17	.	.	PUNCT
ejpam-5015	386	1	the	the	DET
ejpam-5015	386	2	way	way	NOUN
ejpam-5015	386	3	these	these	DET
ejpam-5015	386	4	subsets	subset	NOUN
ejpam-5015	386	5	are	be	AUX
ejpam-5015	386	6	chosen	choose	VERB
ejpam-5015	386	7	and	and	CCONJ
ejpam-5015	386	8	ranked	rank	VERB
ejpam-5015	386	9	can	can	AUX
ejpam-5015	386	10	vary	vary	VERB
ejpam-5015	386	11	,	,	PUNCT
ejpam-5015	386	12	and	and	CCONJ
ejpam-5015	386	13	these	these	DET
ejpam-5015	386	14	specifics	specific	NOUN
ejpam-5015	386	15	constitute	constitute	VERB
ejpam-5015	386	16	the	the	DET
ejpam-5015	386	17	mrss	mrss	PROPN
ejpam-5015	386	18	design	design	NOUN
ejpam-5015	386	19	.	.	PUNCT
ejpam-5015	387	1	further	further	ADJ
ejpam-5015	387	2	research	research	NOUN
ejpam-5015	387	3	should	should	AUX
ejpam-5015	387	4	investigate	investigate	VERB
ejpam-5015	387	5	the	the	DET
ejpam-5015	387	6	performance	performance	NOUN
ejpam-5015	387	7	of	of	ADP
ejpam-5015	387	8	bayesian	bayesian	NOUN
ejpam-5015	387	9	estimators	estimator	NOUN
ejpam-5015	387	10	in	in	ADP
ejpam-5015	387	11	a	a	DET
ejpam-5015	387	12	more	more	ADV
ejpam-5015	387	13	diverse	diverse	ADJ
ejpam-5015	387	14	range	range	NOUN
ejpam-5015	387	15	of	of	ADP
ejpam-5015	387	16	mrss	mrss	ADJ
ejpam-5015	387	17	design	design	NOUN
ejpam-5015	387	18	.	.	PUNCT
ejpam-5015	388	1	additionally	additionally	ADV
ejpam-5015	388	2	,	,	PUNCT
ejpam-5015	388	3	this	this	DET
ejpam-5015	388	4	study	study	NOUN
ejpam-5015	388	5	has	have	AUX
ejpam-5015	388	6	taken	take	VERB
ejpam-5015	388	7	a	a	DET
ejpam-5015	388	8	symmetric	symmetric	ADJ
ejpam-5015	388	9	distribution	distribution	NOUN
ejpam-5015	388	10	of	of	ADP
ejpam-5015	388	11	random	random	ADJ
ejpam-5015	388	12	errors	error	NOUN
ejpam-5015	388	13	as	as	ADP
ejpam-5015	388	14	an	an	DET
ejpam-5015	388	15	assumption	assumption	NOUN
ejpam-5015	388	16	.	.	PUNCT
ejpam-5015	389	1	future	future	ADJ
ejpam-5015	389	2	investigations	investigation	NOUN
ejpam-5015	389	3	could	could	AUX
ejpam-5015	389	4	benefit	benefit	VERB
ejpam-5015	389	5	from	from	ADP
ejpam-5015	389	6	considering	consider	VERB
ejpam-5015	389	7	asymmetric	asymmetric	ADJ
ejpam-5015	389	8	or	or	CCONJ
ejpam-5015	389	9	heavy	heavy	ADV
ejpam-5015	389	10	-	-	PUNCT
ejpam-5015	389	11	tailed	tail	VERB
ejpam-5015	389	12	error	error	NOUN
ejpam-5015	389	13	distributions	distribution	NOUN
ejpam-5015	389	14	to	to	PART
ejpam-5015	389	15	expand	expand	VERB
ejpam-5015	389	16	the	the	DET
ejpam-5015	389	17	scope	scope	NOUN
ejpam-5015	389	18	of	of	ADP
ejpam-5015	389	19	this	this	DET
ejpam-5015	389	20	research	research	NOUN
ejpam-5015	389	21	.	.	PUNCT
ejpam-5015	390	1	moreover	moreover	ADV
ejpam-5015	390	2	,	,	PUNCT
ejpam-5015	390	3	while	while	SCONJ
ejpam-5015	390	4	this	this	DET
ejpam-5015	390	5	study	study	NOUN
ejpam-5015	390	6	highlights	highlight	VERB
ejpam-5015	390	7	the	the	DET
ejpam-5015	390	8	increased	increase	VERB
ejpam-5015	390	9	efficiency	efficiency	NOUN
ejpam-5015	390	10	and	and	CCONJ
ejpam-5015	390	11	simplicity	simplicity	NOUN
ejpam-5015	390	12	of	of	ADP
ejpam-5015	390	13	the	the	DET
ejpam-5015	390	14	bayesian	bayesian	NOUN
ejpam-5015	390	15	approach	approach	NOUN
ejpam-5015	390	16	,	,	PUNCT
ejpam-5015	390	17	it	it	PRON
ejpam-5015	390	18	is	be	AUX
ejpam-5015	390	19	crucial	crucial	ADJ
ejpam-5015	390	20	to	to	PART
ejpam-5015	390	21	further	far	ADV
ejpam-5015	390	22	explore	explore	VERB
ejpam-5015	390	23	the	the	DET
ejpam-5015	390	24	computational	computational	ADJ
ejpam-5015	390	25	aspects	aspect	NOUN
ejpam-5015	390	26	and	and	CCONJ
ejpam-5015	390	27	feasibility	feasibility	NOUN
ejpam-5015	390	28	of	of	ADP
ejpam-5015	390	29	these	these	DET
ejpam-5015	390	30	methods	method	NOUN
ejpam-5015	390	31	,	,	PUNCT
ejpam-5015	390	32	especially	especially	ADV
ejpam-5015	390	33	in	in	ADP
ejpam-5015	390	34	the	the	DET
ejpam-5015	390	35	context	context	NOUN
ejpam-5015	390	36	of	of	ADP
ejpam-5015	390	37	large	large	ADJ
ejpam-5015	390	38	-	-	PUNCT
ejpam-5015	390	39	scale	scale	NOUN
ejpam-5015	390	40	data	datum	NOUN
ejpam-5015	390	41	.	.	PUNCT
ejpam-5015	391	1	future	future	ADJ
ejpam-5015	391	2	research	research	NOUN
ejpam-5015	391	3	should	should	AUX
ejpam-5015	391	4	also	also	ADV
ejpam-5015	391	5	delve	delve	VERB
ejpam-5015	391	6	into	into	ADP
ejpam-5015	391	7	the	the	DET
ejpam-5015	391	8	practical	practical	ADJ
ejpam-5015	391	9	implications	implication	NOUN
ejpam-5015	391	10	and	and	CCONJ
ejpam-5015	391	11	applications	application	NOUN
ejpam-5015	391	12	of	of	ADP
ejpam-5015	391	13	the	the	DET
ejpam-5015	391	14	methodology	methodology	NOUN
ejpam-5015	391	15	proposed	propose	VERB
ejpam-5015	391	16	in	in	ADP
ejpam-5015	391	17	this	this	DET
ejpam-5015	391	18	study	study	NOUN
ejpam-5015	391	19	,	,	PUNCT
ejpam-5015	391	20	in	in	ADP
ejpam-5015	391	21	various	various	ADJ
ejpam-5015	391	22	fields	field	NOUN
ejpam-5015	391	23	and	and	CCONJ
ejpam-5015	391	24	for	for	ADP
ejpam-5015	391	25	a	a	DET
ejpam-5015	391	26	variety	variety	NOUN
ejpam-5015	391	27	of	of	ADP
ejpam-5015	391	28	research	research	NOUN
ejpam-5015	391	29	questions	question	NOUN
ejpam-5015	391	30	.	.	PUNCT
ejpam-5015	392	1	in	in	ADP
ejpam-5015	392	2	conclusion	conclusion	NOUN
ejpam-5015	392	3	,	,	PUNCT
ejpam-5015	392	4	this	this	DET
ejpam-5015	392	5	study	study	NOUN
ejpam-5015	392	6	has	have	AUX
ejpam-5015	392	7	paved	pave	VERB
ejpam-5015	392	8	the	the	DET
ejpam-5015	392	9	way	way	NOUN
ejpam-5015	392	10	for	for	ADP
ejpam-5015	392	11	further	further	ADJ
ejpam-5015	392	12	research	research	NOUN
ejpam-5015	392	13	in	in	ADP
ejpam-5015	392	14	the	the	DET
ejpam-5015	392	15	field	field	NOUN
ejpam-5015	392	16	of	of	ADP
ejpam-5015	392	17	bayesian	bayesian	NOUN
ejpam-5015	392	18	estimation	estimation	NOUN
ejpam-5015	392	19	using	use	VERB
ejpam-5015	392	20	mrss	mrss	NOUN
ejpam-5015	392	21	,	,	PUNCT
ejpam-5015	392	22	providing	provide	VERB
ejpam-5015	392	23	a	a	DET
ejpam-5015	392	24	springboard	springboard	NOUN
ejpam-5015	392	25	for	for	ADP
ejpam-5015	392	26	more	more	ADV
ejpam-5015	392	27	extensive	extensive	ADJ
ejpam-5015	392	28	studies	study	NOUN
ejpam-5015	392	29	,	,	PUNCT
ejpam-5015	392	30	wider	wide	ADJ
ejpam-5015	392	31	applications	application	NOUN
ejpam-5015	392	32	,	,	PUNCT
ejpam-5015	392	33	and	and	CCONJ
ejpam-5015	392	34	refined	refined	ADJ
ejpam-5015	392	35	methodologies	methodology	NOUN
ejpam-5015	392	36	.	.	PUNCT
ejpam-5015	393	1	acknowledgements	acknowledgement	NOUN
ejpam-5015	393	2	the	the	DET
ejpam-5015	393	3	authors	author	NOUN
ejpam-5015	393	4	are	be	AUX
ejpam-5015	393	5	grateful	grateful	ADJ
ejpam-5015	393	6	to	to	ADP
ejpam-5015	393	7	the	the	DET
ejpam-5015	393	8	hebron	hebron	PROPN
ejpam-5015	393	9	university	university	PROPN
ejpam-5015	393	10	,	,	PUNCT
ejpam-5015	393	11	palestine	palestine	PROPN
ejpam-5015	393	12	american	american	PROPN
ejpam-5015	393	13	university	university	PROPN
ejpam-5015	393	14	of	of	ADP
ejpam-5015	393	15	the	the	DET
ejpam-5015	393	16	middle	middle	PROPN
ejpam-5015	393	17	east	east	PROPN
ejpam-5015	393	18	,	,	PUNCT
ejpam-5015	393	19	egaila	egaila	PROPN
ejpam-5015	393	20	54200	54200	NUM
ejpam-5015	393	21	,	,	PUNCT
ejpam-5015	393	22	kuwait	kuwait	PROPN
ejpam-5015	393	23	,	,	PUNCT
ejpam-5015	393	24	and	and	CCONJ
ejpam-5015	393	25	palestine	palestine	PROPN
ejpam-5015	393	26	technical	technical	PROPN
ejpam-5015	393	27	university	university	PROPN
ejpam-5015	393	28	–	–	PUNCT
ejpam-5015	393	29	kadoorie	kadoorie	NOUN
ejpam-5015	393	30	,	,	PUNCT
ejpam-5015	393	31	palestine	palestine	PROPN
ejpam-5015	393	32	,	,	PUNCT
ejpam-5015	393	33	for	for	ADP
ejpam-5015	393	34	their	their	PRON
ejpam-5015	393	35	support	support	NOUN
ejpam-5015	393	36	in	in	ADP
ejpam-5015	393	37	completing	complete	VERB
ejpam-5015	393	38	this	this	DET
ejpam-5015	393	39	research	research	NOUN
ejpam-5015	393	40	.	.	PUNCT
ejpam-5015	394	1	references	reference	NOUN
ejpam-5015	394	2	[	[	X
ejpam-5015	394	3	1	1	X
ejpam-5015	394	4	]	]	PUNCT
ejpam-5015	394	5	said	say	VERB
ejpam-5015	394	6	ali	ali	PROPN
ejpam-5015	394	7	al	al	PROPN
ejpam-5015	394	8	-	-	PUNCT
ejpam-5015	394	9	hadhrami	hadhrami	PROPN
ejpam-5015	394	10	and	and	CCONJ
ejpam-5015	394	11	amer	amer	PROPN
ejpam-5015	394	12	ibrahim	ibrahim	PROPN
ejpam-5015	394	13	al	al	PROPN
ejpam-5015	394	14	-	-	PUNCT
ejpam-5015	394	15	omari	omari	PROPN
ejpam-5015	394	16	.	.	PUNCT
ejpam-5015	395	1	bayesian	bayesian	NOUN
ejpam-5015	395	2	inference	inference	NOUN
ejpam-5015	395	3	on	on	ADP
ejpam-5015	395	4	the	the	DET
ejpam-5015	395	5	variance	variance	NOUN
ejpam-5015	395	6	of	of	ADP
ejpam-5015	395	7	normal	normal	ADJ
ejpam-5015	395	8	distribution	distribution	NOUN
ejpam-5015	395	9	using	use	VERB
ejpam-5015	395	10	moving	move	VERB
ejpam-5015	395	11	extremes	extreme	NOUN
ejpam-5015	395	12	ranked	rank	VERB
ejpam-5015	395	13	set	set	ADJ
ejpam-5015	395	14	sampling	sampling	NOUN
ejpam-5015	395	15	.	.	PUNCT
ejpam-5015	396	1	journal	journal	NOUN
ejpam-5015	396	2	of	of	ADP
ejpam-5015	396	3	modern	modern	ADJ
ejpam-5015	396	4	applied	apply	VERB
ejpam-5015	396	5	statistical	statistical	ADJ
ejpam-5015	396	6	methods	method	NOUN
ejpam-5015	396	7	,	,	PUNCT
ejpam-5015	396	8	8(1):25	8(1):25	NUM
ejpam-5015	396	9	,	,	PUNCT
ejpam-5015	396	10	2009	2009	NUM
ejpam-5015	396	11	.	.	PUNCT
ejpam-5015	397	1	[	[	X
ejpam-5015	397	2	2	2	NUM
ejpam-5015	397	3	]	]	PUNCT
ejpam-5015	397	4	m	m	VERB
ejpam-5015	397	5	fraiwan	fraiwan	NOUN
ejpam-5015	397	6	al	al	PROPN
ejpam-5015	397	7	-	-	PUNCT
ejpam-5015	397	8	saleh	saleh	PROPN
ejpam-5015	397	9	,	,	PUNCT
ejpam-5015	397	10	khalaf	khalaf	PROPN
ejpam-5015	397	11	al	al	PROPN
ejpam-5015	397	12	-	-	PUNCT
ejpam-5015	397	13	shrafat	shrafat	PROPN
ejpam-5015	397	14	,	,	PUNCT
ejpam-5015	397	15	and	and	CCONJ
ejpam-5015	397	16	h	h	NOUN
ejpam-5015	397	17	muttlak	muttlak	ADJ
ejpam-5015	397	18	.	.	PUNCT
ejpam-5015	398	1	bayesian	bayesian	NOUN
ejpam-5015	398	2	estimation	estimation	NOUN
ejpam-5015	398	3	using	use	VERB
ejpam-5015	398	4	ranked	rank	VERB
ejpam-5015	398	5	set	set	ADJ
ejpam-5015	398	6	references	reference	NOUN
ejpam-5015	398	7	199	199	NUM
ejpam-5015	398	8	sampling	sampling	NOUN
ejpam-5015	398	9	.	.	PUNCT
ejpam-5015	399	1	biometrical	biometrical	ADJ
ejpam-5015	399	2	journal	journal	PROPN
ejpam-5015	399	3	:	:	PUNCT
ejpam-5015	399	4	journal	journal	PROPN
ejpam-5015	399	5	of	of	ADP
ejpam-5015	399	6	mathematical	mathematical	ADJ
ejpam-5015	399	7	methods	method	NOUN
ejpam-5015	399	8	in	in	ADP
ejpam-5015	399	9	biosciences	bioscience	NOUN
ejpam-5015	399	10	,	,	PUNCT
ejpam-5015	399	11	42(4):489	42(4):489	NUM
ejpam-5015	399	12	–	–	PUNCT
ejpam-5015	399	13	500	500	NUM
ejpam-5015	399	14	,	,	PUNCT
ejpam-5015	399	15	2000	2000	NUM
ejpam-5015	399	16	.	.	PUNCT
ejpam-5015	400	1	[	[	X
ejpam-5015	400	2	3	3	X
ejpam-5015	400	3	]	]	X
ejpam-5015	400	4	mohammad	mohammad	PROPN
ejpam-5015	400	5	fraiwan	fraiwan	PROPN
ejpam-5015	400	6	al	al	PROPN
ejpam-5015	400	7	-	-	PUNCT
ejpam-5015	400	8	saleh	saleh	PROPN
ejpam-5015	400	9	and	and	CCONJ
ejpam-5015	400	10	khalaf	khalaf	PROPN
ejpam-5015	400	11	al	al	PROPN
ejpam-5015	400	12	-	-	PUNCT
ejpam-5015	400	13	shrafat	shrafat	NOUN
ejpam-5015	400	14	.	.	PUNCT
ejpam-5015	401	1	estimation	estimation	NOUN
ejpam-5015	401	2	of	of	ADP
ejpam-5015	401	3	average	average	ADJ
ejpam-5015	401	4	milk	milk	NOUN
ejpam-5015	401	5	yield	yield	NOUN
ejpam-5015	401	6	using	use	VERB
ejpam-5015	401	7	ranked	rank	VERB
ejpam-5015	401	8	set	set	ADJ
ejpam-5015	401	9	sampling	sampling	NOUN
ejpam-5015	401	10	.	.	PUNCT
ejpam-5015	402	1	environmetrics	environmetric	NOUN
ejpam-5015	402	2	:	:	PUNCT
ejpam-5015	402	3	the	the	DET
ejpam-5015	402	4	official	official	ADJ
ejpam-5015	402	5	journal	journal	NOUN
ejpam-5015	402	6	of	of	ADP
ejpam-5015	402	7	the	the	DET
ejpam-5015	402	8	international	international	ADJ
ejpam-5015	402	9	environmetrics	environmetrics	PROPN
ejpam-5015	402	10	society	society	NOUN
ejpam-5015	402	11	,	,	PUNCT
ejpam-5015	402	12	12(4):395–399	12(4):395–399	NUM
ejpam-5015	402	13	,	,	PUNCT
ejpam-5015	402	14	2001	2001	NUM
ejpam-5015	402	15	.	.	PUNCT
ejpam-5015	403	1	[	[	X
ejpam-5015	403	2	4	4	X
ejpam-5015	403	3	]	]	X
ejpam-5015	403	4	aa	aa	NOUN
ejpam-5015	403	5	alhamide	alhamide	PROPN
ejpam-5015	403	6	,	,	PUNCT
ejpam-5015	403	7	kamarulzaman	kamarulzaman	PROPN
ejpam-5015	403	8	ibrahim	ibrahim	PROPN
ejpam-5015	403	9	,	,	PUNCT
ejpam-5015	403	10	mt	mt	PROPN
ejpam-5015	403	11	alodat	alodat	PROPN
ejpam-5015	403	12	,	,	PUNCT
ejpam-5015	403	13	and	and	CCONJ
ejpam-5015	403	14	wan	wan	PROPN
ejpam-5015	403	15	zawiah	zawiah	PROPN
ejpam-5015	403	16	wan	wan	PROPN
ejpam-5015	403	17	zin	zin	PROPN
ejpam-5015	403	18	.	.	PUNCT
ejpam-5015	404	1	bayesian	bayesian	NOUN
ejpam-5015	404	2	inference	inference	NOUN
ejpam-5015	404	3	for	for	ADP
ejpam-5015	404	4	linear	linear	ADJ
ejpam-5015	404	5	regression	regression	NOUN
ejpam-5015	404	6	under	under	ADP
ejpam-5015	404	7	alpha	alpha	NOUN
ejpam-5015	404	8	-	-	PUNCT
ejpam-5015	404	9	skew	skew	NOUN
ejpam-5015	404	10	-	-	PUNCT
ejpam-5015	404	11	normal	normal	ADJ
ejpam-5015	404	12	prior	prior	ADV
ejpam-5015	404	13	.	.	PUNCT
ejpam-5015	405	1	sains	sain	NOUN
ejpam-5015	405	2	malaysiana	malaysiana	PROPN
ejpam-5015	405	3	,	,	PUNCT
ejpam-5015	405	4	48(1):227	48(1):227	PROPN
ejpam-5015	405	5	–	–	PUNCT
ejpam-5015	405	6	235	235	NUM
ejpam-5015	405	7	,	,	PUNCT
ejpam-5015	405	8	2019	2019	NUM
ejpam-5015	405	9	.	.	PUNCT
ejpam-5015	406	1	[	[	X
ejpam-5015	406	2	5	5	X
ejpam-5015	406	3	]	]	X
ejpam-5015	406	4	iftikhar	iftikhar	PROPN
ejpam-5015	406	5	ali	ali	PROPN
ejpam-5015	406	6	,	,	PUNCT
ejpam-5015	406	7	nabaa	nabaa	PROPN
ejpam-5015	406	8	muhammad	muhammad	PROPN
ejpam-5015	406	9	diaa	diaa	PROPN
ejpam-5015	406	10	,	,	PUNCT
ejpam-5015	406	11	muhammad	muhammad	PROPN
ejpam-5015	406	12	haroon	haroon	PROPN
ejpam-5015	406	13	aftab	aftab	PROPN
ejpam-5015	406	14	,	,	PUNCT
ejpam-5015	406	15	muhammad	muhammad	PROPN
ejpam-5015	406	16	waheed	waheed	PROPN
ejpam-5015	406	17	raheed	raheed	PROPN
ejpam-5015	406	18	,	,	PUNCT
ejpam-5015	406	19	kamel	kamel	PROPN
ejpam-5015	406	20	jebreen	jebreen	PROPN
ejpam-5015	406	21	,	,	PUNCT
ejpam-5015	406	22	and	and	CCONJ
ejpam-5015	406	23	hassan	hassan	PROPN
ejpam-5015	406	24	kanj	kanj	PROPN
ejpam-5015	406	25	.	.	PUNCT
ejpam-5015	407	1	topological	topological	ADJ
ejpam-5015	407	2	effects	effect	NOUN
ejpam-5015	407	3	of	of	ADP
ejpam-5015	407	4	chiral	chiral	ADJ
ejpam-5015	407	5	pamam	pamam	NOUN
ejpam-5015	407	6	dendrimer	dendrimer	NOUN
ejpam-5015	407	7	for	for	ADP
ejpam-5015	407	8	the	the	DET
ejpam-5015	407	9	treatment	treatment	NOUN
ejpam-5015	407	10	of	of	ADP
ejpam-5015	407	11	cancer	cancer	NOUN
ejpam-5015	407	12	.	.	PUNCT
ejpam-5015	408	1	31(2	31(2	NUM
ejpam-5015	408	2	)	)	PUNCT
ejpam-5015	408	3	.	.	PUNCT
ejpam-5015	409	1	[	[	X
ejpam-5015	409	2	6	6	NUM
ejpam-5015	409	3	]	]	PUNCT
ejpam-5015	409	4	mt	mt	PROPN
ejpam-5015	409	5	alodat	alodat	PROPN
ejpam-5015	409	6	,	,	PUNCT
ejpam-5015	409	7	mt	mt	PROPN
ejpam-5015	409	8	al	al	PROPN
ejpam-5015	409	9	-	-	PUNCT
ejpam-5015	409	10	rawwash	rawwash	PROPN
ejpam-5015	409	11	,	,	PUNCT
ejpam-5015	409	12	and	and	CCONJ
ejpam-5015	409	13	i	i	PRON
ejpam-5015	409	14	m	m	VERB
ejpam-5015	409	15	nawajah	nawajah	PROPN
ejpam-5015	409	16	.	.	PUNCT
ejpam-5015	410	1	analysis	analysis	NOUN
ejpam-5015	410	2	of	of	ADP
ejpam-5015	410	3	simple	simple	ADJ
ejpam-5015	410	4	linear	linear	ADJ
ejpam-5015	410	5	regression	regression	NOUN
ejpam-5015	410	6	via	via	ADP
ejpam-5015	410	7	median	median	PROPN
ejpam-5015	410	8	ranked	rank	VERB
ejpam-5015	410	9	set	set	ADJ
ejpam-5015	410	10	sampling	sampling	NOUN
ejpam-5015	410	11	.	.	PUNCT
ejpam-5015	411	1	metron	metron	PROPN
ejpam-5015	411	2	,	,	PUNCT
ejpam-5015	411	3	67(1):57–74	67(1):57–74	NUM
ejpam-5015	411	4	,	,	PUNCT
ejpam-5015	411	5	2009	2009	NUM
ejpam-5015	411	6	.	.	PUNCT
ejpam-5015	412	1	[	[	X
ejpam-5015	412	2	7	7	X
ejpam-5015	412	3	]	]	X
ejpam-5015	412	4	mt	mt	PROPN
ejpam-5015	412	5	alodat	alodat	PROPN
ejpam-5015	412	6	,	,	PUNCT
ejpam-5015	412	7	my	my	PRON
ejpam-5015	412	8	al	al	PROPN
ejpam-5015	412	9	-	-	PUNCT
ejpam-5015	412	10	rawwash	rawwash	NOUN
ejpam-5015	412	11	,	,	PUNCT
ejpam-5015	412	12	and	and	CCONJ
ejpam-5015	412	13	i	i	PRON
ejpam-5015	412	14	m	m	VERB
ejpam-5015	412	15	nawajah	nawajah	PROPN
ejpam-5015	412	16	.	.	PUNCT
ejpam-5015	413	1	inference	inference	NOUN
ejpam-5015	413	2	about	about	ADP
ejpam-5015	413	3	the	the	DET
ejpam-5015	413	4	regression	regression	NOUN
ejpam-5015	413	5	parameters	parameter	NOUN
ejpam-5015	413	6	using	use	VERB
ejpam-5015	413	7	median	median	NOUN
ejpam-5015	413	8	-	-	PUNCT
ejpam-5015	413	9	ranked	rank	VERB
ejpam-5015	413	10	set	set	ADJ
ejpam-5015	413	11	sampling	sampling	NOUN
ejpam-5015	413	12	.	.	PUNCT
ejpam-5015	414	1	communications	communication	NOUN
ejpam-5015	414	2	in	in	ADP
ejpam-5015	414	3	statistics	statistic	NOUN
ejpam-5015	414	4	—	—	PUNCT
ejpam-5015	414	5	theory	theory	NOUN
ejpam-5015	414	6	and	and	CCONJ
ejpam-5015	414	7	methods	method	NOUN
ejpam-5015	414	8	,	,	PUNCT
ejpam-5015	414	9	39(14):2604–2616	39(14):2604–2616	NUM
ejpam-5015	414	10	,	,	PUNCT
ejpam-5015	414	11	2010	2010	NUM
ejpam-5015	414	12	.	.	PUNCT
ejpam-5015	415	1	[	[	X
ejpam-5015	415	2	8	8	NUM
ejpam-5015	415	3	]	]	X
ejpam-5015	415	4	mt	mt	PROPN
ejpam-5015	415	5	alodat	alodat	PROPN
ejpam-5015	415	6	and	and	CCONJ
ejpam-5015	415	7	oa	oa	PROPN
ejpam-5015	415	8	al	al	PROPN
ejpam-5015	415	9	-	-	PUNCT
ejpam-5015	415	10	sagheer	sagheer	NOUN
ejpam-5015	415	11	.	.	PUNCT
ejpam-5015	416	1	estimation	estimation	NOUN
ejpam-5015	416	2	the	the	DET
ejpam-5015	416	3	location	location	NOUN
ejpam-5015	416	4	and	and	CCONJ
ejpam-5015	416	5	scale	scale	NOUN
ejpam-5015	416	6	parameters	parameter	NOUN
ejpam-5015	416	7	using	use	VERB
ejpam-5015	416	8	ranked	rank	VERB
ejpam-5015	416	9	set	set	ADJ
ejpam-5015	416	10	sampling	sampling	NOUN
ejpam-5015	416	11	.	.	PUNCT
ejpam-5015	417	1	j.	j.	PROPN
ejpam-5015	417	2	appl	appl	PROPN
ejpam-5015	417	3	.	.	PROPN
ejpam-5015	418	1	statis	statis	PROPN
ejpam-5015	418	2	.	.	PUNCT
ejpam-5015	419	1	sci	sci	PROPN
ejpam-5015	419	2	,	,	PUNCT
ejpam-5015	419	3	15:245–252	15:245–252	NUM
ejpam-5015	419	4	,	,	PUNCT
ejpam-5015	419	5	2007	2007	NUM
ejpam-5015	419	6	.	.	PUNCT
ejpam-5015	420	1	[	[	X
ejpam-5015	420	2	9	9	NUM
ejpam-5015	420	3	]	]	PUNCT
ejpam-5015	420	4	kara	kara	PROPN
ejpam-5015	420	5	gülay	gülay	PROPN
ejpam-5015	420	6	begüm	begüm	NOUN
ejpam-5015	420	7	and	and	CCONJ
ejpam-5015	420	8	demirel	demirel	NOUN
ejpam-5015	420	9	neslihan	neslihan	NOUN
ejpam-5015	420	10	.	.	PUNCT
ejpam-5015	421	1	two	two	NUM
ejpam-5015	421	2	-	-	PUNCT
ejpam-5015	421	3	layer	layer	NOUN
ejpam-5015	421	4	median	median	NOUN
ejpam-5015	421	5	ranked	rank	VERB
ejpam-5015	421	6	set	set	ADJ
ejpam-5015	421	7	sampling	sampling	NOUN
ejpam-5015	421	8	.	.	PUNCT
ejpam-5015	422	1	hacettepe	hacettepe	PROPN
ejpam-5015	422	2	journal	journal	PROPN
ejpam-5015	422	3	of	of	ADP
ejpam-5015	422	4	mathematics	mathematic	NOUN
ejpam-5015	422	5	and	and	CCONJ
ejpam-5015	422	6	statistics	statistic	NOUN
ejpam-5015	422	7	,	,	PUNCT
ejpam-5015	422	8	page	page	NOUN
ejpam-5015	422	9	1–10	1–10	NOUN
ejpam-5015	422	10	.	.	PUNCT
ejpam-5015	423	1	[	[	X
ejpam-5015	423	2	10	10	NUM
ejpam-5015	423	3	]	]	X
ejpam-5015	423	4	maria	maria	PROPN
ejpam-5015	423	5	de	de	X
ejpam-5015	423	6	iorio	iorio	PROPN
ejpam-5015	423	7	,	,	PUNCT
ejpam-5015	423	8	peter	peter	PROPN
ejpam-5015	423	9	müller	müller	PROPN
ejpam-5015	423	10	,	,	PUNCT
ejpam-5015	423	11	gary	gary	PROPN
ejpam-5015	423	12	l	l	PROPN
ejpam-5015	423	13	rosner	rosner	PROPN
ejpam-5015	423	14	,	,	PUNCT
ejpam-5015	423	15	and	and	CCONJ
ejpam-5015	423	16	steven	steven	PROPN
ejpam-5015	423	17	n	n	PROPN
ejpam-5015	423	18	maceachern	maceachern	NOUN
ejpam-5015	423	19	.	.	PUNCT
ejpam-5015	424	1	an	an	DET
ejpam-5015	424	2	anova	anova	PROPN
ejpam-5015	424	3	model	model	NOUN
ejpam-5015	424	4	for	for	ADP
ejpam-5015	424	5	dependent	dependent	ADJ
ejpam-5015	424	6	random	random	ADJ
ejpam-5015	424	7	measures	measure	NOUN
ejpam-5015	424	8	.	.	PUNCT
ejpam-5015	425	1	journal	journal	NOUN
ejpam-5015	425	2	of	of	ADP
ejpam-5015	425	3	the	the	DET
ejpam-5015	425	4	american	american	PROPN
ejpam-5015	425	5	statistical	statistical	PROPN
ejpam-5015	425	6	association	association	NOUN
ejpam-5015	425	7	,	,	PUNCT
ejpam-5015	425	8	99(465):205	99(465):205	NUM
ejpam-5015	425	9	–	–	PUNCT
ejpam-5015	425	10	215	215	NUM
ejpam-5015	425	11	,	,	PUNCT
ejpam-5015	425	12	2004	2004	NUM
ejpam-5015	425	13	.	.	PUNCT
ejpam-5015	426	1	[	[	X
ejpam-5015	426	2	11	11	NUM
ejpam-5015	426	3	]	]	PUNCT
ejpam-5015	426	4	begüm	begüm	VERB
ejpam-5015	426	5	kara	kara	PROPN
ejpam-5015	426	6	gülay	gülay	PROPN
ejpam-5015	426	7	and	and	CCONJ
ejpam-5015	426	8	neslihan	neslihan	NOUN
ejpam-5015	426	9	demirel	demirel	NOUN
ejpam-5015	426	10	.	.	PUNCT
ejpam-5015	427	1	two	two	NUM
ejpam-5015	427	2	-	-	PUNCT
ejpam-5015	427	3	layer	layer	NOUN
ejpam-5015	427	4	median	median	NOUN
ejpam-5015	427	5	ranked	rank	VERB
ejpam-5015	427	6	set	set	ADJ
ejpam-5015	427	7	sampling	sampling	NOUN
ejpam-5015	427	8	.	.	PUNCT
ejpam-5015	428	1	hacettepe	hacettepe	PROPN
ejpam-5015	428	2	journal	journal	PROPN
ejpam-5015	428	3	of	of	ADP
ejpam-5015	428	4	mathematics	mathematic	NOUN
ejpam-5015	428	5	and	and	CCONJ
ejpam-5015	428	6	statistics	statistic	NOUN
ejpam-5015	428	7	,	,	PUNCT
ejpam-5015	428	8	48:1–10	48:1–10	NOUN
ejpam-5015	428	9	,	,	PUNCT
ejpam-5015	428	10	2019	2019	NUM
ejpam-5015	428	11	.	.	PUNCT
ejpam-5015	429	1	[	[	X
ejpam-5015	429	2	12	12	NUM
ejpam-5015	429	3	]	]	PUNCT
ejpam-5015	429	4	abdul	abdul	PROPN
ejpam-5015	429	5	haq	haq	PROPN
ejpam-5015	429	6	,	,	PUNCT
ejpam-5015	429	7	jennifer	jennifer	PROPN
ejpam-5015	429	8	brown	brown	PROPN
ejpam-5015	429	9	,	,	PUNCT
ejpam-5015	429	10	and	and	CCONJ
ejpam-5015	429	11	elena	elena	PROPN
ejpam-5015	429	12	moltchanova	moltchanova	PROPN
ejpam-5015	429	13	.	.	PUNCT
ejpam-5015	430	1	improved	improve	VERB
ejpam-5015	430	2	best	good	ADJ
ejpam-5015	430	3	linear	linear	ADJ
ejpam-5015	430	4	unbiased	unbiased	ADJ
ejpam-5015	430	5	estimators	estimator	NOUN
ejpam-5015	430	6	for	for	ADP
ejpam-5015	430	7	the	the	DET
ejpam-5015	430	8	simple	simple	ADJ
ejpam-5015	430	9	linear	linear	ADJ
ejpam-5015	430	10	regression	regression	NOUN
ejpam-5015	430	11	model	model	NOUN
ejpam-5015	430	12	using	use	VERB
ejpam-5015	430	13	double	double	ADJ
ejpam-5015	430	14	ranked	rank	VERB
ejpam-5015	430	15	set	set	ADJ
ejpam-5015	430	16	sampling	sample	VERB
ejpam-5015	430	17	schemes	scheme	NOUN
ejpam-5015	430	18	.	.	PUNCT
ejpam-5015	431	1	communications	communication	NOUN
ejpam-5015	431	2	in	in	ADP
ejpam-5015	431	3	statistics	statistic	NOUN
ejpam-5015	431	4	-	-	PUNCT
ejpam-5015	431	5	theory	theory	NOUN
ejpam-5015	431	6	and	and	CCONJ
ejpam-5015	431	7	methods	method	NOUN
ejpam-5015	431	8	,	,	PUNCT
ejpam-5015	431	9	45(12):3541–3561	45(12):3541–3561	PROPN
ejpam-5015	431	10	,	,	PUNCT
ejpam-5015	431	11	2016	2016	NUM
ejpam-5015	431	12	.	.	PUNCT
ejpam-5015	432	1	[	[	X
ejpam-5015	432	2	13	13	NUM
ejpam-5015	432	3	]	]	X
ejpam-5015	432	4	amal	amal	PROPN
ejpam-5015	432	5	s	s	PART
ejpam-5015	432	6	hassan	hassan	PROPN
ejpam-5015	432	7	.	.	PUNCT
ejpam-5015	433	1	maximum	maximum	ADJ
ejpam-5015	433	2	likelihood	likelihood	NOUN
ejpam-5015	433	3	and	and	CCONJ
ejpam-5015	433	4	bayes	bayes	NOUN
ejpam-5015	433	5	estimators	estimator	NOUN
ejpam-5015	433	6	of	of	ADP
ejpam-5015	433	7	the	the	DET
ejpam-5015	433	8	unknown	unknown	ADJ
ejpam-5015	433	9	parameters	parameter	NOUN
ejpam-5015	433	10	for	for	ADP
ejpam-5015	433	11	exponentiated	exponentiated	ADJ
ejpam-5015	433	12	exponential	exponential	ADJ
ejpam-5015	433	13	distribution	distribution	NOUN
ejpam-5015	433	14	using	use	VERB
ejpam-5015	433	15	ranked	rank	VERB
ejpam-5015	433	16	set	set	ADJ
ejpam-5015	433	17	sampling	sampling	NOUN
ejpam-5015	433	18	.	.	PUNCT
ejpam-5015	434	1	international	international	ADJ
ejpam-5015	434	2	journal	journal	NOUN
ejpam-5015	434	3	of	of	ADP
ejpam-5015	434	4	engineering	engineering	NOUN
ejpam-5015	434	5	research	research	NOUN
ejpam-5015	434	6	and	and	CCONJ
ejpam-5015	434	7	applications	application	NOUN
ejpam-5015	434	8	,	,	PUNCT
ejpam-5015	434	9	3(1):720–725	3(1):720–725	NUM
ejpam-5015	434	10	,	,	PUNCT
ejpam-5015	434	11	2013	2013	NUM
ejpam-5015	434	12	.	.	PUNCT
ejpam-5015	435	1	[	[	X
ejpam-5015	435	2	14	14	NUM
ejpam-5015	435	3	]	]	X
ejpam-5015	435	4	amal	amal	PROPN
ejpam-5015	435	5	helu	helu	PROPN
ejpam-5015	435	6	,	,	PUNCT
ejpam-5015	435	7	muhammad	muhammad	PROPN
ejpam-5015	435	8	abu	abu	PROPN
ejpam-5015	435	9	-	-	PUNCT
ejpam-5015	435	10	salih	salih	PROPN
ejpam-5015	435	11	,	,	PUNCT
ejpam-5015	435	12	and	and	CCONJ
ejpam-5015	435	13	osama	osama	PROPN
ejpam-5015	435	14	alkam	alkam	ADV
ejpam-5015	435	15	.	.	PUNCT
ejpam-5015	436	1	bayes	bayes	PROPN
ejpam-5015	436	2	estimation	estimation	NOUN
ejpam-5015	436	3	of	of	ADP
ejpam-5015	436	4	weibull	weibull	NOUN
ejpam-5015	436	5	distribution	distribution	NOUN
ejpam-5015	436	6	parameters	parameter	NOUN
ejpam-5015	436	7	using	use	VERB
ejpam-5015	436	8	ranked	rank	VERB
ejpam-5015	436	9	set	set	ADJ
ejpam-5015	436	10	sampling	sampling	NOUN
ejpam-5015	436	11	.	.	PUNCT
ejpam-5015	437	1	communications	communication	NOUN
ejpam-5015	437	2	in	in	ADP
ejpam-5015	437	3	statistics	statistic	NOUN
ejpam-5015	437	4	—	—	PUNCT
ejpam-5015	437	5	theory	theory	NOUN
ejpam-5015	437	6	and	and	CCONJ
ejpam-5015	437	7	methods	method	NOUN
ejpam-5015	437	8	,	,	PUNCT
ejpam-5015	437	9	39(14):2533–2551	39(14):2533–2551	NUM
ejpam-5015	437	10	,	,	PUNCT
ejpam-5015	437	11	2010	2010	NUM
ejpam-5015	437	12	.	.	PUNCT
ejpam-5015	438	1	[	[	X
ejpam-5015	438	2	15	15	NUM
ejpam-5015	438	3	]	]	X
ejpam-5015	438	4	kamel	kamel	PROPN
ejpam-5015	438	5	jebreen	jebreen	PROPN
ejpam-5015	438	6	.	.	PUNCT
ejpam-5015	439	1	modèles	modèle	VERB
ejpam-5015	439	2	graphiques	graphique	NOUN
ejpam-5015	439	3	pour	pour	X
ejpam-5015	439	4	la	la	PROPN
ejpam-5015	439	5	classification	classification	NOUN
ejpam-5015	439	6	et	et	NOUN
ejpam-5015	439	7	les	les	X
ejpam-5015	439	8	séries	séries	ADP
ejpam-5015	439	9	temporelles	temporelle	NOUN
ejpam-5015	439	10	.	.	PUNCT
ejpam-5015	440	1	aixmarseille	aixmarseille	NOUN
ejpam-5015	440	2	.	.	PUNCT
ejpam-5015	441	1	[	[	X
ejpam-5015	441	2	16	16	NUM
ejpam-5015	441	3	]	]	X
ejpam-5015	441	4	kamel	kamel	PROPN
ejpam-5015	441	5	jebreen	jebreen	PROPN
ejpam-5015	441	6	,	,	PUNCT
ejpam-5015	441	7	muhammad	muhammad	PROPN
ejpam-5015	441	8	aftab	aftab	PROPN
ejpam-5015	441	9	,	,	PUNCT
ejpam-5015	441	10	iftikhar	iftikhar	PROPN
ejpam-5015	441	11	ali	ali	PROPN
ejpam-5015	441	12	,	,	PUNCT
ejpam-5015	441	13	mohammad	mohammad	PROPN
ejpam-5015	441	14	sowaity	sowaity	NOUN
ejpam-5015	441	15	,	,	PUNCT
ejpam-5015	441	16	and	and	CCONJ
ejpam-5015	441	17	hassan	hassan	PROPN
ejpam-5015	441	18	kanj	kanj	PROPN
ejpam-5015	441	19	.	.	PUNCT
ejpam-5015	442	1	topological	topological	ADJ
ejpam-5015	442	2	aspects	aspect	NOUN
ejpam-5015	442	3	investigated	investigate	VERB
ejpam-5015	442	4	from	from	ADP
ejpam-5015	442	5	m	m	NOUN
ejpam-5015	442	6	-	-	ADJ
ejpam-5015	442	7	polynomial	polynomial	ADJ
ejpam-5015	442	8	of	of	ADP
ejpam-5015	442	9	-sheet	-sheet	NOUN
ejpam-5015	442	10	of	of	ADP
ejpam-5015	442	11	boron	boron	NOUN
ejpam-5015	442	12	clusters	cluster	NOUN
ejpam-5015	442	13	.	.	PUNCT
ejpam-5015	443	1	international	international	ADJ
ejpam-5015	443	2	journal	journal	PROPN
ejpam-5015	443	3	of	of	ADP
ejpam-5015	443	4	chemical	chemical	ADJ
ejpam-5015	443	5	and	and	CCONJ
ejpam-5015	443	6	biochemical	biochemical	ADJ
ejpam-5015	443	7	sciences	science	NOUN
ejpam-5015	443	8	,	,	PUNCT
ejpam-5015	443	9	24(4):469–477	24(4):469–477	NOUN
ejpam-5015	443	10	,	,	PUNCT
ejpam-5015	443	11	2023	2023	NUM
ejpam-5015	443	12	.	.	PUNCT
ejpam-5015	444	1	references	reference	NOUN
ejpam-5015	444	2	200	200	NUM
ejpam-5015	444	3	[	[	X
ejpam-5015	444	4	17	17	NUM
ejpam-5015	444	5	]	]	X
ejpam-5015	444	6	kamel	kamel	PROPN
ejpam-5015	444	7	jebreen	jebreen	PROPN
ejpam-5015	444	8	and	and	CCONJ
ejpam-5015	444	9	badih	badih	ADJ
ejpam-5015	444	10	ghattas	ghatta	NOUN
ejpam-5015	444	11	.	.	PUNCT
ejpam-5015	445	1	bayesian	bayesian	NOUN
ejpam-5015	445	2	network	network	NOUN
ejpam-5015	445	3	classification	classification	NOUN
ejpam-5015	445	4	:	:	PUNCT
ejpam-5015	445	5	application	application	NOUN
ejpam-5015	445	6	to	to	PART
ejpam-5015	445	7	epilepsy	epilepsy	NOUN
ejpam-5015	445	8	type	type	NOUN
ejpam-5015	445	9	prediction	prediction	NOUN
ejpam-5015	445	10	using	use	VERB
ejpam-5015	445	11	pet	pet	ADJ
ejpam-5015	445	12	scan	scan	PROPN
ejpam-5015	445	13	data	datum	NOUN
ejpam-5015	445	14	.	.	PUNCT
ejpam-5015	446	1	in	in	ADP
ejpam-5015	446	2	2016	2016	NUM
ejpam-5015	446	3	15th	15th	ADJ
ejpam-5015	446	4	ieee	ieee	PROPN
ejpam-5015	446	5	international	international	ADJ
ejpam-5015	446	6	conference	conference	NOUN
ejpam-5015	446	7	on	on	ADP
ejpam-5015	446	8	machine	machine	NOUN
ejpam-5015	446	9	learning	learning	NOUN
ejpam-5015	446	10	and	and	CCONJ
ejpam-5015	446	11	applications	application	NOUN
ejpam-5015	446	12	(	(	PUNCT
ejpam-5015	446	13	icmla	icmla	NOUN
ejpam-5015	446	14	)	)	PUNCT
ejpam-5015	446	15	,	,	PUNCT
ejpam-5015	446	16	pages	page	VERB
ejpam-5015	446	17	965–970	965–970	NUM
ejpam-5015	446	18	.	.	PUNCT
ejpam-5015	447	1	[	[	X
ejpam-5015	447	2	18	18	NUM
ejpam-5015	447	3	]	]	X
ejpam-5015	447	4	kamel	kamel	PROPN
ejpam-5015	447	5	jebreen	jebreen	PROPN
ejpam-5015	447	6	,	,	PUNCT
ejpam-5015	447	7	mohamad	mohamad	PROPN
ejpam-5015	447	8	motasem	motasem	PROPN
ejpam-5015	447	9	nawaf	nawaf	PROPN
ejpam-5015	447	10	,	,	PUNCT
ejpam-5015	447	11	amjad	amjad	PROPN
ejpam-5015	447	12	barham	barham	PROPN
ejpam-5015	447	13	,	,	PUNCT
ejpam-5015	447	14	and	and	CCONJ
ejpam-5015	447	15	badih	badih	ADJ
ejpam-5015	447	16	ghattas	ghatta	NOUN
ejpam-5015	447	17	.	.	PUNCT
ejpam-5015	448	1	inferring	infer	VERB
ejpam-5015	448	2	linear	linear	PROPN
ejpam-5015	448	3	and	and	CCONJ
ejpam-5015	448	4	nonlinear	nonlinear	ADJ
ejpam-5015	448	5	interaction	interaction	NOUN
ejpam-5015	448	6	networks	network	NOUN
ejpam-5015	448	7	using	use	VERB
ejpam-5015	448	8	neighborhood	neighborhood	NOUN
ejpam-5015	448	9	support	support	NOUN
ejpam-5015	448	10	vector	vector	NOUN
ejpam-5015	448	11	machines	machine	NOUN
ejpam-5015	448	12	.	.	PUNCT
ejpam-5015	449	1	in	in	ADP
ejpam-5015	449	2	2021	2021	NUM
ejpam-5015	449	3	international	international	ADJ
ejpam-5015	449	4	conference	conference	NOUN
ejpam-5015	449	5	on	on	ADP
ejpam-5015	449	6	engineering	engineering	NOUN
ejpam-5015	449	7	and	and	CCONJ
ejpam-5015	449	8	emerging	emerge	VERB
ejpam-5015	449	9	technologies	technology	NOUN
ejpam-5015	449	10	(	(	PUNCT
ejpam-5015	449	11	iceet	iceet	NOUN
ejpam-5015	449	12	)	)	PUNCT
ejpam-5015	449	13	,	,	PUNCT
ejpam-5015	449	14	pages	page	NOUN
ejpam-5015	449	15	1–6	1–6	NUM
ejpam-5015	449	16	.	.	PUNCT
ejpam-5015	450	1	issn	issn	PROPN
ejpam-5015	450	2	:	:	PUNCT
ejpam-5015	450	3	2409	2409	NUM
ejpam-5015	450	4	-	-	SYM
ejpam-5015	450	5	2983	2983	NUM
ejpam-5015	450	6	.	.	PUNCT
ejpam-5015	451	1	[	[	X
ejpam-5015	451	2	19	19	NUM
ejpam-5015	451	3	]	]	X
ejpam-5015	451	4	hassan	hassan	PROPN
ejpam-5015	451	5	kanj	kanj	PROPN
ejpam-5015	451	6	,	,	PUNCT
ejpam-5015	451	7	hifza	hifza	PROPN
ejpam-5015	451	8	iqbal	iqbal	PROPN
ejpam-5015	451	9	,	,	PUNCT
ejpam-5015	451	10	muhammad	muhammad	PROPN
ejpam-5015	451	11	haroon	haroon	PROPN
ejpam-5015	451	12	aftab	aftab	PROPN
ejpam-5015	451	13	,	,	PUNCT
ejpam-5015	451	14	hasnain	hasnain	PROPN
ejpam-5015	451	15	raza	raza	PROPN
ejpam-5015	451	16	,	,	PUNCT
ejpam-5015	451	17	kamel	kamel	PROPN
ejpam-5015	451	18	jebreen	jebreen	PROPN
ejpam-5015	451	19	,	,	PUNCT
ejpam-5015	451	20	and	and	CCONJ
ejpam-5015	451	21	mohammed	mohammed	PROPN
ejpam-5015	451	22	issa	issa	PROPN
ejpam-5015	451	23	sowaity	sowaity	NOUN
ejpam-5015	451	24	.	.	PUNCT
ejpam-5015	452	1	topological	topological	ADJ
ejpam-5015	452	2	characterization	characterization	NOUN
ejpam-5015	452	3	of	of	ADP
ejpam-5015	452	4	hexagonal	hexagonal	ADJ
ejpam-5015	452	5	network	network	NOUN
ejpam-5015	452	6	and	and	CCONJ
ejpam-5015	452	7	non	non	ADJ
ejpam-5015	452	8	-	-	ADJ
ejpam-5015	452	9	kekulean	kekulean	ADJ
ejpam-5015	452	10	benzenoid	benzenoid	NOUN
ejpam-5015	452	11	hydrocarbon	hydrocarbon	NOUN
ejpam-5015	452	12	.	.	PUNCT
ejpam-5015	453	1	16(4):2187–2197	16(4):2187–2197	X
ejpam-5015	453	2	.	.	PUNCT
ejpam-5015	454	1	[	[	X
ejpam-5015	454	2	20	20	NUM
ejpam-5015	454	3	]	]	X
ejpam-5015	454	4	jessica	jessica	PROPN
ejpam-5015	454	5	k	k	PROPN
ejpam-5015	454	6	kohlschmidt	kohlschmidt	PROPN
ejpam-5015	454	7	,	,	PUNCT
ejpam-5015	454	8	elizabeth	elizabeth	PROPN
ejpam-5015	454	9	a	a	DET
ejpam-5015	454	10	stasny	stasny	NOUN
ejpam-5015	454	11	,	,	PUNCT
ejpam-5015	454	12	and	and	CCONJ
ejpam-5015	454	13	douglas	douglas	PROPN
ejpam-5015	454	14	a	a	DET
ejpam-5015	454	15	wolfe	wolfe	PROPN
ejpam-5015	454	16	.	.	PROPN
ejpam-5015	454	17	ranked	rank	VERB
ejpam-5015	454	18	set	set	ADJ
ejpam-5015	454	19	sampling	sample	VERB
ejpam-5015	454	20	for	for	ADP
ejpam-5015	454	21	a	a	DET
ejpam-5015	454	22	population	population	NOUN
ejpam-5015	454	23	proportion	proportion	NOUN
ejpam-5015	454	24	:	:	PUNCT
ejpam-5015	454	25	allocation	allocation	NOUN
ejpam-5015	454	26	of	of	ADP
ejpam-5015	454	27	sample	sample	NOUN
ejpam-5015	454	28	units	unit	NOUN
ejpam-5015	454	29	to	to	ADP
ejpam-5015	454	30	each	each	DET
ejpam-5015	454	31	judgment	judgment	NOUN
ejpam-5015	454	32	order	order	NOUN
ejpam-5015	454	33	statistic	statistic	NOUN
ejpam-5015	454	34	.	.	PUNCT
ejpam-5015	455	1	pakistan	pakistan	PROPN
ejpam-5015	455	2	journal	journal	PROPN
ejpam-5015	455	3	of	of	ADP
ejpam-5015	455	4	statistics	statistic	NOUN
ejpam-5015	455	5	and	and	CCONJ
ejpam-5015	455	6	operation	operation	NOUN
ejpam-5015	455	7	research	research	NOUN
ejpam-5015	455	8	,	,	PUNCT
ejpam-5015	455	9	pages	page	NOUN
ejpam-5015	455	10	511–530	511–530	NUM
ejpam-5015	455	11	,	,	PUNCT
ejpam-5015	455	12	2012	2012	NUM
ejpam-5015	455	13	.	.	PUNCT
ejpam-5015	456	1	[	[	X
ejpam-5015	456	2	21	21	NUM
ejpam-5015	456	3	]	]	X
ejpam-5015	456	4	tao	tao	PROPN
ejpam-5015	456	5	li	li	PROPN
ejpam-5015	456	6	and	and	CCONJ
ejpam-5015	456	7	narayanaswamy	narayanaswamy	PROPN
ejpam-5015	456	8	balakrishnan	balakrishnan	PROPN
ejpam-5015	456	9	.	.	PUNCT
ejpam-5015	457	1	best	good	ADJ
ejpam-5015	457	2	linear	linear	ADJ
ejpam-5015	457	3	unbiased	unbiased	ADJ
ejpam-5015	457	4	estimators	estimator	NOUN
ejpam-5015	457	5	of	of	ADP
ejpam-5015	457	6	parameters	parameter	NOUN
ejpam-5015	457	7	of	of	ADP
ejpam-5015	457	8	a	a	DET
ejpam-5015	457	9	simple	simple	ADJ
ejpam-5015	457	10	linear	linear	NOUN
ejpam-5015	457	11	regression	regression	NOUN
ejpam-5015	457	12	model	model	NOUN
ejpam-5015	457	13	based	base	VERB
ejpam-5015	457	14	on	on	ADP
ejpam-5015	457	15	ordered	order	VERB
ejpam-5015	457	16	ranked	rank	VERB
ejpam-5015	457	17	set	set	VERB
ejpam-5015	457	18	samples	sample	NOUN
ejpam-5015	457	19	.	.	PUNCT
ejpam-5015	458	1	journal	journal	NOUN
ejpam-5015	458	2	of	of	ADP
ejpam-5015	458	3	statistical	statistical	ADJ
ejpam-5015	458	4	computation	computation	NOUN
ejpam-5015	458	5	and	and	CCONJ
ejpam-5015	458	6	simulation	simulation	NOUN
ejpam-5015	458	7	,	,	PUNCT
ejpam-5015	458	8	78(12):1267–1278	78(12):1267–1278	NUM
ejpam-5015	458	9	,	,	PUNCT
ejpam-5015	458	10	2008	2008	NUM
ejpam-5015	458	11	.	.	PUNCT
ejpam-5015	459	1	[	[	X
ejpam-5015	459	2	22	22	NUM
ejpam-5015	459	3	]	]	X
ejpam-5015	459	4	ga	ga	PROPN
ejpam-5015	459	5	mcintyre	mcintyre	PROPN
ejpam-5015	459	6	.	.	PUNCT
ejpam-5015	460	1	a	a	DET
ejpam-5015	460	2	method	method	NOUN
ejpam-5015	460	3	for	for	ADP
ejpam-5015	460	4	unbiased	unbiased	ADJ
ejpam-5015	460	5	selective	selective	ADJ
ejpam-5015	460	6	sampling	sampling	NOUN
ejpam-5015	460	7	,	,	PUNCT
ejpam-5015	460	8	using	use	VERB
ejpam-5015	460	9	ranked	rank	VERB
ejpam-5015	460	10	sets	set	NOUN
ejpam-5015	460	11	.	.	PUNCT
ejpam-5015	461	1	australian	australian	ADJ
ejpam-5015	461	2	journal	journal	NOUN
ejpam-5015	461	3	of	of	ADP
ejpam-5015	461	4	agricultural	agricultural	ADJ
ejpam-5015	461	5	research	research	NOUN
ejpam-5015	461	6	,	,	PUNCT
ejpam-5015	461	7	3(4):385–390	3(4):385–390	NUM
ejpam-5015	461	8	,	,	PUNCT
ejpam-5015	461	9	1952	1952	NUM
ejpam-5015	461	10	.	.	PUNCT
ejpam-5015	462	1	[	[	X
ejpam-5015	462	2	23	23	NUM
ejpam-5015	462	3	]	]	X
ejpam-5015	462	4	ha	ha	X
ejpam-5015	462	5	muttlak	muttlak	PROPN
ejpam-5015	462	6	.	.	PUNCT
ejpam-5015	463	1	median	median	PROPN
ejpam-5015	463	2	ranked	rank	VERB
ejpam-5015	463	3	set	set	ADJ
ejpam-5015	463	4	sampling	sample	VERB
ejpam-5015	463	5	with	with	ADP
ejpam-5015	463	6	concomitant	concomitant	ADJ
ejpam-5015	463	7	variables	variable	NOUN
ejpam-5015	463	8	and	and	CCONJ
ejpam-5015	463	9	a	a	DET
ejpam-5015	463	10	comparison	comparison	NOUN
ejpam-5015	463	11	with	with	ADP
ejpam-5015	463	12	ranked	rank	VERB
ejpam-5015	463	13	set	set	ADJ
ejpam-5015	463	14	sampling	sampling	NOUN
ejpam-5015	463	15	and	and	CCONJ
ejpam-5015	463	16	regression	regression	NOUN
ejpam-5015	463	17	estimators	estimator	NOUN
ejpam-5015	463	18	.	.	PUNCT
ejpam-5015	464	1	environmetrics	environmetric	NOUN
ejpam-5015	464	2	:	:	PUNCT
ejpam-5015	464	3	the	the	DET
ejpam-5015	464	4	official	official	ADJ
ejpam-5015	464	5	journal	journal	NOUN
ejpam-5015	464	6	of	of	ADP
ejpam-5015	464	7	the	the	DET
ejpam-5015	464	8	international	international	ADJ
ejpam-5015	464	9	environmetrics	environmetrics	PROPN
ejpam-5015	464	10	society	society	NOUN
ejpam-5015	464	11	,	,	PUNCT
ejpam-5015	464	12	9(3):255–267	9(3):255–267	NUM
ejpam-5015	464	13	,	,	PUNCT
ejpam-5015	464	14	1998	1998	NUM
ejpam-5015	464	15	.	.	PUNCT
ejpam-5015	465	1	[	[	X
ejpam-5015	465	2	24	24	NUM
ejpam-5015	465	3	]	]	X
ejpam-5015	465	4	martyn	martyn	PROPN
ejpam-5015	465	5	plummer	plummer	PROPN
ejpam-5015	465	6	et	et	PROPN
ejpam-5015	465	7	al	al	PROPN
ejpam-5015	465	8	.	.	PUNCT
ejpam-5015	466	1	jags	jag	NOUN
ejpam-5015	466	2	:	:	PUNCT
ejpam-5015	466	3	a	a	DET
ejpam-5015	466	4	program	program	NOUN
ejpam-5015	466	5	for	for	ADP
ejpam-5015	466	6	analysis	analysis	NOUN
ejpam-5015	466	7	of	of	ADP
ejpam-5015	466	8	bayesian	bayesian	NOUN
ejpam-5015	466	9	graphical	graphical	ADJ
ejpam-5015	466	10	models	model	NOUN
ejpam-5015	466	11	using	use	VERB
ejpam-5015	466	12	gibbs	gibbs	PROPN
ejpam-5015	466	13	sampling	sampling	NOUN
ejpam-5015	466	14	.	.	PUNCT
ejpam-5015	467	1	in	in	ADP
ejpam-5015	467	2	proceedings	proceeding	NOUN
ejpam-5015	467	3	of	of	ADP
ejpam-5015	467	4	the	the	DET
ejpam-5015	467	5	3rd	3rd	ADJ
ejpam-5015	467	6	international	international	ADJ
ejpam-5015	467	7	workshop	workshop	NOUN
ejpam-5015	467	8	on	on	ADP
ejpam-5015	467	9	distributed	distribute	VERB
ejpam-5015	467	10	statistical	statistical	ADJ
ejpam-5015	467	11	computing	computing	NOUN
ejpam-5015	467	12	,	,	PUNCT
ejpam-5015	467	13	volume	volume	NOUN
ejpam-5015	467	14	124	124	NUM
ejpam-5015	467	15	,	,	PUNCT
ejpam-5015	467	16	pages	page	NOUN
ejpam-5015	467	17	1–10	1–10	PROPN
ejpam-5015	467	18	.	.	PUNCT
ejpam-5015	468	1	vienna	vienna	PROPN
ejpam-5015	468	2	,	,	PUNCT
ejpam-5015	468	3	austria	austria	PROPN
ejpam-5015	468	4	.	.	PROPN
ejpam-5015	468	5	,	,	PUNCT
ejpam-5015	468	6	2003	2003	NUM
ejpam-5015	468	7	.	.	PUNCT
ejpam-5015	469	1	[	[	X
ejpam-5015	469	2	25	25	NUM
ejpam-5015	469	3	]	]	X
ejpam-5015	469	4	hakan	hakan	PROPN
ejpam-5015	469	5	savaş	savaş	PROPN
ejpam-5015	469	6	sazak	sazak	PROPN
ejpam-5015	469	7	and	and	CCONJ
ejpam-5015	469	8	melis	melis	PROPN
ejpam-5015	469	9	zeybek	zeybek	PROPN
ejpam-5015	469	10	.	.	PUNCT
ejpam-5015	470	1	the	the	DET
ejpam-5015	470	2	modified	modify	VERB
ejpam-5015	470	3	maximum	maximum	ADJ
ejpam-5015	470	4	likelihood	likelihood	NOUN
ejpam-5015	470	5	estimators	estimator	NOUN
ejpam-5015	470	6	for	for	ADP
ejpam-5015	470	7	the	the	DET
ejpam-5015	470	8	parameters	parameter	NOUN
ejpam-5015	470	9	of	of	ADP
ejpam-5015	470	10	the	the	DET
ejpam-5015	470	11	regression	regression	NOUN
ejpam-5015	470	12	model	model	NOUN
ejpam-5015	470	13	under	under	ADP
ejpam-5015	470	14	bivariate	bivariate	ADJ
ejpam-5015	470	15	median	median	NOUN
ejpam-5015	470	16	ranked	rank	VERB
ejpam-5015	470	17	set	set	ADJ
ejpam-5015	470	18	sampling	sampling	NOUN
ejpam-5015	470	19	.	.	PUNCT
ejpam-5015	471	1	computational	computational	ADJ
ejpam-5015	471	2	statistics	statistic	NOUN
ejpam-5015	471	3	,	,	PUNCT
ejpam-5015	471	4	37(3):1069–1109	37(3):1069–1109	NUM
ejpam-5015	471	5	,	,	PUNCT
ejpam-5015	471	6	2022	2022	NUM
ejpam-5015	471	7	.	.	PUNCT
ejpam-5015	472	1	[	[	X
ejpam-5015	472	2	26	26	NUM
ejpam-5015	472	3	]	]	X
ejpam-5015	472	4	arun	arun	PROPN
ejpam-5015	472	5	kumar	kumar	PROPN
ejpam-5015	472	6	sinha	sinha	PROPN
ejpam-5015	472	7	.	.	PROPN
ejpam-5015	472	8	ranked	rank	VERB
ejpam-5015	472	9	set	set	ADJ
ejpam-5015	472	10	sampling	sampling	NOUN
ejpam-5015	472	11	:	:	PUNCT
ejpam-5015	472	12	as	as	ADP
ejpam-5015	472	13	a	a	DET
ejpam-5015	472	14	cost	cost	NOUN
ejpam-5015	472	15	-	-	PUNCT
ejpam-5015	472	16	effective	effective	ADJ
ejpam-5015	472	17	and	and	CCONJ
ejpam-5015	472	18	more	more	ADV
ejpam-5015	472	19	efficient	efficient	ADJ
ejpam-5015	472	20	data	datum	NOUN
ejpam-5015	472	21	collection	collection	NOUN
ejpam-5015	472	22	method	method	NOUN
ejpam-5015	472	23	.	.	PUNCT
ejpam-5015	473	1	statistical	statistical	ADJ
ejpam-5015	473	2	journal	journal	NOUN
ejpam-5015	473	3	of	of	ADP
ejpam-5015	473	4	the	the	DET
ejpam-5015	473	5	iaos	iaos	NOUN
ejpam-5015	473	6	,	,	PUNCT
ejpam-5015	473	7	32(4):607–611	32(4):607–611	PROPN
ejpam-5015	473	8	,	,	PUNCT
ejpam-5015	473	9	2016	2016	NUM
ejpam-5015	473	10	.	.	PUNCT
ejpam-5015	474	1	[	[	X
ejpam-5015	474	2	27	27	NUM
ejpam-5015	474	3	]	]	X
ejpam-5015	474	4	douglas	douglas	PROPN
ejpam-5015	474	5	a	a	DET
ejpam-5015	474	6	wolfe	wolfe	PROPN
ejpam-5015	474	7	.	.	PROPN
ejpam-5015	475	1	ranked	rank	VERB
ejpam-5015	475	2	set	set	ADJ
ejpam-5015	475	3	sampling	sampling	NOUN
ejpam-5015	475	4	:	:	PUNCT
ejpam-5015	475	5	its	its	PRON
ejpam-5015	475	6	relevance	relevance	NOUN
ejpam-5015	475	7	and	and	CCONJ
ejpam-5015	475	8	impact	impact	NOUN
ejpam-5015	475	9	on	on	ADP
ejpam-5015	475	10	statistical	statistical	ADJ
ejpam-5015	475	11	inference	inference	NOUN
ejpam-5015	475	12	.	.	PUNCT
ejpam-5015	476	1	international	international	ADJ
ejpam-5015	476	2	scholarly	scholarly	ADJ
ejpam-5015	476	3	research	research	NOUN
ejpam-5015	476	4	notices	notice	NOUN
ejpam-5015	476	5	,	,	PUNCT
ejpam-5015	476	6	2012	2012	NUM
ejpam-5015	476	7	,	,	PUNCT
ejpam-5015	476	8	2012	2012	NUM
ejpam-5015	476	9	.	.	PUNCT
ejpam-5015	477	1	[	[	X
ejpam-5015	477	2	28	28	NUM
ejpam-5015	477	3	]	]	X
ejpam-5015	477	4	dong	dong	PROPN
ejpam-5015	477	5	-	-	PUNCT
ejpam-5015	477	6	sen	sen	PROPN
ejpam-5015	477	7	yao	yao	PROPN
ejpam-5015	477	8	,	,	PUNCT
ejpam-5015	477	9	wang	wang	PROPN
ejpam-5015	477	10	-	-	PUNCT
ejpam-5015	477	11	xue	xue	PROPN
ejpam-5015	477	12	chen	chen	PROPN
ejpam-5015	477	13	,	,	PUNCT
ejpam-5015	477	14	and	and	CCONJ
ejpam-5015	477	15	chun	chun	PROPN
ejpam-5015	477	16	-	-	PUNCT
ejpam-5015	477	17	xian	xian	PROPN
ejpam-5015	477	18	long	long	ADJ
ejpam-5015	477	19	.	.	PUNCT
ejpam-5015	478	1	parametric	parametric	ADJ
ejpam-5015	478	2	estimation	estimation	NOUN
ejpam-5015	478	3	for	for	ADP
ejpam-5015	478	4	the	the	DET
ejpam-5015	478	5	simple	simple	ADJ
ejpam-5015	478	6	linear	linear	ADJ
ejpam-5015	478	7	regression	regression	NOUN
ejpam-5015	478	8	model	model	NOUN
ejpam-5015	478	9	under	under	ADP
ejpam-5015	478	10	moving	move	VERB
ejpam-5015	478	11	extremes	extreme	NOUN
ejpam-5015	478	12	ranked	rank	VERB
ejpam-5015	478	13	set	set	ADJ
ejpam-5015	478	14	sampling	sample	VERB
ejpam-5015	478	15	design	design	NOUN
ejpam-5015	478	16	.	.	PUNCT
ejpam-5015	479	1	applied	apply	VERB
ejpam-5015	479	2	mathematics	mathematic	NOUN
ejpam-5015	479	3	-	-	PUNCT
ejpam-5015	479	4	a	a	DET
ejpam-5015	479	5	journal	journal	NOUN
ejpam-5015	479	6	of	of	ADP
ejpam-5015	479	7	chinese	chinese	ADJ
ejpam-5015	479	8	universities	university	NOUN
ejpam-5015	479	9	,	,	PUNCT
ejpam-5015	479	10	36(2):269–277	36(2):269–277	PROPN
ejpam-5015	479	11	,	,	PUNCT
ejpam-5015	479	12	2021	2021	NUM
ejpam-5015	479	13	.	.	PUNCT