id	sid	tid	token	lemma	pos
iajs-2800	1	1	ibn	ibn	PROPN
iajs-2800	1	2	al	al	PROPN
iajs-2800	1	3	-	-	PUNCT
iajs-2800	1	4	haitham	haitham	PROPN
iajs-2800	1	5	jour	jour	X
iajs-2800	1	6	.	.	PROPN
iajs-2800	1	7	for	for	ADP
iajs-2800	1	8	pure	pure	ADJ
iajs-2800	1	9	&	&	CCONJ
iajs-2800	1	10	appl	appl	PROPN
iajs-2800	1	11	.	.	PUNCT
iajs-2800	2	1	sci	sci	PROPN
iajs-2800	2	2	.	.	PROPN
iajs-2800	3	1	53	53	NUM
iajs-2800	3	2	(	(	PUNCT
iajs-2800	3	3	1)2022	1)2022	NOUN
iajs-2800	3	4	60	60	NUM
iajs-2800	3	5	this	this	DET
iajs-2800	3	6	work	work	NOUN
iajs-2800	3	7	is	be	AUX
iajs-2800	3	8	licensed	license	VERB
iajs-2800	3	9	under	under	ADP
iajs-2800	3	10	a	a	DET
iajs-2800	3	11	creative	creative	ADJ
iajs-2800	3	12	commons	common	NOUN
iajs-2800	3	13	attribution	attribution	NOUN
iajs-2800	3	14	4.0	4.0	NUM
iajs-2800	3	15	international	international	ADJ
iajs-2800	3	16	license	license	NOUN
iajs-2800	3	17	.	.	PUNCT
iajs-2800	4	1	posterior	posterior	ADJ
iajs-2800	4	2	estimates	estimate	NOUN
iajs-2800	4	3	for	for	ADP
iajs-2800	4	4	the	the	DET
iajs-2800	4	5	parameter	parameter	NOUN
iajs-2800	4	6	of	of	ADP
iajs-2800	4	7	the	the	DET
iajs-2800	4	8	poisson	poisson	NOUN
iajs-2800	4	9	distribution	distribution	NOUN
iajs-2800	4	10	by	by	ADP
iajs-2800	4	11	using	use	VERB
iajs-2800	4	12	two	two	NUM
iajs-2800	4	13	different	different	ADJ
iajs-2800	4	14	loss	loss	NOUN
iajs-2800	4	15	functions	function	NOUN
iajs-2800	4	16	jinan	jinan	PROPN
iajs-2800	4	17	a.	a.	PROPN
iajs-2800	4	18	naser	naser	PROPN
iajs-2800	4	19	al	al	PROPN
iajs-2800	4	20	-	-	PUNCT
iajs-2800	4	21	obedy	obedy	ADJ
iajs-2800	4	22	drjanan1964@gmail.com	drjanan1964@gmail.com	PROPN
iajs-2800	4	23	technical	technical	PROPN
iajs-2800	4	24	college	college	PROPN
iajs-2800	4	25	of	of	ADP
iajs-2800	4	26	management	management	NOUN
iajs-2800	4	27	-	-	PUNCT
iajs-2800	4	28	baghdad	baghdad	PROPN
iajs-2800	4	29	,	,	PUNCT
iajs-2800	4	30	baghdad	baghdad	PROPN
iajs-2800	4	31	,	,	PUNCT
iajs-2800	4	32	iraq	iraq	PROPN
iajs-2800	4	33	abstract	abstract	NOUN
iajs-2800	4	34	in	in	ADP
iajs-2800	4	35	this	this	DET
iajs-2800	4	36	paper	paper	NOUN
iajs-2800	4	37	,	,	PUNCT
iajs-2800	4	38	bayes	bayes	PROPN
iajs-2800	4	39	estimators	estimator	NOUN
iajs-2800	4	40	of	of	ADP
iajs-2800	4	41	poisson	poisson	NOUN
iajs-2800	4	42	distribution	distribution	NOUN
iajs-2800	4	43	have	have	AUX
iajs-2800	4	44	been	be	AUX
iajs-2800	4	45	derived	derive	VERB
iajs-2800	4	46	by	by	ADP
iajs-2800	4	47	using	use	VERB
iajs-2800	4	48	two	two	NUM
iajs-2800	4	49	loss	loss	NOUN
iajs-2800	4	50	functions	function	NOUN
iajs-2800	4	51	:	:	PUNCT
iajs-2800	4	52	the	the	DET
iajs-2800	4	53	squared	square	VERB
iajs-2800	4	54	error	error	NOUN
iajs-2800	4	55	loss	loss	NOUN
iajs-2800	4	56	function	function	NOUN
iajs-2800	4	57	and	and	CCONJ
iajs-2800	4	58	the	the	DET
iajs-2800	4	59	proposed	propose	VERB
iajs-2800	4	60	exponential	exponential	ADJ
iajs-2800	4	61	loss	loss	NOUN
iajs-2800	4	62	function	function	NOUN
iajs-2800	4	63	in	in	ADP
iajs-2800	4	64	this	this	DET
iajs-2800	4	65	study	study	NOUN
iajs-2800	4	66	,	,	PUNCT
iajs-2800	4	67	based	base	VERB
iajs-2800	4	68	on	on	ADP
iajs-2800	4	69	different	different	ADJ
iajs-2800	4	70	priors	prior	NOUN
iajs-2800	4	71	classified	classify	VERB
iajs-2800	4	72	as	as	ADP
iajs-2800	4	73	the	the	DET
iajs-2800	4	74	two	two	NUM
iajs-2800	4	75	different	different	ADJ
iajs-2800	4	76	informative	informative	ADJ
iajs-2800	4	77	prior	prior	ADJ
iajs-2800	4	78	distributions	distribution	NOUN
iajs-2800	4	79	represented	represent	VERB
iajs-2800	4	80	by	by	ADP
iajs-2800	4	81	erlang	erlang	PROPN
iajs-2800	4	82	and	and	CCONJ
iajs-2800	4	83	inverse	inverse	NOUN
iajs-2800	4	84	levy	levy	NOUN
iajs-2800	4	85	prior	prior	ADJ
iajs-2800	4	86	distributions	distribution	NOUN
iajs-2800	4	87	and	and	CCONJ
iajs-2800	4	88	non	non	ADJ
iajs-2800	4	89	-	-	ADJ
iajs-2800	4	90	informative	informative	ADJ
iajs-2800	4	91	prior	prior	ADV
iajs-2800	4	92	for	for	ADP
iajs-2800	4	93	the	the	DET
iajs-2800	4	94	shape	shape	NOUN
iajs-2800	4	95	parameter	parameter	NOUN
iajs-2800	4	96	of	of	ADP
iajs-2800	4	97	poisson	poisson	NOUN
iajs-2800	4	98	distribution	distribution	NOUN
iajs-2800	4	99	.	.	PUNCT
iajs-2800	5	1	the	the	DET
iajs-2800	5	2	maximum	maximum	ADJ
iajs-2800	5	3	likelihood	likelihood	NOUN
iajs-2800	5	4	estimator	estimator	NOUN
iajs-2800	5	5	(	(	PUNCT
iajs-2800	5	6	mle	mle	PROPN
iajs-2800	5	7	)	)	PUNCT
iajs-2800	5	8	of	of	ADP
iajs-2800	5	9	the	the	DET
iajs-2800	5	10	poisson	poisson	NOUN
iajs-2800	5	11	distribution	distribution	NOUN
iajs-2800	5	12	has	have	AUX
iajs-2800	5	13	also	also	ADV
iajs-2800	5	14	been	be	AUX
iajs-2800	5	15	derived	derive	VERB
iajs-2800	5	16	.	.	PUNCT
iajs-2800	6	1	a	a	DET
iajs-2800	6	2	simulation	simulation	NOUN
iajs-2800	6	3	study	study	NOUN
iajs-2800	6	4	has	have	AUX
iajs-2800	6	5	been	be	AUX
iajs-2800	6	6	fulfilled	fulfil	VERB
iajs-2800	6	7	to	to	PART
iajs-2800	6	8	compare	compare	VERB
iajs-2800	6	9	the	the	DET
iajs-2800	6	10	accuracy	accuracy	NOUN
iajs-2800	6	11	of	of	ADP
iajs-2800	6	12	the	the	DET
iajs-2800	6	13	bayes	bayes	NOUN
iajs-2800	6	14	estimates	estimate	VERB
iajs-2800	6	15	with	with	ADP
iajs-2800	6	16	the	the	DET
iajs-2800	6	17	corresponding	corresponding	ADJ
iajs-2800	6	18	maximum	maximum	ADJ
iajs-2800	6	19	likelihood	likelihood	NOUN
iajs-2800	6	20	estimate	estimate	NOUN
iajs-2800	6	21	(	(	PUNCT
iajs-2800	6	22	mle	mle	PROPN
iajs-2800	6	23	)	)	PUNCT
iajs-2800	6	24	of	of	ADP
iajs-2800	6	25	the	the	DET
iajs-2800	6	26	poisson	poisson	NOUN
iajs-2800	6	27	distribution	distribution	NOUN
iajs-2800	6	28	based	base	VERB
iajs-2800	6	29	on	on	ADP
iajs-2800	6	30	the	the	DET
iajs-2800	6	31	root	root	NOUN
iajs-2800	6	32	mean	mean	VERB
iajs-2800	6	33	squared	square	VERB
iajs-2800	6	34	error	error	NOUN
iajs-2800	6	35	(	(	PUNCT
iajs-2800	6	36	rmse	rmse	NOUN
iajs-2800	6	37	)	)	PUNCT
iajs-2800	6	38	for	for	ADP
iajs-2800	6	39	different	different	ADJ
iajs-2800	6	40	cases	case	NOUN
iajs-2800	6	41	of	of	ADP
iajs-2800	6	42	the	the	DET
iajs-2800	6	43	parameter	parameter	NOUN
iajs-2800	6	44	of	of	ADP
iajs-2800	6	45	the	the	DET
iajs-2800	6	46	poisson	poisson	NOUN
iajs-2800	6	47	distribution	distribution	NOUN
iajs-2800	6	48	and	and	CCONJ
iajs-2800	6	49	different	different	ADJ
iajs-2800	6	50	sample	sample	NOUN
iajs-2800	6	51	sizes	size	NOUN
iajs-2800	6	52	.	.	PUNCT
iajs-2800	7	1	keywords	keyword	NOUN
iajs-2800	7	2	:	:	PUNCT
iajs-2800	7	3	the	the	DET
iajs-2800	7	4	poisson	poisson	NOUN
iajs-2800	7	5	distribution	distribution	NOUN
iajs-2800	7	6	,	,	PUNCT
iajs-2800	7	7	mle	mle	PROPN
iajs-2800	7	8	,	,	PUNCT
iajs-2800	7	9	bayes	bayes	PROPN
iajs-2800	7	10	estimation	estimation	NOUN
iajs-2800	7	11	,	,	PUNCT
iajs-2800	7	12	self	self	NOUN
iajs-2800	7	13	,	,	PUNCT
iajs-2800	7	14	the	the	DET
iajs-2800	7	15	proposed	propose	VERB
iajs-2800	7	16	loss	loss	NOUN
iajs-2800	7	17	function	function	NOUN
iajs-2800	7	18	.	.	PUNCT
iajs-2800	8	1	1	1	X
iajs-2800	8	2	.	.	X
iajs-2800	8	3	introduction	introduction	NOUN
iajs-2800	8	4	the	the	DET
iajs-2800	8	5	poisson	poisson	NOUN
iajs-2800	8	6	distribution	distribution	NOUN
iajs-2800	8	7	is	be	AUX
iajs-2800	8	8	a	a	DET
iajs-2800	8	9	discrete	discrete	ADJ
iajs-2800	8	10	probability	probability	NOUN
iajs-2800	8	11	distribution	distribution	NOUN
iajs-2800	8	12	for	for	ADP
iajs-2800	8	13	the	the	DET
iajs-2800	8	14	counts	count	NOUN
iajs-2800	8	15	of	of	ADP
iajs-2800	8	16	events	event	NOUN
iajs-2800	8	17	that	that	PRON
iajs-2800	8	18	occur	occur	VERB
iajs-2800	8	19	randomly	randomly	ADV
iajs-2800	8	20	in	in	ADP
iajs-2800	8	21	a	a	DET
iajs-2800	8	22	given	give	VERB
iajs-2800	8	23	interval	interval	NOUN
iajs-2800	8	24	of	of	ADP
iajs-2800	8	25	time	time	NOUN
iajs-2800	8	26	(	(	PUNCT
iajs-2800	8	27	or	or	CCONJ
iajs-2800	8	28	space	space	NOUN
iajs-2800	8	29	)	)	PUNCT
iajs-2800	8	30	.	.	PUNCT
iajs-2800	9	1	also	also	ADV
iajs-2800	9	2	,	,	PUNCT
iajs-2800	9	3	it	it	PRON
iajs-2800	9	4	is	be	AUX
iajs-2800	9	5	an	an	DET
iajs-2800	9	6	appropriate	appropriate	ADJ
iajs-2800	9	7	model	model	NOUN
iajs-2800	9	8	for	for	ADP
iajs-2800	9	9	;	;	PUNCT
iajs-2800	9	10	the	the	DET
iajs-2800	9	11	number	number	NOUN
iajs-2800	9	12	of	of	ADP
iajs-2800	9	13	phone	phone	NOUN
iajs-2800	9	14	calls	call	NOUN
iajs-2800	9	15	received	receive	VERB
iajs-2800	9	16	by	by	ADP
iajs-2800	9	17	a	a	DET
iajs-2800	9	18	telephone	telephone	NOUN
iajs-2800	9	19	operator	operator	NOUN
iajs-2800	9	20	in	in	ADP
iajs-2800	9	21	a	a	DET
iajs-2800	9	22	ten	ten	NUM
iajs-2800	9	23	minutes	minute	NOUN
iajs-2800	9	24	the	the	DET
iajs-2800	9	25	number	number	NOUN
iajs-2800	9	26	of	of	ADP
iajs-2800	9	27	flaws	flaw	NOUN
iajs-2800	9	28	in	in	ADP
iajs-2800	9	29	a	a	DET
iajs-2800	9	30	bolt	bolt	NOUN
iajs-2800	9	31	of	of	ADP
iajs-2800	9	32	fabric	fabric	NOUN
iajs-2800	9	33	,	,	PUNCT
iajs-2800	9	34	the	the	DET
iajs-2800	9	35	number	number	NOUN
iajs-2800	9	36	of	of	ADP
iajs-2800	9	37	spelling	spelling	NOUN
iajs-2800	9	38	errors	error	NOUN
iajs-2800	9	39	on	on	ADP
iajs-2800	9	40	each	each	DET
iajs-2800	9	41	page	page	NOUN
iajs-2800	9	42	of	of	ADP
iajs-2800	9	43	a	a	DET
iajs-2800	9	44	document	document	NOUN
iajs-2800	9	45	.	.	PUNCT
iajs-2800	10	1	the	the	DET
iajs-2800	10	2	poisson	poisson	NOUN
iajs-2800	10	3	distribution	distribution	NOUN
iajs-2800	10	4	has	have	VERB
iajs-2800	10	5	widespread	widespread	ADJ
iajs-2800	10	6	applications	application	NOUN
iajs-2800	10	7	in	in	ADP
iajs-2800	10	8	almost	almost	ADV
iajs-2800	10	9	every	every	PRON
iajs-2800	10	10	science	science	NOUN
iajs-2800	10	11	,	,	PUNCT
iajs-2800	10	12	engineering	engineering	NOUN
iajs-2800	10	13	and	and	CCONJ
iajs-2800	10	14	medicine	medicine	NOUN
iajs-2800	10	15	.	.	PUNCT
iajs-2800	11	1	so	so	ADV
iajs-2800	11	2	,	,	PUNCT
iajs-2800	11	3	it	it	PRON
iajs-2800	11	4	is	be	AUX
iajs-2800	11	5	important	important	ADJ
iajs-2800	11	6	to	to	PART
iajs-2800	11	7	study	study	VERB
iajs-2800	11	8	different	different	ADJ
iajs-2800	11	9	estimation	estimation	NOUN
iajs-2800	11	10	methods	method	NOUN
iajs-2800	11	11	for	for	ADP
iajs-2800	11	12	the	the	DET
iajs-2800	11	13	poisson	poisson	NOUN
iajs-2800	11	14	distribution	distribution	NOUN
iajs-2800	11	15	.	.	PUNCT
iajs-2800	12	1	many	many	ADJ
iajs-2800	12	2	authors	author	NOUN
iajs-2800	12	3	investigate	investigate	VERB
iajs-2800	12	4	the	the	DET
iajs-2800	12	5	effects	effect	NOUN
iajs-2800	12	6	on	on	ADP
iajs-2800	12	7	bayes	baye	NOUN
iajs-2800	12	8	’	'	PUNCT
iajs-2800	12	9	estimators	estimator	NOUN
iajs-2800	12	10	of	of	ADP
iajs-2800	12	11	the	the	DET
iajs-2800	12	12	poisson	poisson	NOUN
iajs-2800	12	13	distribution	distribution	NOUN
iajs-2800	12	14	based	base	VERB
iajs-2800	12	15	on	on	ADP
iajs-2800	12	16	different	different	ADJ
iajs-2800	12	17	loss	loss	NOUN
iajs-2800	12	18	functions	function	NOUN
iajs-2800	12	19	,	,	PUNCT
iajs-2800	12	20	and	and	CCONJ
iajs-2800	12	21	the	the	DET
iajs-2800	12	22	prior	prior	ADJ
iajs-2800	12	23	distributions	distribution	NOUN
iajs-2800	12	24	represented	represent	VERB
iajs-2800	12	25	by	by	ADP
iajs-2800	12	26	informative	informative	ADJ
iajs-2800	12	27	prior	prior	ADV
iajs-2800	12	28	and	and	CCONJ
iajs-2800	12	29	noninformative	noninformative	ADJ
iajs-2800	12	30	prior	prior	ADV
iajs-2800	12	31	.	.	PUNCT
iajs-2800	13	1	we	we	PRON
iajs-2800	13	2	mention	mention	VERB
iajs-2800	13	3	some	some	PRON
iajs-2800	13	4	of	of	ADP
iajs-2800	13	5	them	they	PRON
iajs-2800	13	6	as	as	SCONJ
iajs-2800	13	7	follows	follow	VERB
iajs-2800	13	8	:	:	PUNCT
iajs-2800	14	1	[	[	X
iajs-2800	14	2	1	1	X
iajs-2800	14	3	]	]	PUNCT
iajs-2800	14	4	discussed	discuss	VERB
iajs-2800	14	5	bayes	bayes	NOUN
iajs-2800	14	6	estimators	estimator	NOUN
iajs-2800	14	7	for	for	ADP
iajs-2800	14	8	the	the	DET
iajs-2800	14	9	binomial	binomial	ADJ
iajs-2800	14	10	and	and	CCONJ
iajs-2800	14	11	poisson	poisson	NOUN
iajs-2800	14	12	distribution	distribution	NOUN
iajs-2800	14	13	,	,	PUNCT
iajs-2800	14	14	based	base	VERB
iajs-2800	14	15	on	on	ADP
iajs-2800	14	16	informative	informative	ADJ
iajs-2800	14	17	and	and	CCONJ
iajs-2800	14	18	non	non	ADJ
iajs-2800	14	19	-	-	ADJ
iajs-2800	14	20	informative	informative	ADJ
iajs-2800	14	21	priors	prior	NOUN
iajs-2800	14	22	.	.	PUNCT
iajs-2800	15	1	he	he	PRON
iajs-2800	15	2	concludes	conclude	VERB
iajs-2800	15	3	that	that	SCONJ
iajs-2800	15	4	using	use	VERB
iajs-2800	15	5	non	non	ADJ
iajs-2800	15	6	-	-	ADJ
iajs-2800	15	7	informative	informative	ADJ
iajs-2800	15	8	priors	prior	NOUN
iajs-2800	15	9	results	result	VERB
iajs-2800	15	10	in	in	ADP
iajs-2800	15	11	equal	equal	ADJ
iajs-2800	15	12	tails	tail	NOUN
iajs-2800	15	13	posterior	posterior	ADJ
iajs-2800	15	14	probability	probability	NOUN
iajs-2800	15	15	intervals	interval	NOUN
iajs-2800	15	16	in	in	ADP
iajs-2800	15	17	the	the	DET
iajs-2800	15	18	corresponding	corresponding	ADJ
iajs-2800	15	19	frequentist	frequentist	NOUN
iajs-2800	15	20	confidence	confidence	NOUN
iajs-2800	15	21	intervals	interval	NOUN
iajs-2800	15	22	.	.	PUNCT
iajs-2800	16	1	also	also	ADV
iajs-2800	16	2	,	,	PUNCT
iajs-2800	16	3	he	he	PRON
iajs-2800	16	4	pointed	point	VERB
iajs-2800	16	5	out	out	ADP
iajs-2800	16	6	that	that	SCONJ
iajs-2800	16	7	the	the	DET
iajs-2800	16	8	posterior	posterior	ADJ
iajs-2800	16	9	ibn	ibn	PROPN
iajs-2800	16	10	al	al	PROPN
iajs-2800	16	11	haitham	haitham	PROPN
iajs-2800	16	12	journal	journal	PROPN
iajs-2800	16	13	for	for	ADP
iajs-2800	16	14	pure	pure	ADJ
iajs-2800	16	15	and	and	CCONJ
iajs-2800	16	16	applied	apply	VERB
iajs-2800	16	17	science	science	NOUN
iajs-2800	16	18	journal	journal	PROPN
iajs-2800	16	19	homepage	homepage	NOUN
iajs-2800	16	20	:	:	PUNCT
iajs-2800	16	21	http://jih.uobaghdad.edu.iq/index.php/j/index	http://jih.uobaghdad.edu.iq/index.php/j/index	NOUN
iajs-2800	16	22	doi	doi	NOUN
iajs-2800	16	23	:	:	PUNCT
iajs-2800	16	24	10.30526/35.1.2800	10.30526/35.1.2800	NOUN
iajs-2800	16	25	article	article	NOUN
iajs-2800	16	26	history	history	NOUN
iajs-2800	16	27	:	:	PUNCT
iajs-2800	16	28	received	receive	VERB
iajs-2800	16	29	7,september	7,september	NUM
iajs-2800	16	30	,	,	PUNCT
iajs-2800	16	31	2021	2021	NUM
iajs-2800	16	32	,	,	PUNCT
iajs-2800	16	33	accepted	accept	VERB
iajs-2800	16	34	5	5	NUM
iajs-2800	16	35	,	,	PUNCT
iajs-2800	16	36	december	december	PROPN
iajs-2800	16	37	,	,	PUNCT
iajs-2800	16	38	2021	2021	NUM
iajs-2800	16	39	,	,	PUNCT
iajs-2800	16	40	published	publish	VERB
iajs-2800	16	41	in	in	ADP
iajs-2800	16	42	january	january	PROPN
iajs-2800	16	43	2022	2022	NUM
iajs-2800	16	44	.	.	PUNCT
iajs-2800	17	1	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
iajs-2800	17	2	mailto:drjanan1964@gmail.com	mailto:drjanan1964@gmail.com	PROPN
iajs-2800	17	3	ibn	ibn	PROPN
iajs-2800	17	4	al	al	PROPN
iajs-2800	17	5	-	-	PUNCT
iajs-2800	17	6	haitham	haitham	PROPN
iajs-2800	17	7	jour	jour	X
iajs-2800	17	8	.	.	PROPN
iajs-2800	17	9	for	for	ADP
iajs-2800	17	10	pure	pure	ADJ
iajs-2800	17	11	&	&	CCONJ
iajs-2800	17	12	appl	appl	PROPN
iajs-2800	17	13	.	.	PUNCT
iajs-2800	18	1	sci	sci	PROPN
iajs-2800	18	2	.	.	PROPN
iajs-2800	19	1	53	53	NUM
iajs-2800	19	2	(	(	PUNCT
iajs-2800	19	3	1)2022	1)2022	PROPN
iajs-2800	19	4	61	61	NUM
iajs-2800	19	5	mean	mean	NOUN
iajs-2800	19	6	is	be	AUX
iajs-2800	19	7	larger	large	ADJ
iajs-2800	19	8	than	than	ADP
iajs-2800	19	9	the	the	DET
iajs-2800	19	10	mle	mle	NOUN
iajs-2800	19	11	,	,	PUNCT
iajs-2800	19	12	which	which	PRON
iajs-2800	19	13	explains	explain	VERB
iajs-2800	19	14	why	why	SCONJ
iajs-2800	19	15	the	the	DET
iajs-2800	19	16	bayesian	bayesian	NOUN
iajs-2800	19	17	interval	interval	NOUN
iajs-2800	19	18	is	be	AUX
iajs-2800	19	19	slightly	slightly	ADV
iajs-2800	19	20	shifted	shift	VERB
iajs-2800	19	21	to	to	ADP
iajs-2800	19	22	the	the	DET
iajs-2800	19	23	right	right	NOUN
iajs-2800	19	24	compared	compare	VERB
iajs-2800	19	25	to	to	ADP
iajs-2800	19	26	the	the	DET
iajs-2800	19	27	frequentist	frequentist	NOUN
iajs-2800	19	28	interval	interval	NOUN
iajs-2800	19	29	.	.	PUNCT
iajs-2800	20	1	[	[	X
iajs-2800	20	2	2	2	X
iajs-2800	20	3	]	]	PUNCT
iajs-2800	20	4	examined	examine	VERB
iajs-2800	20	5	bayes	bayes	PROPN
iajs-2800	20	6	estimators	estimator	NOUN
iajs-2800	20	7	of	of	ADP
iajs-2800	20	8	unknown	unknown	ADJ
iajs-2800	20	9	parameters	parameter	NOUN
iajs-2800	20	10	of	of	ADP
iajs-2800	20	11	the	the	DET
iajs-2800	20	12	poisson	poisson	NOUN
iajs-2800	20	13	distribution	distribution	NOUN
iajs-2800	20	14	under	under	ADP
iajs-2800	20	15	different	different	ADJ
iajs-2800	20	16	priors	prior	NOUN
iajs-2800	20	17	.	.	PUNCT
iajs-2800	21	1	they	they	PRON
iajs-2800	21	2	have	have	AUX
iajs-2800	21	3	derived	derive	VERB
iajs-2800	21	4	the	the	DET
iajs-2800	21	5	posterior	posterior	ADJ
iajs-2800	21	6	distributions	distribution	NOUN
iajs-2800	21	7	for	for	ADP
iajs-2800	21	8	the	the	DET
iajs-2800	21	9	unknown	unknown	ADJ
iajs-2800	21	10	parameter	parameter	NOUN
iajs-2800	21	11	of	of	ADP
iajs-2800	21	12	the	the	DET
iajs-2800	21	13	poisson	poisson	NOUN
iajs-2800	21	14	distribution	distribution	NOUN
iajs-2800	21	15	using	use	VERB
iajs-2800	21	16	single	single	ADJ
iajs-2800	21	17	priors	prior	NOUN
iajs-2800	21	18	such	such	ADJ
iajs-2800	21	19	as	as	ADP
iajs-2800	21	20	uniform	uniform	NOUN
iajs-2800	21	21	,	,	PUNCT
iajs-2800	21	22	jeffrey	jeffrey	PROPN
iajs-2800	21	23	’s	’s	PROPN
iajs-2800	21	24	,	,	PUNCT
iajs-2800	21	25	gamma	gamma	NOUN
iajs-2800	21	26	distribution	distribution	NOUN
iajs-2800	21	27	,	,	PUNCT
iajs-2800	21	28	also	also	ADV
iajs-2800	21	29	under	under	ADP
iajs-2800	21	30	double	double	ADJ
iajs-2800	21	31	priors	prior	NOUN
iajs-2800	21	32	such	such	ADJ
iajs-2800	21	33	as	as	ADP
iajs-2800	21	34	gamma	gamma	NOUN
iajs-2800	21	35	-	-	PUNCT
iajs-2800	21	36	chi	chi	ADJ
iajs-2800	21	37	-	-	PUNCT
iajs-2800	21	38	square	square	NOUN
iajs-2800	21	39	distributions	distribution	NOUN
iajs-2800	21	40	,	,	PUNCT
iajs-2800	21	41	gamma	gamma	NOUN
iajs-2800	21	42	-	-	PUNCT
iajs-2800	21	43	exponential	exponential	NOUN
iajs-2800	21	44	distributions	distribution	NOUN
iajs-2800	21	45	,	,	PUNCT
iajs-2800	21	46	chi	chi	ADJ
iajs-2800	21	47	-	-	PUNCT
iajs-2800	21	48	square	square	ADJ
iajs-2800	21	49	-	-	PUNCT
iajs-2800	21	50	exponential	exponential	NOUN
iajs-2800	21	51	distributions	distribution	NOUN
iajs-2800	21	52	.	.	PUNCT
iajs-2800	22	1	they	they	PRON
iajs-2800	22	2	used	use	VERB
iajs-2800	22	3	r	r	NOUN
iajs-2800	22	4	software	software	NOUN
iajs-2800	22	5	to	to	PART
iajs-2800	22	6	find	find	VERB
iajs-2800	22	7	posterior	posterior	ADJ
iajs-2800	22	8	estimates	estimate	NOUN
iajs-2800	22	9	.	.	PUNCT
iajs-2800	23	1	they	they	PRON
iajs-2800	23	2	explained	explain	VERB
iajs-2800	23	3	the	the	DET
iajs-2800	23	4	results	result	NOUN
iajs-2800	23	5	of	of	ADP
iajs-2800	23	6	this	this	DET
iajs-2800	23	7	study	study	NOUN
iajs-2800	23	8	through	through	ADP
iajs-2800	23	9	numerical	numerical	ADJ
iajs-2800	23	10	and	and	CCONJ
iajs-2800	23	11	graphical	graphical	ADJ
iajs-2800	23	12	posterior	posterior	ADJ
iajs-2800	23	13	densities	density	NOUN
iajs-2800	23	14	of	of	ADP
iajs-2800	23	15	the	the	DET
iajs-2800	23	16	parameters	parameter	NOUN
iajs-2800	23	17	.	.	PUNCT
iajs-2800	24	1	[	[	X
iajs-2800	24	2	3	3	NUM
iajs-2800	24	3	]	]	PUNCT
iajs-2800	24	4	deals	deal	NOUN
iajs-2800	24	5	with	with	ADP
iajs-2800	24	6	the	the	DET
iajs-2800	24	7	problem	problem	NOUN
iajs-2800	24	8	of	of	ADP
iajs-2800	24	9	estimating	estimate	VERB
iajs-2800	24	10	parameters	parameter	NOUN
iajs-2800	24	11	of	of	ADP
iajs-2800	24	12	some	some	DET
iajs-2800	24	13	well	well	ADV
iajs-2800	24	14	-	-	PUNCT
iajs-2800	24	15	known	know	VERB
iajs-2800	24	16	distribution	distribution	NOUN
iajs-2800	24	17	functions	function	NOUN
iajs-2800	24	18	such	such	ADJ
iajs-2800	24	19	as	as	ADP
iajs-2800	24	20	binomial	binomial	ADJ
iajs-2800	24	21	,	,	PUNCT
iajs-2800	24	22	poisson	poisson	NOUN
iajs-2800	24	23	,	,	PUNCT
iajs-2800	24	24	normal	normal	ADJ
iajs-2800	24	25	and	and	CCONJ
iajs-2800	24	26	exponential	exponential	ADJ
iajs-2800	24	27	distribution	distribution	NOUN
iajs-2800	24	28	function	function	NOUN
iajs-2800	24	29	.	.	PUNCT
iajs-2800	25	1	he	he	PRON
iajs-2800	25	2	derived	derive	VERB
iajs-2800	25	3	estimation	estimation	NOUN
iajs-2800	25	4	of	of	ADP
iajs-2800	25	5	parameters	parameter	NOUN
iajs-2800	25	6	by	by	ADP
iajs-2800	25	7	using	use	VERB
iajs-2800	25	8	maximum	maximum	ADJ
iajs-2800	25	9	likelihood	likelihood	NOUN
iajs-2800	25	10	,	,	PUNCT
iajs-2800	25	11	method	method	NOUN
iajs-2800	25	12	of	of	ADP
iajs-2800	25	13	moment	moment	NOUN
iajs-2800	25	14	,	,	PUNCT
iajs-2800	25	15	and	and	CCONJ
iajs-2800	25	16	bayes	bayes	PROPN
iajs-2800	25	17	estimation	estimation	NOUN
iajs-2800	25	18	.	.	PUNCT
iajs-2800	26	1	he	he	PRON
iajs-2800	26	2	derived	derive	VERB
iajs-2800	26	3	bayes	bayes	NOUN
iajs-2800	26	4	estimators	estimator	NOUN
iajs-2800	26	5	for	for	ADP
iajs-2800	26	6	the	the	DET
iajs-2800	26	7	parameters	parameter	NOUN
iajs-2800	26	8	of	of	ADP
iajs-2800	26	9	these	these	DET
iajs-2800	26	10	distributions	distribution	NOUN
iajs-2800	26	11	using	use	VERB
iajs-2800	26	12	lindley	lindley	NOUN
iajs-2800	26	13	's	's	PART
iajs-2800	26	14	approximation	approximation	NOUN
iajs-2800	26	15	based	base	VERB
iajs-2800	26	16	on	on	ADP
iajs-2800	26	17	different	different	ADJ
iajs-2800	26	18	types	type	NOUN
iajs-2800	26	19	of	of	ADP
iajs-2800	26	20	priors	prior	NOUN
iajs-2800	26	21	.	.	PUNCT
iajs-2800	27	1	[	[	X
iajs-2800	27	2	4	4	X
iajs-2800	27	3	]	]	PUNCT
iajs-2800	27	4	discussed	discuss	VERB
iajs-2800	27	5	different	different	ADJ
iajs-2800	27	6	estimation	estimation	NOUN
iajs-2800	27	7	methods	method	NOUN
iajs-2800	27	8	for	for	ADP
iajs-2800	27	9	poisson	poisson	NOUN
iajs-2800	27	10	parameter	parameter	NOUN
iajs-2800	27	11	estimations	estimation	NOUN
iajs-2800	27	12	.	.	PUNCT
iajs-2800	28	1	which	which	PRON
iajs-2800	28	2	were	be	AUX
iajs-2800	28	3	represented	represent	VERB
iajs-2800	28	4	by	by	ADP
iajs-2800	28	5	maximum	maximum	ADJ
iajs-2800	28	6	likelihood	likelihood	NOUN
iajs-2800	28	7	,	,	PUNCT
iajs-2800	28	8	markov	markov	NOUN
iajs-2800	28	9	chain	chain	NOUN
iajs-2800	28	10	monte	monte	PROPN
iajs-2800	28	11	carlo	carlo	PROPN
iajs-2800	28	12	,	,	PUNCT
iajs-2800	28	13	and	and	CCONJ
iajs-2800	28	14	bayes	bayes	PROPN
iajs-2800	28	15	method	method	NOUN
iajs-2800	28	16	.	.	PUNCT
iajs-2800	29	1	he	he	PRON
iajs-2800	29	2	derives	derive	VERB
iajs-2800	29	3	the	the	DET
iajs-2800	29	4	bayes	bayes	NOUN
iajs-2800	29	5	estimators	estimator	NOUN
iajs-2800	29	6	under	under	ADP
iajs-2800	29	7	the	the	DET
iajs-2800	29	8	squared	square	VERB
iajs-2800	29	9	error	error	NOUN
iajs-2800	29	10	loss	loss	NOUN
iajs-2800	29	11	function	function	NOUN
iajs-2800	29	12	based	base	VERB
iajs-2800	29	13	on	on	ADP
iajs-2800	29	14	gamma	gamma	NOUN
iajs-2800	29	15	prior	prior	ADJ
iajs-2800	29	16	distribution	distribution	NOUN
iajs-2800	29	17	.	.	PUNCT
iajs-2800	30	1	he	he	PRON
iajs-2800	30	2	used	use	VERB
iajs-2800	30	3	a	a	DET
iajs-2800	30	4	simulation	simulation	NOUN
iajs-2800	30	5	study	study	NOUN
iajs-2800	30	6	for	for	ADP
iajs-2800	30	7	investigating	investigate	VERB
iajs-2800	30	8	the	the	DET
iajs-2800	30	9	performance	performance	NOUN
iajs-2800	30	10	of	of	ADP
iajs-2800	30	11	the	the	DET
iajs-2800	30	12	ml	ml	NOUN
iajs-2800	30	13	method	method	NOUN
iajs-2800	30	14	,	,	PUNCT
iajs-2800	30	15	the	the	DET
iajs-2800	30	16	markov	markov	NOUN
iajs-2800	30	17	chain	chain	NOUN
iajs-2800	30	18	monte	monte	PROPN
iajs-2800	30	19	carlo	carlo	PROPN
iajs-2800	30	20	method	method	NOUN
iajs-2800	30	21	,	,	PUNCT
iajs-2800	30	22	and	and	CCONJ
iajs-2800	30	23	the	the	DET
iajs-2800	30	24	bayes	bayes	PROPN
iajs-2800	30	25	method	method	NOUN
iajs-2800	30	26	.	.	PUNCT
iajs-2800	31	1	also	also	ADV
iajs-2800	31	2	,	,	PUNCT
iajs-2800	31	3	he	he	PRON
iajs-2800	31	4	applies	apply	VERB
iajs-2800	31	5	to	to	PART
iajs-2800	31	6	test	test	VERB
iajs-2800	31	7	a	a	DET
iajs-2800	31	8	hypothesis	hypothesis	NOUN
iajs-2800	31	9	that	that	SCONJ
iajs-2800	31	10	the	the	DET
iajs-2800	31	11	means	mean	NOUN
iajs-2800	31	12	of	of	ADP
iajs-2800	31	13	poisson	poisson	PROPN
iajs-2800	31	14	parameter	parameter	PROPN
iajs-2800	31	15	estimations	estimation	NOUN
iajs-2800	31	16	obtained	obtain	VERB
iajs-2800	31	17	from	from	ADP
iajs-2800	31	18	the	the	DET
iajs-2800	31	19	ml	ml	NOUN
iajs-2800	31	20	method	method	NOUN
iajs-2800	31	21	,	,	PUNCT
iajs-2800	31	22	markov	markov	NOUN
iajs-2800	31	23	chain	chain	NOUN
iajs-2800	31	24	monte	monte	PROPN
iajs-2800	31	25	carlo	carlo	PROPN
iajs-2800	31	26	method	method	NOUN
iajs-2800	31	27	,	,	PUNCT
iajs-2800	31	28	and	and	CCONJ
iajs-2800	31	29	bayes	bayes	PROPN
iajs-2800	31	30	method	method	NOUN
iajs-2800	31	31	were	be	AUX
iajs-2800	31	32	not	not	PART
iajs-2800	31	33	different	different	ADJ
iajs-2800	31	34	from	from	ADP
iajs-2800	31	35	the	the	DET
iajs-2800	31	36	true	true	ADJ
iajs-2800	31	37	parameters	parameter	NOUN
iajs-2800	31	38	.	.	PUNCT
iajs-2800	32	1	[	[	X
iajs-2800	32	2	5	5	NUM
iajs-2800	32	3	]	]	PUNCT
iajs-2800	32	4	described	describe	VERB
iajs-2800	32	5	several	several	ADJ
iajs-2800	32	6	interval	interval	NOUN
iajs-2800	32	7	estimators	estimator	NOUN
iajs-2800	32	8	for	for	SCONJ
iajs-2800	32	9	the	the	DET
iajs-2800	32	10	poisson	poisson	NOUN
iajs-2800	32	11	mean	mean	VERB
iajs-2800	32	12	,	,	PUNCT
iajs-2800	32	13	such	such	ADJ
iajs-2800	32	14	as	as	ADP
iajs-2800	32	15	classical	classical	ADJ
iajs-2800	32	16	interval	interval	NOUN
iajs-2800	32	17	estimators	estimator	NOUN
iajs-2800	32	18	:	:	PUNCT
iajs-2800	32	19	the	the	DET
iajs-2800	32	20	wald	wald	PROPN
iajs-2800	32	21	interval	interval	NOUN
iajs-2800	32	22	estimator	estimator	NOUN
iajs-2800	32	23	,	,	PUNCT
iajs-2800	32	24	the	the	DET
iajs-2800	32	25	score	score	NOUN
iajs-2800	32	26	interval	interval	NOUN
iajs-2800	32	27	estimator	estimator	NOUN
iajs-2800	32	28	,	,	PUNCT
iajs-2800	32	29	the	the	DET
iajs-2800	32	30	exact	exact	ADJ
iajs-2800	32	31	interval	interval	NOUN
iajs-2800	32	32	estimator	estimator	NOUN
iajs-2800	32	33	,	,	PUNCT
iajs-2800	32	34	and	and	CCONJ
iajs-2800	32	35	the	the	DET
iajs-2800	32	36	bootstrap	bootstrap	NOUN
iajs-2800	32	37	interval	interval	NOUN
iajs-2800	32	38	estimator	estimator	NOUN
iajs-2800	32	39	.	.	PUNCT
iajs-2800	33	1	also	also	ADV
iajs-2800	33	2	,	,	PUNCT
iajs-2800	33	3	they	they	PRON
iajs-2800	33	4	described	describe	VERB
iajs-2800	33	5	bayes	bayes	NOUN
iajs-2800	33	6	credible	credible	ADJ
iajs-2800	33	7	estimators	estimator	NOUN
iajs-2800	33	8	,	,	PUNCT
iajs-2800	33	9	such	such	ADJ
iajs-2800	33	10	as	as	ADP
iajs-2800	33	11	the	the	DET
iajs-2800	33	12	equal	equal	ADJ
iajs-2800	33	13	tails	tail	NOUN
iajs-2800	33	14	credible	credible	ADJ
iajs-2800	33	15	interval	interval	NOUN
iajs-2800	33	16	estimator	estimator	NOUN
iajs-2800	33	17	,	,	PUNCT
iajs-2800	33	18	jeffrey	jeffrey	PROPN
iajs-2800	33	19	's	's	PART
iajs-2800	33	20	prior	prior	ADJ
iajs-2800	33	21	credible	credible	ADJ
iajs-2800	33	22	interval	interval	NOUN
iajs-2800	33	23	estimator	estimator	NOUN
iajs-2800	33	24	,	,	PUNCT
iajs-2800	33	25	the	the	DET
iajs-2800	33	26	highest	high	ADJ
iajs-2800	33	27	posterior	posterior	ADJ
iajs-2800	33	28	density	density	NOUN
iajs-2800	33	29	(	(	PUNCT
iajs-2800	33	30	hpd	hpd	NOUN
iajs-2800	33	31	)	)	PUNCT
iajs-2800	33	32	credible	credible	ADJ
iajs-2800	33	33	interval	interval	NOUN
iajs-2800	33	34	estimator	estimator	NOUN
iajs-2800	33	35	,	,	PUNCT
iajs-2800	33	36	the	the	DET
iajs-2800	33	37	relative	relative	ADJ
iajs-2800	33	38	surprise	surprise	NOUN
iajs-2800	33	39	credible	credible	ADJ
iajs-2800	33	40	interval	interval	NOUN
iajs-2800	33	41	estimator	estimator	NOUN
iajs-2800	33	42	.	.	PUNCT
iajs-2800	34	1	they	they	PRON
iajs-2800	34	2	derived	derive	VERB
iajs-2800	34	3	bayes	bayes	NOUN
iajs-2800	34	4	estimators	estimator	NOUN
iajs-2800	34	5	based	base	VERB
iajs-2800	34	6	on	on	ADP
iajs-2800	34	7	four	four	NUM
iajs-2800	34	8	different	different	ADJ
iajs-2800	34	9	priors	prior	NOUN
iajs-2800	34	10	,	,	PUNCT
iajs-2800	34	11	such	such	ADJ
iajs-2800	34	12	as	as	ADP
iajs-2800	34	13	uniform	uniform	NOUN
iajs-2800	34	14	prior	prior	ADV
iajs-2800	34	15	,	,	PUNCT
iajs-2800	34	16	exponential	exponential	ADJ
iajs-2800	34	17	prior	prior	NOUN
iajs-2800	34	18	,	,	PUNCT
iajs-2800	34	19	gamma	gamma	PROPN
iajs-2800	34	20	prior	prior	ADV
iajs-2800	34	21	and	and	CCONJ
iajs-2800	34	22	chi	chi	ADJ
iajs-2800	34	23	-	-	PUNCT
iajs-2800	34	24	square	square	NOUN
iajs-2800	34	25	prior	prior	NOUN
iajs-2800	34	26	.	.	PUNCT
iajs-2800	35	1	performances	performance	NOUN
iajs-2800	35	2	of	of	ADP
iajs-2800	35	3	the	the	DET
iajs-2800	35	4	proposed	propose	VERB
iajs-2800	35	5	bayes	bayes	NOUN
iajs-2800	35	6	estimators	estimator	NOUN
iajs-2800	35	7	have	have	AUX
iajs-2800	35	8	been	be	AUX
iajs-2800	35	9	studied	study	VERB
iajs-2800	35	10	and	and	CCONJ
iajs-2800	35	11	compared	compare	VERB
iajs-2800	35	12	in	in	ADP
iajs-2800	35	13	terms	term	NOUN
iajs-2800	35	14	of	of	ADP
iajs-2800	35	15	coverage	coverage	NOUN
iajs-2800	35	16	probabilities	probability	NOUN
iajs-2800	35	17	and	and	CCONJ
iajs-2800	35	18	coverage	coverage	NOUN
iajs-2800	35	19	lengths	length	NOUN
iajs-2800	35	20	based	base	VERB
iajs-2800	35	21	on	on	ADP
iajs-2800	35	22	a	a	DET
iajs-2800	35	23	simulation	simulation	NOUN
iajs-2800	35	24	study	study	NOUN
iajs-2800	35	25	.	.	PUNCT
iajs-2800	36	1	the	the	DET
iajs-2800	36	2	methodology	methodology	NOUN
iajs-2800	36	3	is	be	AUX
iajs-2800	36	4	also	also	ADV
iajs-2800	36	5	illustrated	illustrate	VERB
iajs-2800	36	6	on	on	ADP
iajs-2800	36	7	a	a	DET
iajs-2800	36	8	real	real	ADJ
iajs-2800	36	9	data	datum	NOUN
iajs-2800	36	10	set	set	VERB
iajs-2800	36	11	.	.	PUNCT
iajs-2800	37	1	[	[	X
iajs-2800	37	2	6	6	NUM
iajs-2800	37	3	]	]	PUNCT
iajs-2800	37	4	derived	derive	VERB
iajs-2800	37	5	the	the	DET
iajs-2800	37	6	bayes	bayes	PROPN
iajs-2800	37	7	posterior	posterior	ADJ
iajs-2800	37	8	estimator	estimator	NOUN
iajs-2800	37	9	of	of	ADP
iajs-2800	37	10	the	the	DET
iajs-2800	37	11	parameter	parameter	NOUN
iajs-2800	37	12	of	of	ADP
iajs-2800	37	13	the	the	DET
iajs-2800	37	14	poisson	poisson	NOUN
iajs-2800	37	15	distribution	distribution	NOUN
iajs-2800	37	16	under	under	ADP
iajs-2800	37	17	the	the	DET
iajs-2800	37	18	squared	square	VERB
iajs-2800	37	19	error	error	NOUN
iajs-2800	37	20	and	and	CCONJ
iajs-2800	37	21	stein	stein	PROPN
iajs-2800	37	22	's	's	PART
iajs-2800	37	23	loss	loss	NOUN
iajs-2800	37	24	functions	function	NOUN
iajs-2800	37	25	.	.	PUNCT
iajs-2800	38	1	he	he	PRON
iajs-2800	38	2	obtains	obtain	VERB
iajs-2800	38	3	the	the	DET
iajs-2800	38	4	empirical	empirical	ADJ
iajs-2800	38	5	bayes	bayes	NOUN
iajs-2800	38	6	estimators	estimator	NOUN
iajs-2800	38	7	of	of	ADP
iajs-2800	38	8	the	the	DET
iajs-2800	38	9	parameter	parameter	NOUN
iajs-2800	38	10	of	of	ADP
iajs-2800	38	11	the	the	DET
iajs-2800	38	12	poisson	poisson	NOUN
iajs-2800	38	13	distribution	distribution	NOUN
iajs-2800	38	14	based	base	VERB
iajs-2800	38	15	on	on	ADP
iajs-2800	38	16	gamma	gamma	NOUN
iajs-2800	38	17	prior	prior	ADJ
iajs-2800	38	18	distribution	distribution	NOUN
iajs-2800	38	19	.	.	PUNCT
iajs-2800	39	1	he	he	PRON
iajs-2800	39	2	investigates	investigate	VERB
iajs-2800	39	3	the	the	DET
iajs-2800	39	4	behavior	behavior	NOUN
iajs-2800	39	5	of	of	ADP
iajs-2800	39	6	estimators	estimator	NOUN
iajs-2800	39	7	for	for	ADP
iajs-2800	39	8	the	the	DET
iajs-2800	39	9	parameter	parameter	NOUN
iajs-2800	39	10	of	of	ADP
iajs-2800	39	11	poisson	poisson	NOUN
iajs-2800	39	12	distribution	distribution	NOUN
iajs-2800	39	13	by	by	ADP
iajs-2800	39	14	using	use	VERB
iajs-2800	39	15	simulation	simulation	NOUN
iajs-2800	39	16	results	result	NOUN
iajs-2800	39	17	.	.	PUNCT
iajs-2800	40	1	[	[	X
iajs-2800	40	2	7	7	X
iajs-2800	40	3	]	]	PUNCT
iajs-2800	40	4	discussed	discuss	VERB
iajs-2800	40	5	the	the	DET
iajs-2800	40	6	e	e	NOUN
iajs-2800	40	7	-	-	NOUN
iajs-2800	40	8	bayesian	bayesian	ADJ
iajs-2800	40	9	and	and	CCONJ
iajs-2800	40	10	empirical	empirical	ADJ
iajs-2800	40	11	ebayesian	ebayesian	ADJ
iajs-2800	40	12	estimates	estimate	NOUN
iajs-2800	40	13	for	for	ADP
iajs-2800	40	14	the	the	DET
iajs-2800	40	15	parameter	parameter	NOUN
iajs-2800	40	16	of	of	ADP
iajs-2800	40	17	the	the	DET
iajs-2800	40	18	poisson	poisson	NOUN
iajs-2800	40	19	distribution	distribution	NOUN
iajs-2800	40	20	.	.	PUNCT
iajs-2800	41	1	he	he	PRON
iajs-2800	41	2	also	also	ADV
iajs-2800	41	3	derived	derive	VERB
iajs-2800	41	4	posterior	posterior	ADJ
iajs-2800	41	5	risk	risk	NOUN
iajs-2800	41	6	for	for	ADP
iajs-2800	41	7	empirical	empirical	ADJ
iajs-2800	41	8	e	e	NOUN
iajs-2800	41	9	-	-	NOUN
iajs-2800	41	10	bayesian	bayesian	ADJ
iajs-2800	41	11	e	e	NOUN
iajs-2800	41	12	-	-	NOUN
iajs-2800	41	13	bayesian	bayesian	ADJ
iajs-2800	41	14	approximation	approximation	NOUN
iajs-2800	41	15	based	base	VERB
iajs-2800	41	16	on	on	ADP
iajs-2800	41	17	the	the	DET
iajs-2800	41	18	squared	square	VERB
iajs-2800	41	19	error	error	NOUN
iajs-2800	41	20	loss	loss	NOUN
iajs-2800	41	21	function	function	NOUN
iajs-2800	41	22	.	.	PUNCT
iajs-2800	42	1	he	he	PRON
iajs-2800	42	2	investigates	investigate	VERB
iajs-2800	42	3	the	the	DET
iajs-2800	42	4	behavior	behavior	NOUN
iajs-2800	42	5	of	of	ADP
iajs-2800	42	6	different	different	ADJ
iajs-2800	42	7	estimators	estimator	NOUN
iajs-2800	42	8	for	for	ADP
iajs-2800	42	9	the	the	DET
iajs-2800	42	10	parameter	parameter	NOUN
iajs-2800	42	11	of	of	ADP
iajs-2800	42	12	poisson	poisson	NOUN
iajs-2800	42	13	distribution	distribution	NOUN
iajs-2800	42	14	based	base	VERB
iajs-2800	42	15	on	on	ADP
iajs-2800	42	16	monte	monte	PROPN
iajs-2800	42	17	carlo	carlo	PROPN
iajs-2800	42	18	simulation	simulation	PROPN
iajs-2800	42	19	.	.	PUNCT
iajs-2800	43	1	he	he	PRON
iajs-2800	43	2	also	also	ADV
iajs-2800	43	3	applied	apply	VERB
iajs-2800	43	4	ee	ee	PROPN
iajs-2800	43	5	-	-	PUNCT
iajs-2800	43	6	bayesian	bayesian	NOUN
iajs-2800	43	7	estimates	estimate	NOUN
iajs-2800	43	8	and	and	CCONJ
iajs-2800	43	9	ee	ee	NOUN
iajs-2800	43	10	-	-	PUNCT
iajs-2800	43	11	posterior	posterior	ADJ
iajs-2800	43	12	risk	risk	NOUN
iajs-2800	43	13	on	on	ADP
iajs-2800	43	14	a	a	DET
iajs-2800	43	15	real	real	ADJ
iajs-2800	43	16	data	datum	NOUN
iajs-2800	43	17	set	set	VERB
iajs-2800	43	18	.	.	PUNCT
iajs-2800	44	1	[	[	X
iajs-2800	44	2	8	8	NUM
iajs-2800	44	3	]	]	PUNCT
iajs-2800	44	4	used	use	VERB
iajs-2800	44	5	different	different	ADJ
iajs-2800	44	6	estimation	estimation	NOUN
iajs-2800	44	7	methods	method	NOUN
iajs-2800	44	8	for	for	ADP
iajs-2800	44	9	the	the	DET
iajs-2800	44	10	parameter	parameter	NOUN
iajs-2800	44	11	poisson	poisson	NOUN
iajs-2800	44	12	,	,	PUNCT
iajs-2800	44	13	represented	represent	VERB
iajs-2800	44	14	by	by	ADP
iajs-2800	44	15	maximum	maximum	ADJ
iajs-2800	44	16	likelihood	likelihood	NOUN
iajs-2800	44	17	,	,	PUNCT
iajs-2800	44	18	empirical	empirical	ADJ
iajs-2800	44	19	bayes	bayes	NOUN
iajs-2800	44	20	and	and	CCONJ
iajs-2800	44	21	bayes	bayes	PROPN
iajs-2800	44	22	estimation	estimation	NOUN
iajs-2800	44	23	.	.	PUNCT
iajs-2800	45	1	she	she	PRON
iajs-2800	45	2	derived	derive	VERB
iajs-2800	45	3	the	the	DET
iajs-2800	45	4	posterior	posterior	ADJ
iajs-2800	45	5	distribution	distribution	NOUN
iajs-2800	45	6	of	of	ADP
iajs-2800	45	7	the	the	DET
iajs-2800	45	8	poisson	poisson	NOUN
iajs-2800	45	9	parameter	parameter	NOUN
iajs-2800	45	10	under	under	ADP
iajs-2800	45	11	the	the	DET
iajs-2800	45	12	squared	square	VERB
iajs-2800	45	13	error	error	NOUN
iajs-2800	45	14	and	and	CCONJ
iajs-2800	45	15	quadratic	quadratic	ADJ
iajs-2800	45	16	loss	loss	NOUN
iajs-2800	45	17	functions	function	NOUN
iajs-2800	45	18	based	base	VERB
iajs-2800	45	19	on	on	ADP
iajs-2800	45	20	gamma	gamma	NOUN
iajs-2800	45	21	prior	prior	ADJ
iajs-2800	45	22	distribution	distribution	NOUN
iajs-2800	45	23	.	.	PUNCT
iajs-2800	46	1	she	she	PRON
iajs-2800	46	2	used	use	VERB
iajs-2800	46	3	a	a	DET
iajs-2800	46	4	simulation	simulation	NOUN
iajs-2800	46	5	method	method	NOUN
iajs-2800	46	6	to	to	PART
iajs-2800	46	7	obtain	obtain	VERB
iajs-2800	46	8	the	the	DET
iajs-2800	46	9	results	result	NOUN
iajs-2800	46	10	,	,	PUNCT
iajs-2800	46	11	to	to	ADP
iajs-2800	46	12	including	include	VERB
iajs-2800	46	13	the	the	DET
iajs-2800	46	14	point	point	NOUN
iajs-2800	46	15	estimates	estimate	NOUN
iajs-2800	46	16	and	and	CCONJ
iajs-2800	46	17	confidence	confidence	NOUN
iajs-2800	46	18	intervals	interval	NOUN
iajs-2800	46	19	and	and	CCONJ
iajs-2800	46	20	the	the	DET
iajs-2800	46	21	mean	mean	ADJ
iajs-2800	46	22	square	square	ADJ
iajs-2800	46	23	error	error	NOUN
iajs-2800	46	24	(	(	PUNCT
iajs-2800	46	25	mse	mse	NOUN
iajs-2800	46	26	)	)	PUNCT
iajs-2800	46	27	for	for	ADP
iajs-2800	46	28	the	the	DET
iajs-2800	46	29	parameter	parameter	NOUN
iajs-2800	46	30	poisson	poisson	NOUN
iajs-2800	46	31	.	.	PUNCT
iajs-2800	47	1	she	she	PRON
iajs-2800	47	2	applied	apply	VERB
iajs-2800	47	3	methods	method	NOUN
iajs-2800	47	4	of	of	ADP
iajs-2800	47	5	estimation	estimation	NOUN
iajs-2800	47	6	on	on	ADP
iajs-2800	47	7	a	a	DET
iajs-2800	47	8	real	real	ADJ
iajs-2800	47	9	data	datum	NOUN
iajs-2800	47	10	set	set	VERB
iajs-2800	47	11	.	.	PUNCT
iajs-2800	48	1	our	our	PRON
iajs-2800	48	2	aim	aim	NOUN
iajs-2800	48	3	in	in	ADP
iajs-2800	48	4	this	this	DET
iajs-2800	48	5	study	study	NOUN
iajs-2800	48	6	is	be	AUX
iajs-2800	48	7	to	to	PART
iajs-2800	48	8	examine	examine	VERB
iajs-2800	48	9	the	the	DET
iajs-2800	48	10	effects	effect	NOUN
iajs-2800	48	11	of	of	ADP
iajs-2800	48	12	the	the	DET
iajs-2800	48	13	squared	square	VERB
iajs-2800	48	14	error	error	NOUN
iajs-2800	48	15	loss	loss	NOUN
iajs-2800	48	16	function	function	NOUN
iajs-2800	48	17	,	,	PUNCT
iajs-2800	48	18	and	and	CCONJ
iajs-2800	48	19	the	the	DET
iajs-2800	48	20	proposed	propose	VERB
iajs-2800	48	21	exponential	exponential	ADJ
iajs-2800	48	22	loss	loss	NOUN
iajs-2800	48	23	function	function	NOUN
iajs-2800	48	24	which	which	PRON
iajs-2800	48	25	are	be	AUX
iajs-2800	48	26	presented	present	VERB
iajs-2800	48	27	in	in	ADP
iajs-2800	48	28	this	this	DET
iajs-2800	48	29	study	study	NOUN
iajs-2800	48	30	,	,	PUNCT
iajs-2800	48	31	based	base	VERB
iajs-2800	48	32	on	on	ADP
iajs-2800	48	33	different	different	ADJ
iajs-2800	48	34	priors	prior	NOUN
iajs-2800	48	35	ibn	ibn	PROPN
iajs-2800	48	36	al	al	PROPN
iajs-2800	48	37	-	-	PUNCT
iajs-2800	48	38	haitham	haitham	PROPN
iajs-2800	48	39	jour	jour	X
iajs-2800	48	40	.	.	PROPN
iajs-2800	48	41	for	for	ADP
iajs-2800	48	42	pure	pure	ADJ
iajs-2800	48	43	&	&	CCONJ
iajs-2800	48	44	appl	appl	PROPN
iajs-2800	48	45	.	.	PUNCT
iajs-2800	49	1	sci	sci	PROPN
iajs-2800	49	2	.	.	PROPN
iajs-2800	50	1	53	53	NUM
iajs-2800	50	2	(	(	PUNCT
iajs-2800	50	3	1)2022	1)2022	PROPN
iajs-2800	50	4	62	62	NUM
iajs-2800	50	5	represented	represent	VERB
iajs-2800	50	6	by	by	ADP
iajs-2800	50	7	erlang	erlang	PROPN
iajs-2800	50	8	and	and	CCONJ
iajs-2800	50	9	levy	levy	VERB
iajs-2800	50	10	prior	prior	ADJ
iajs-2800	50	11	distributions	distribution	NOUN
iajs-2800	50	12	and	and	CCONJ
iajs-2800	50	13	non	non	ADJ
iajs-2800	50	14	-	-	ADJ
iajs-2800	50	15	informative	informative	ADJ
iajs-2800	50	16	prior	prior	ADV
iajs-2800	50	17	on	on	ADP
iajs-2800	50	18	bayes	bayes	PROPN
iajs-2800	50	19	’s	’s	PART
iajs-2800	50	20	estimators	estimator	NOUN
iajs-2800	50	21	of	of	ADP
iajs-2800	50	22	poisson	poisson	NOUN
iajs-2800	50	23	distribution	distribution	NOUN
iajs-2800	50	24	.	.	PUNCT
iajs-2800	51	1	we	we	PRON
iajs-2800	51	2	compared	compare	VERB
iajs-2800	51	3	the	the	DET
iajs-2800	51	4	accuracy	accuracy	NOUN
iajs-2800	51	5	for	for	ADP
iajs-2800	51	6	bayes	baye	NOUN
iajs-2800	51	7	’	'	PUNCT
iajs-2800	51	8	estimators	estimator	NOUN
iajs-2800	51	9	with	with	ADP
iajs-2800	51	10	the	the	DET
iajs-2800	51	11	corresponding	corresponding	ADJ
iajs-2800	51	12	maximum	maximum	ADJ
iajs-2800	51	13	likelihood	likelihood	NOUN
iajs-2800	51	14	estimator	estimator	NOUN
iajs-2800	51	15	(	(	PUNCT
iajs-2800	51	16	mle	mle	PROPN
iajs-2800	51	17	)	)	PUNCT
iajs-2800	51	18	of	of	ADP
iajs-2800	51	19	poisson	poisson	NOUN
iajs-2800	51	20	distribution	distribution	NOUN
iajs-2800	51	21	based	base	VERB
iajs-2800	51	22	on	on	ADP
iajs-2800	51	23	the	the	DET
iajs-2800	51	24	root	root	NOUN
iajs-2800	51	25	mean	mean	VERB
iajs-2800	51	26	squared	square	VERB
iajs-2800	51	27	error	error	NOUN
iajs-2800	51	28	(	(	PUNCT
iajs-2800	51	29	rmse	rmse	NOUN
iajs-2800	51	30	)	)	PUNCT
iajs-2800	51	31	.	.	PUNCT
iajs-2800	52	1	2	2	X
iajs-2800	52	2	.	.	X
iajs-2800	52	3	poisson	poisson	NOUN
iajs-2800	52	4	distribution	distribution	NOUN
iajs-2800	52	5	assuming	assume	VERB
iajs-2800	52	6	that	that	SCONJ
iajs-2800	52	7	)	)	PUNCT
iajs-2800	53	1	t	t	X
iajs-2800	53	2	...	...	PUNCT
iajs-2800	53	3	,	,	PUNCT
iajs-2800	53	4	,	,	PUNCT
iajs-2800	53	5	t	t	PROPN
iajs-2800	53	6	,	,	PUNCT
iajs-2800	53	7	t	t	PROPN
iajs-2800	53	8	(	(	PUNCT
iajs-2800	53	9	n21	n21	PROPN
iajs-2800	53	10	be	be	AUX
iajs-2800	53	11	identical	identical	ADJ
iajs-2800	53	12	independent	independent	ADJ
iajs-2800	53	13	distribution	distribution	NOUN
iajs-2800	53	14	(	(	PUNCT
iajs-2800	53	15	iid	iid	NOUN
iajs-2800	53	16	)	)	PUNCT
iajs-2800	53	17	random	random	ADJ
iajs-2800	53	18	variables	variable	NOUN
iajs-2800	53	19	from	from	ADP
iajs-2800	53	20	the	the	DET
iajs-2800	53	21	poisson	poisson	NOUN
iajs-2800	53	22	distribution	distribution	NOUN
iajs-2800	53	23	with	with	ADP
iajs-2800	53	24	the	the	DET
iajs-2800	53	25	following	follow	VERB
iajs-2800	53	26	probability	probability	NOUN
iajs-2800	53	27	mass	mass	NOUN
iajs-2800	53	28	function	function	NOUN
iajs-2800	53	29	[	[	X
iajs-2800	53	30	7,8	7,8	NUM
iajs-2800	53	31	]	]	PUNCT
iajs-2800	53	32	.	.	PUNCT
iajs-2800	53	33	)	)	PUNCT
iajs-2800	54	1	1	1	NUM
iajs-2800	54	2	(	(	PUNCT
iajs-2800	54	3	0θ	0θ	NOUN
iajs-2800	54	4	...	...	PUNCT
iajs-2800	54	5	,	,	PUNCT
iajs-2800	54	6	2	2	NUM
iajs-2800	54	7	,	,	PUNCT
iajs-2800	54	8	0,1	0,1	NUM
iajs-2800	54	9	t	t	PROPN
iajs-2800	54	10	,	,	PUNCT
iajs-2800	54	11	t	t	PROPN
iajs-2800	54	12	!	!	PUNCT
iajs-2800	55	1	θe	θe	ADP
iajs-2800	55	2	θ	θ	PROPN
iajs-2800	55	3	and	and	CCONJ
iajs-2800	55	4	)	)	PUNCT
iajs-2800	55	5	t	t	PROPN
iajs-2800	55	6	;	;	PUNCT
iajs-2800	55	7	(	(	PUNCT
iajs-2800	55	8	p	p	NOUN
iajs-2800	55	9	tθ	tθ	ADP
iajs-2800	55	10			ADJ
iajs-2800	55	11			NOUN
iajs-2800	55	12	with	with	ADP
iajs-2800	55	13	the	the	DET
iajs-2800	55	14	shape	shape	NOUN
iajs-2800	55	15	parameter	parameter	NOUN
iajs-2800	55	16	0θ	0θ	NOUN
iajs-2800	55	17			PROPN
iajs-2800	55	18	.	.	PUNCT
iajs-2800	56	1	the	the	DET
iajs-2800	56	2	cumulative	cumulative	ADJ
iajs-2800	56	3	distribution	distribution	NOUN
iajs-2800	56	4	function	function	NOUN
iajs-2800	56	5	has	have	VERB
iajs-2800	56	6	no	no	DET
iajs-2800	56	7	particular	particular	ADJ
iajs-2800	56	8	form	form	NOUN
iajs-2800	56	9	.	.	PUNCT
iajs-2800	57	1	with	with	ADP
iajs-2800	57	2	mean	mean	ADJ
iajs-2800	57	3	=	=	NUM
iajs-2800	57	4	variance=	variance=	NUM
iajs-2800	57	5	θ	θ	NOUN
iajs-2800	57	6	.	.	PUNCT
iajs-2800	58	1	2.1	2.1	NUM
iajs-2800	58	2	maximum	maximum	ADJ
iajs-2800	58	3	likelihood	likelihood	NOUN
iajs-2800	58	4	estimation	estimation	NOUN
iajs-2800	58	5	(	(	PUNCT
iajs-2800	58	6	mle	mle	PROPN
iajs-2800	58	7	)	)	PUNCT
iajs-2800	58	8	the	the	DET
iajs-2800	58	9	likelihood	likelihood	NOUN
iajs-2800	58	10	function	function	NOUN
iajs-2800	58	11	for	for	ADP
iajs-2800	58	12	the	the	DET
iajs-2800	58	13	sample	sample	NOUN
iajs-2800	58	14	observation	observation	NOUN
iajs-2800	58	15	of	of	ADP
iajs-2800	58	16	the	the	DET
iajs-2800	58	17	poisson	poisson	NOUN
iajs-2800	58	18	distribution	distribution	NOUN
iajs-2800	58	19	defined	define	VERB
iajs-2800	58	20	by	by	ADP
iajs-2800	58	21	equation	equation	NOUN
iajs-2800	58	22	(	(	PUNCT
iajs-2800	58	23	1	1	X
iajs-2800	58	24	)	)	PUNCT
iajs-2800	58	25	will	will	AUX
iajs-2800	58	26	be	be	AUX
iajs-2800	58	27	as	as	SCONJ
iajs-2800	58	28	follows	follow	VERB
iajs-2800	58	29	[	[	PRON
iajs-2800	58	30	7,8	7,8	NUM
iajs-2800	58	31	]	]	X
iajs-2800	58	32	:	:	PUNCT
iajs-2800	58	33	(	(	PUNCT
iajs-2800	58	34	2	2	X
iajs-2800	58	35	)	)	PUNCT
iajs-2800	58	36	t!π	t!π	PROPN
iajs-2800	58	37	θe	θe	ADP
iajs-2800	58	38	θ	θ	PROPN
iajs-2800	58	39	)	)	PUNCT
iajs-2800	58	40	n	n	NOUN
iajs-2800	58	41	1i	1i	NOUN
iajs-2800	58	42	;	;	PUNCT
iajs-2800	58	43	n21	n21	PROPN
iajs-2800	58	44	i	i	PROPN
iajs-2800	58	45	tn	tn	PROPN
iajs-2800	58	46	1inθ	1inθ	PROPN
iajs-2800	58	47	t	t	NUM
iajs-2800	58	48	...	...	PUNCT
iajs-2800	58	49	,	,	PUNCT
iajs-2800	58	50	,	,	PUNCT
iajs-2800	58	51	t	t	PROPN
iajs-2800	58	52	,	,	PUNCT
iajs-2800	58	53	tl	tl	PROPN
iajs-2800	58	54	(	(	PUNCT
iajs-2800	58	55			NOUN
iajs-2800	58	56			PROPN
iajs-2800	58	57			VERB
iajs-2800	58	58			PROPN
iajs-2800	58	59	the	the	DET
iajs-2800	58	60	log	log	NOUN
iajs-2800	58	61	-	-	PUNCT
iajs-2800	58	62	likelihood	likelihood	NOUN
iajs-2800	58	63	function	function	NOUN
iajs-2800	58	64	l	l	NOUN
iajs-2800	58	65	)	)	PUNCT
iajs-2800	58	66	(	(	PUNCT
iajs-2800	58	67	ln	ln	ADJ
iajs-2800	58	68			NOUN
iajs-2800	58	69	,	,	PUNCT
iajs-2800	58	70	then	then	ADV
iajs-2800	58	71	the	the	DET
iajs-2800	58	72	first	first	ADJ
iajs-2800	58	73	partial	partial	ADJ
iajs-2800	58	74	derivative	derivative	NOUN
iajs-2800	58	75	of	of	ADP
iajs-2800	58	76	the	the	DET
iajs-2800	58	77	log	log	NOUN
iajs-2800	58	78	of	of	ADP
iajs-2800	58	79	the	the	DET
iajs-2800	58	80	likelihood	likelihood	NOUN
iajs-2800	58	81	l	l	NOUN
iajs-2800	58	82	with	with	ADP
iajs-2800	58	83	respect	respect	NOUN
iajs-2800	58	84	to	to	ADP
iajs-2800	58	85	θ	θ	PROPN
iajs-2800	58	86	as	as	SCONJ
iajs-2800	58	87	follows	follow	VERB
iajs-2800	59	1	0	0	NUM
iajs-2800	59	2	θ	θ	NOUN
iajs-2800	60	1	i	i	PRON
iajs-2800	60	2	t	t	PROPN
iajs-2800	60	3	--n	--n	PROPN
iajs-2800	60	4	θ	θ	PROPN
iajs-2800	60	5	logt	logt	PROPN
iajs-2800	60	6	-logθt	-logθt	NOUN
iajs-2800	60	7	i	i	PRON
iajs-2800	60	8	nθ	nθ	VERB
iajs-2800	60	9	n	n	ADV
iajs-2800	61	1	1i	1i	NOUN
iajs-2800	62	1	i	i	PRON
iajs-2800	62	2	n	n	VERB
iajs-2800	62	3	1i	1i	NOUN
iajs-2800	63	1	i	i	PRON
iajs-2800	63	2	n	n	VERB
iajs-2800	63	3	1	1	NUM
iajs-2800	63	4			NOUN
iajs-2800	63	5			X
iajs-2800	64	1			NUM
iajs-2800	64	2			ADJ
iajs-2800	64	3			NOUN
iajs-2800	64	4			NUM
iajs-2800	65	1			NUM
iajs-2800	65	2			NOUN
iajs-2800	66	1			NUM
iajs-2800	66	2			PROPN
iajs-2800	66	3			X
iajs-2800	66	4			ADJ
iajs-2800	66	5	then	then	ADV
iajs-2800	66	6	maximum	maximum	ADJ
iajs-2800	66	7	likelihood	likelihood	PROPN
iajs-2800	66	8	estimator(mle	estimator(mle	NOUN
iajs-2800	66	9	)	)	PUNCT
iajs-2800	66	10	of	of	ADP
iajs-2800	66	11	θ	θ	PROPN
iajs-2800	66	12	is	be	AUX
iajs-2800	66	13	given	give	VERB
iajs-2800	66	14	by	by	ADP
iajs-2800	66	15	(	(	PUNCT
iajs-2800	66	16	3	3	X
iajs-2800	66	17	)	)	PUNCT
iajs-2800	66	18	t	t	NOUN
iajs-2800	66	19	n	n	ADP
iajs-2800	66	20	t	t	NOUN
iajs-2800	66	21	θ	θ	X
iajs-2800	67	1	i	i	PRON
iajs-2800	67	2	n	n	VERB
iajs-2800	68	1	i	i	NOUN
iajs-2800	68	2	mle	mle	NOUN
iajs-2800	68	3	^	^	PUNCT
iajs-2800	68	4			NUM
iajs-2800	68	5			NUM
iajs-2800	68	6	2.2	2.2	NUM
iajs-2800	68	7	bayesian	bayesian	NOUN
iajs-2800	68	8	estimation	estimation	NOUN
iajs-2800	68	9	we	we	PRON
iajs-2800	68	10	derive	derive	VERB
iajs-2800	68	11	the	the	DET
iajs-2800	68	12	posterior	posterior	ADJ
iajs-2800	68	13	distribution	distribution	NOUN
iajs-2800	68	14	of	of	ADP
iajs-2800	68	15	θ	θ	PROPN
iajs-2800	68	16	under	under	ADP
iajs-2800	68	17	assuming	assume	VERB
iajs-2800	68	18	different	different	ADJ
iajs-2800	68	19	priors	prior	NOUN
iajs-2800	68	20	informative	informative	ADJ
iajs-2800	68	21	priors	prior	NOUN
iajs-2800	68	22	such	such	ADJ
iajs-2800	68	23	as	as	ADP
iajs-2800	68	24	erlang	erlang	NOUN
iajs-2800	68	25	and	and	CCONJ
iajs-2800	68	26	levy	levy	NOUN
iajs-2800	68	27	and	and	CCONJ
iajs-2800	68	28	non	non	ADJ
iajs-2800	68	29	-	-	ADJ
iajs-2800	68	30	informative	informative	ADJ
iajs-2800	68	31	prior	prior	ADV
iajs-2800	68	32	whereas	whereas	SCONJ
iajs-2800	68	33	,	,	PUNCT
iajs-2800	68	34	bayes	bayes	PROPN
iajs-2800	68	35	estimation	estimation	NOUN
iajs-2800	68	36	under	under	ADP
iajs-2800	68	37	squared	square	VERB
iajs-2800	68	38	error	error	NOUN
iajs-2800	68	39	loss	loss	NOUN
iajs-2800	68	40	function	function	NOUN
iajs-2800	68	41	and	and	CCONJ
iajs-2800	68	42	bayes	bayes	PROPN
iajs-2800	68	43	estimation	estimation	NOUN
iajs-2800	68	44	under	under	ADP
iajs-2800	68	45	the	the	DET
iajs-2800	68	46	proposed	propose	VERB
iajs-2800	68	47	loss	loss	NOUN
iajs-2800	68	48	function	function	NOUN
iajs-2800	68	49	based	base	VERB
iajs-2800	68	50	on	on	ADP
iajs-2800	68	51	different	different	ADJ
iajs-2800	68	52	priors	prior	NOUN
iajs-2800	68	53	.	.	PUNCT
iajs-2800	69	1	2.2.1	2.2.1	NUM
iajs-2800	69	2	posterior	posterior	ADJ
iajs-2800	69	3	distribution	distribution	NOUN
iajs-2800	69	4	(	(	PUNCT
iajs-2800	69	5	a	a	X
iajs-2800	69	6	)	)	PUNCT
iajs-2800	69	7	.	.	PUNCT
iajs-2800	70	1	posterior	posterior	ADJ
iajs-2800	70	2	distribution	distribution	NOUN
iajs-2800	70	3	under	under	ADP
iajs-2800	70	4	erlang	erlang	PROPN
iajs-2800	70	5	's	's	PART
iajs-2800	70	6	prior	prior	ADJ
iajs-2800	70	7	information	information	NOUN
iajs-2800	70	8	it	it	PRON
iajs-2800	70	9	is	be	AUX
iajs-2800	70	10	assumed	assume	VERB
iajs-2800	70	11	the	the	DET
iajs-2800	70	12	prior	prior	NOUN
iajs-2800	70	13	for	for	ADP
iajs-2800	70	14	an	an	DET
iajs-2800	70	15	unknown	unknown	ADJ
iajs-2800	70	16	parameter	parameter	NOUN
iajs-2800	70	17	θ	θ	PROPN
iajs-2800	70	18	is	be	AUX
iajs-2800	70	19	erlang	erlang	NOUN
iajs-2800	70	20	distribution	distribution	NOUN
iajs-2800	70	21	with	with	ADP
iajs-2800	70	22	hyperparameters	hyperparameter	NOUN
iajs-2800	70	23	)	)	PUNCT
iajs-2800	70	24	δ	δ	PROPN
iajs-2800	70	25	(	(	PUNCT
iajs-2800	70	26	as	as	SCONJ
iajs-2800	70	27	given	give	VERB
iajs-2800	70	28	below[9,10	below[9,10	NOUN
iajs-2800	70	29	]	]	PUNCT
iajs-2800	70	30	:	:	PUNCT
iajs-2800	70	31	(	(	PUNCT
iajs-2800	70	32	4	4	NUM
iajs-2800	70	33	)	)	PUNCT
iajs-2800	70	34	0	0	NUM
iajs-2800	71	1	δ	δ	PROPN
iajs-2800	71	2	,	,	PUNCT
iajs-2800	71	3	θth	θth	PROPN
iajs-2800	71	4	wi	wi	PROPN
iajs-2800	71	5	)	)	PUNCT
iajs-2800	72	1	θ	θ	PROPN
iajs-2800	72	2	δ	δ	PROPN
iajs-2800	72	3	exp(θ	exp(θ	PROPN
iajs-2800	72	4	δ	δ	PROPN
iajs-2800	72	5	)	)	PUNCT
iajs-2800	72	6	θ	θ	PROPN
iajs-2800	72	7	(	(	PUNCT
iajs-2800	72	8	k	k	NOUN
iajs-2800	72	9	2	2	NUM
iajs-2800	72	10	1	1	NUM
iajs-2800	72	11			X
iajs-2800	72	12	then	then	ADV
iajs-2800	72	13	,	,	PUNCT
iajs-2800	72	14	the	the	DET
iajs-2800	72	15	posterior	posterior	ADJ
iajs-2800	72	16	distribution	distribution	NOUN
iajs-2800	72	17	of	of	ADP
iajs-2800	72	18	θ	θ	PROPN
iajs-2800	72	19	for	for	ADP
iajs-2800	72	20	the	the	DET
iajs-2800	72	21	given	give	VERB
iajs-2800	72	22	the	the	DET
iajs-2800	72	23	data	datum	NOUN
iajs-2800	72	24	t	t	PROPN
iajs-2800	72	25	is	be	AUX
iajs-2800	72	26	given	give	VERB
iajs-2800	72	27	by	by	ADP
iajs-2800	72	28	:	:	PUNCT
iajs-2800	72	29	)	)	PUNCT
iajs-2800	72	30	(	(	PUNCT
iajs-2800	72	31	5	5	X
iajs-2800	72	32	)	)	PUNCT
iajs-2800	72	33	dθ	dθ	PROPN
iajs-2800	72	34	θ	θ	PROPN
iajs-2800	72	35	k	k	PROPN
iajs-2800	72	36	(	(	PUNCT
iajs-2800	72	37	)	)	PUNCT
iajs-2800	72	38	l(θ	l(θ	PROPN
iajs-2800	72	39	θ	θ	PROPN
iajs-2800	72	40	)	)	PUNCT
iajs-2800	73	1	θ	θ	X
iajs-2800	74	1	k	k	X
iajs-2800	74	2	(	(	PUNCT
iajs-2800	74	3	)	)	PUNCT
iajs-2800	74	4	l(θ	l(θ	PROPN
iajs-2800	74	5	t	t	PROPN
iajs-2800	74	6	)	)	PUNCT
iajs-2800	74	7	\θ	\θ	NOUN
iajs-2800	74	8	h	h	NOUN
iajs-2800	74	9	(	(	PUNCT
iajs-2800	74	10			NOUN
iajs-2800	74	11			NUM
iajs-2800	74	12	substituting	substitute	VERB
iajs-2800	74	13	equation	equation	NOUN
iajs-2800	74	14	(	(	PUNCT
iajs-2800	74	15	2	2	NUM
iajs-2800	74	16	)	)	PUNCT
iajs-2800	74	17	and	and	CCONJ
iajs-2800	74	18	equation	equation	NOUN
iajs-2800	74	19	(	(	PUNCT
iajs-2800	74	20	4	4	NUM
iajs-2800	74	21	)	)	PUNCT
iajs-2800	74	22	in	in	ADP
iajs-2800	74	23	equation	equation	NOUN
iajs-2800	74	24	(	(	PUNCT
iajs-2800	74	25	5	5	NUM
iajs-2800	74	26	)	)	PUNCT
iajs-2800	74	27	,	,	PUNCT
iajs-2800	74	28	yields	yield	VERB
iajs-2800	74	29	the	the	DET
iajs-2800	74	30	posterior	posterior	ADJ
iajs-2800	74	31	probability	probability	NOUN
iajs-2800	74	32	density	density	NOUN
iajs-2800	74	33	function	function	NOUN
iajs-2800	74	34	of	of	ADP
iajs-2800	74	35	the	the	DET
iajs-2800	74	36	shape	shape	NOUN
iajs-2800	74	37	parameter	parameter	NOUN
iajs-2800	74	38	θ	θ	PROPN
iajs-2800	74	39	as	as	ADP
iajs-2800	74	40	the	the	DET
iajs-2800	74	41	following	following	NOUN
iajs-2800	74	42	:	:	PUNCT
iajs-2800	74	43	ibn	ibn	PROPN
iajs-2800	74	44	al	al	PROPN
iajs-2800	74	45	-	-	PUNCT
iajs-2800	74	46	haitham	haitham	PROPN
iajs-2800	74	47	jour	jour	X
iajs-2800	74	48	.	.	PROPN
iajs-2800	75	1	for	for	ADP
iajs-2800	75	2	pure	pure	ADJ
iajs-2800	75	3	&	&	CCONJ
iajs-2800	75	4	appl	appl	PROPN
iajs-2800	75	5	.	.	PUNCT
iajs-2800	76	1	sci	sci	PROPN
iajs-2800	76	2	.	.	PROPN
iajs-2800	77	1	53	53	NUM
iajs-2800	77	2	(	(	PUNCT
iajs-2800	77	3	1)2022	1)2022	PROPN
iajs-2800	77	4	63	63	NUM
iajs-2800	77	5	(	(	PUNCT
iajs-2800	77	6	6	6	NUM
iajs-2800	77	7	)	)	PUNCT
iajs-2800	77	8	θ	θ	NOUN
iajs-2800	77	9	0	0	NUM
iajs-2800	77	10	)	)	PUNCT
iajs-2800	77	11	)	)	PUNCT
iajs-2800	78	1	dn	dn	NOUN
iajs-2800	78	2	(	(	PUNCT
iajs-2800	78	3	δ	δ	PROPN
iajs-2800	78	4	θ	θ	PROPN
iajs-2800	78	5	exp	exp	NOUN
iajs-2800	78	6	(	(	PUNCT
iajs-2800	78	7	1	1	NUM
iajs-2800	78	8	i	i	NOUN
iajs-2800	78	9	t	t	NOUN
iajs-2800	78	10	θ	θ	PROPN
iajs-2800	78	11	)	)	PUNCT
iajs-2800	78	12	)	)	PUNCT
iajs-2800	79	1	n	n	CCONJ
iajs-2800	79	2	(	(	PUNCT
iajs-2800	79	3	δ	δ	PROPN
iajs-2800	79	4	θ	θ	PROPN
iajs-2800	79	5	exp	exp	NOUN
iajs-2800	79	6	(	(	PUNCT
iajs-2800	79	7	1	1	NUM
iajs-2800	79	8	i	i	NOUN
iajs-2800	79	9	t	t	NOUN
iajs-2800	79	10	θ	θ	X
iajs-2800	80	1	]	]	X
iajs-2800	80	2	dθ	dθ	PROPN
iajs-2800	80	3	)	)	PUNCT
iajs-2800	80	4	θ	θ	PROPN
iajs-2800	80	5	δ	δ	PROPN
iajs-2800	80	6	exp(θ	exp(θ	PROPN
iajs-2800	80	7	δ	δ	PROPN
iajs-2800	80	8	[	[	PUNCT
iajs-2800	80	9	t!n	t!n	NOUN
iajs-2800	80	10	1i	1i	NOUN
iajs-2800	80	11	π	π	NOUN
iajs-2800	80	12	i	i	PRON
iajs-2800	80	13	tθ	tθ	VERB
iajs-2800	80	14	θ)exp(-n	θ)exp(-n	NOUN
iajs-2800	80	15	0	0	NUM
iajs-2800	80	16	]	]	PUNCT
iajs-2800	80	17	)	)	PUNCT
iajs-2800	80	18	θ	θ	PROPN
iajs-2800	80	19	δ	δ	PROPN
iajs-2800	80	20	exp	exp	PROPN
iajs-2800	80	21	(	(	PUNCT
iajs-2800	80	22	θδ	θδ	ADP
iajs-2800	80	23	[	[	PUNCT
iajs-2800	80	24	t!π	t!π	PROPN
iajs-2800	80	25	i	i	PRON
iajs-2800	80	26	t	t	NOUN
iajs-2800	80	27	θ	θ	PROPN
iajs-2800	80	28	θ)exp(-n	θ)exp(-n	PROPN
iajs-2800	80	29	t	t	PROPN
iajs-2800	80	30	)	)	PUNCT
iajs-2800	80	31	\θ	\θ	NOUN
iajs-2800	80	32	(	(	PUNCT
iajs-2800	80	33	h	h	NOUN
iajs-2800	80	34	n	n	CCONJ
iajs-2800	80	35	n	n	CCONJ
iajs-2800	80	36	2	2	NUM
iajs-2800	80	37	n	n	SYM
iajs-2800	80	38	2	2	NUM
iajs-2800	80	39	n	n	NUM
iajs-2800	80	40	1i	1i	NOUN
iajs-2800	80	41	1i	1i	NOUN
iajs-2800	80	42	1i	1i	NOUN
iajs-2800	80	43	n	n	PRON
iajs-2800	80	44	1i	1i	NOUN
iajs-2800	80	45	1i	1i	NOUN
iajs-2800	80	46	1	1	NUM
iajs-2800	80	47			NOUN
iajs-2800	80	48			VERB
iajs-2800	80	49			PROPN
iajs-2800	80	50			NOUN
iajs-2800	80	51			PROPN
iajs-2800	80	52			VERB
iajs-2800	80	53			PROPN
iajs-2800	80	54			NOUN
iajs-2800	80	55			X
iajs-2800	80	56			PUNCT
iajs-2800	80	57			VERB
iajs-2800	80	58			X
iajs-2800	81	1			NUM
iajs-2800	82	1			NUM
iajs-2800	82	2			PRON
iajs-2800	83	1			PRON
iajs-2800	83	2			NUM
iajs-2800	83	3			PROPN
iajs-2800	83	4	rewrite	rewrite	PROPN
iajs-2800	83	5	12)t(1	12)t(1	NUM
iajs-2800	83	6	t	t	NOUN
iajs-2800	84	1	i	i	PRON
iajs-2800	85	1	n	n	CCONJ
iajs-2800	85	2	1ii	1ii	ADJ
iajs-2800	85	3	n	n	CCONJ
iajs-2800	85	4	1i	1i	NOUN
iajs-2800	85	5			NUM
iajs-2800	85	6			NUM
iajs-2800	85	7	and	and	CCONJ
iajs-2800	85	8	by	by	ADP
iajs-2800	85	9	multiplying	multiply	VERB
iajs-2800	85	10	the	the	DET
iajs-2800	85	11	integral	integral	ADJ
iajs-2800	85	12	in	in	ADP
iajs-2800	85	13	equation	equation	NOUN
iajs-2800	85	14	(	(	PUNCT
iajs-2800	85	15	6	6	NUM
iajs-2800	85	16	)	)	PUNCT
iajs-2800	85	17	by	by	ADP
iajs-2800	85	18	the	the	DET
iajs-2800	85	19	quantity	quantity	NOUN
iajs-2800	85	20	which	which	PRON
iajs-2800	85	21	equals	equal	VERB
iajs-2800	85	22	to	to	PART
iajs-2800	85	23	)	)	PUNCT
iajs-2800	86	1	i	i	PRON
iajs-2800	86	2	t	t	PROPN
iajs-2800	86	3	)	)	PUNCT
iajs-2800	87	1	n	n	CCONJ
iajs-2800	87	2	(	(	PUNCT
iajs-2800	87	3	δ	δ	NOUN
iajs-2800	87	4	2	2	X
iajs-2800	87	5	)	)	PUNCT
iajs-2800	87	6	i	i	PRON
iajs-2800	87	7	tγ	tγ	VERB
iajs-2800	87	8	(	(	PUNCT
iajs-2800	87	9	(	(	PUNCT
iajs-2800	87	10	)	)	PUNCT
iajs-2800	87	11	2	2	X
iajs-2800	87	12	)	)	PUNCT
iajs-2800	87	13	i	i	PRON
iajs-2800	87	14	tγ	tγ	VERB
iajs-2800	87	15	(	(	PUNCT
iajs-2800	87	16	i	i	NOUN
iajs-2800	87	17	t	t	PROPN
iajs-2800	87	18	)	)	PUNCT
iajs-2800	87	19	n	n	CCONJ
iajs-2800	87	20	(	(	PUNCT
iajs-2800	87	21	δ	δ	PROPN
iajs-2800	87	22	(	(	PUNCT
iajs-2800	87	23	2	2	NUM
iajs-2800	87	24	)	)	PUNCT
iajs-2800	87	25	(	(	PUNCT
iajs-2800	87	26	2	2	NUM
iajs-2800	87	27	)	)	PUNCT
iajs-2800	87	28	(	(	PUNCT
iajs-2800	87	29	n	n	NOUN
iajs-2800	87	30	1i	1i	NUM
iajs-2800	87	31	n	n	NOUN
iajs-2800	87	32	1i	1i	NOUN
iajs-2800	87	33	n	n	NOUN
iajs-2800	88	1	1i	1i	NOUN
iajs-2800	89	1	n	n	PROPN
iajs-2800	89	2	1i	1i	NOUN
iajs-2800	89	3			ADV
iajs-2800	89	4			VERB
iajs-2800	89	5			X
iajs-2800	89	6			PUNCT
iajs-2800	89	7			NOUN
iajs-2800	89	8			PROPN
iajs-2800	89	9			X
iajs-2800	89	10			VERB
iajs-2800	89	11			PROPN
iajs-2800	90	1			ADJ
iajs-2800	90	2			ADJ
iajs-2800	91	1			NOUN
iajs-2800	91	2	,	,	PUNCT
iajs-2800	91	3	where	where	SCONJ
iajs-2800	91	4	)	)	PUNCT
iajs-2800	91	5	γ	γ	X
iajs-2800	91	6	(	(	PUNCT
iajs-2800	91	7	.	.	PUNCT
iajs-2800	91	8	is	be	AUX
iajs-2800	91	9	a	a	DET
iajs-2800	91	10	gamma	gamma	NOUN
iajs-2800	91	11	function	function	NOUN
iajs-2800	91	12	.after	.after	PUNCT
iajs-2800	92	1	some	some	DET
iajs-2800	92	2	simplification	simplification	NOUN
iajs-2800	92	3	,	,	PUNCT
iajs-2800	92	4	it	it	PRON
iajs-2800	92	5	yields	yield	VERB
iajs-2800	92	6	(	(	PUNCT
iajs-2800	92	7	7	7	NUM
iajs-2800	92	8	)	)	PUNCT
iajs-2800	92	9	)	)	PUNCT
iajs-2800	92	10	)	)	PUNCT
iajs-2800	93	1	n	n	CCONJ
iajs-2800	93	2	(	(	PUNCT
iajs-2800	93	3	δ	δ	PROPN
iajs-2800	93	4	θ	θ	PROPN
iajs-2800	93	5	exp	exp	NOUN
iajs-2800	93	6	(	(	PUNCT
iajs-2800	93	7	θ	θ	PROPN
iajs-2800	93	8	θ),a(t	θ),a(t	PART
iajs-2800	93	9	2)t	2)t	NUM
iajs-2800	93	10	γ	γ	X
iajs-2800	93	11	(	(	PUNCT
iajs-2800	93	12	t	t	PROPN
iajs-2800	93	13	)	)	PUNCT
iajs-2800	93	14	n	n	CCONJ
iajs-2800	93	15	(	(	PUNCT
iajs-2800	93	16	δ	δ	PROPN
iajs-2800	93	17	t	t	PROPN
iajs-2800	93	18	)	)	PUNCT
iajs-2800	93	19	\θ	\θ	NOUN
iajs-2800	93	20	(	(	PUNCT
iajs-2800	93	21	h	h	NOUN
iajs-2800	93	22	1)2	1)2	NUM
iajs-2800	93	23	(	(	PUNCT
iajs-2800	93	24	2	2	NUM
iajs-2800	93	25	)	)	PUNCT
iajs-2800	93	26	(	(	PUNCT
iajs-2800	93	27	i	i	PRON
iajs-2800	93	28	n	n	VERB
iajs-2800	94	1	1i	1i	NOUN
iajs-2800	94	2	t	t	NOUN
iajs-2800	95	1	i	i	PRON
iajs-2800	95	2	n	n	VERB
iajs-2800	95	3	1i	1i	NOUN
iajs-2800	96	1	i	i	PRON
iajs-2800	96	2	n	n	VERB
iajs-2800	96	3	1i	1i	NOUN
iajs-2800	96	4	1	1	NUM
iajs-2800	96	5			PROPN
iajs-2800	96	6			PROPN
iajs-2800	96	7			X
iajs-2800	96	8			VERB
iajs-2800	96	9			PROPN
iajs-2800	96	10			PROPN
iajs-2800	96	11			X
iajs-2800	96	12			X
iajs-2800	97	1			NUM
iajs-2800	98	1			NUM
iajs-2800	98	2			INTJ
iajs-2800	98	3	where	where	SCONJ
iajs-2800	98	4	1dθ	1dθ	ADJ
iajs-2800	98	5	)	)	PUNCT
iajs-2800	98	6	)	)	PUNCT
iajs-2800	99	1	n	n	CCONJ
iajs-2800	99	2	(	(	PUNCT
iajs-2800	99	3	δ	δ	PROPN
iajs-2800	99	4	θ	θ	PROPN
iajs-2800	99	5	exp	exp	NOUN
iajs-2800	99	6	(	(	PUNCT
iajs-2800	99	7	θ	θ	PROPN
iajs-2800	99	8	2)tγ	2)tγ	PROPN
iajs-2800	99	9	(	(	PUNCT
iajs-2800	99	10	t	t	PROPN
iajs-2800	99	11	)	)	PUNCT
iajs-2800	99	12	n	n	CCONJ
iajs-2800	99	13	(	(	PUNCT
iajs-2800	99	14	δ	δ	PROPN
iajs-2800	99	15	0	0	NUM
iajs-2800	99	16	θ)a(t	θ)a(t	ADJ
iajs-2800	99	17	,	,	PUNCT
iajs-2800	99	18	1)2	1)2	NUM
iajs-2800	99	19	(	(	PUNCT
iajs-2800	99	20	2	2	NUM
iajs-2800	99	21	)	)	PUNCT
iajs-2800	99	22	(	(	PUNCT
iajs-2800	99	23	i	i	PRON
iajs-2800	99	24	n	n	VERB
iajs-2800	100	1	1i	1i	NOUN
iajs-2800	100	2	t	t	NOUN
iajs-2800	101	1	i	i	PRON
iajs-2800	101	2	n	n	VERB
iajs-2800	101	3	1i	1i	NOUN
iajs-2800	101	4	i	i	PRON
iajs-2800	101	5	n	n	VERB
iajs-2800	101	6	1i	1i	X
iajs-2800	101	7			VERB
iajs-2800	101	8			PROPN
iajs-2800	101	9			X
iajs-2800	101	10			X
iajs-2800	101	11			PUNCT
iajs-2800	101	12			VERB
iajs-2800	101	13			PRON
iajs-2800	101	14			PROPN
iajs-2800	101	15			X
iajs-2800	101	16			X
iajs-2800	102	1			NOUN
iajs-2800	103	1			ADJ
iajs-2800	103	2			ADJ
iajs-2800	103	3	.	.	PUNCT
iajs-2800	104	1	be	be	AUX
iajs-2800	104	2	the	the	DET
iajs-2800	104	3	integral	integral	ADJ
iajs-2800	104	4	of	of	ADP
iajs-2800	104	5	the	the	DET
iajs-2800	104	6	pdf	pdf	NOUN
iajs-2800	104	7	of	of	ADP
iajs-2800	104	8	gamma	gamma	NOUN
iajs-2800	104	9	distribution	distribution	NOUN
iajs-2800	104	10	[	[	X
iajs-2800	104	11	11	11	NUM
iajs-2800	104	12	]	]	PUNCT
iajs-2800	104	13	.	.	PUNCT
iajs-2800	105	1	then	then	ADV
iajs-2800	105	2	the	the	DET
iajs-2800	105	3	posterior	posterior	ADJ
iajs-2800	105	4	distribution	distribution	NOUN
iajs-2800	105	5	of	of	ADP
iajs-2800	105	6	θ	θ	PROPN
iajs-2800	105	7	is	be	AUX
iajs-2800	105	8	gamma	gamma	NOUN
iajs-2800	105	9	distribution	distribution	NOUN
iajs-2800	105	10	as	as	ADP
iajs-2800	105	11	(	(	PUNCT
iajs-2800	105	12	8)	8)	NUM
iajs-2800	105	13	0n	0n	NOUN
iajs-2800	105	14	,	,	PUNCT
iajs-2800	105	15	δ	δ	PROPN
iajs-2800	105	16	,	,	PUNCT
iajs-2800	105	17	0θ	0θ	NOUN
iajs-2800	105	18	,	,	PUNCT
iajs-2800	105	19	)	)	PUNCT
iajs-2800	105	20	)	)	PUNCT
iajs-2800	106	1	n	n	CCONJ
iajs-2800	106	2	(	(	PUNCT
iajs-2800	106	3	δ	δ	PROPN
iajs-2800	106	4	θ	θ	PROPN
iajs-2800	106	5	exp	exp	NOUN
iajs-2800	106	6	(	(	PUNCT
iajs-2800	106	7	θ	θ	PROPN
iajs-2800	106	8	2)tγ	2)tγ	PROPN
iajs-2800	106	9	(	(	PUNCT
iajs-2800	106	10	t	t	PROPN
iajs-2800	106	11	)	)	PUNCT
iajs-2800	106	12	n	n	CCONJ
iajs-2800	106	13	(	(	PUNCT
iajs-2800	106	14	δ	δ	PROPN
iajs-2800	106	15	t	t	PROPN
iajs-2800	106	16	)	)	PUNCT
iajs-2800	106	17	\θ	\θ	NOUN
iajs-2800	106	18	(	(	PUNCT
iajs-2800	106	19	h	h	NOUN
iajs-2800	106	20	1)2	1)2	NUM
iajs-2800	106	21	(	(	PUNCT
iajs-2800	106	22	2	2	NUM
iajs-2800	106	23	)	)	PUNCT
iajs-2800	106	24	(	(	PUNCT
iajs-2800	106	25	i	i	PRON
iajs-2800	106	26	n	n	VERB
iajs-2800	107	1	1i	1i	NOUN
iajs-2800	107	2	t	t	NOUN
iajs-2800	108	1	i	i	PRON
iajs-2800	108	2	n	n	VERB
iajs-2800	108	3	1i	1i	NOUN
iajs-2800	109	1	i	i	PRON
iajs-2800	109	2	n	n	VERB
iajs-2800	109	3	1i	1i	NUM
iajs-2800	109	4	1	1	NUM
iajs-2800	109	5			NOUN
iajs-2800	109	6			NOUN
iajs-2800	109	7			X
iajs-2800	109	8			VERB
iajs-2800	109	9			PROPN
iajs-2800	109	10			PROPN
iajs-2800	109	11			X
iajs-2800	109	12			X
iajs-2800	110	1			NUM
iajs-2800	111	1			NUM
iajs-2800	111	2			NOUN
iajs-2800	111	3	i.e.	i.e.	X
iajs-2800	111	4	)	)	PUNCT
iajs-2800	111	5	)	)	PUNCT
iajs-2800	112	1	n	n	CCONJ
iajs-2800	112	2	(	(	PUNCT
iajs-2800	112	3	δ2),t	δ2),t	ADP
iajs-2800	112	4	gamma	gamma	PROPN
iajs-2800	112	5	(	(	PUNCT
iajs-2800	112	6	(	(	PUNCT
iajs-2800	112	7	)	)	PUNCT
iajs-2800	112	8	t	t	PROPN
iajs-2800	112	9	\θ	\θ	NOUN
iajs-2800	112	10	(	(	PUNCT
iajs-2800	112	11	i	i	NOUN
iajs-2800	112	12	n	n	VERB
iajs-2800	112	13	1i	1i	NUM
iajs-2800	112	14			ADP
iajs-2800	112	15			NOUN
iajs-2800	112	16	with	with	ADP
iajs-2800	112	17	posterior	posterior	ADJ
iajs-2800	112	18	mean	mean	NOUN
iajs-2800	112	19	is	be	AUX
iajs-2800	112	20	)	)	PUNCT
iajs-2800	112	21	n	n	X
iajs-2800	112	22	(	(	PUNCT
iajs-2800	112	23	δ	δ	PROPN
iajs-2800	112	24	2)t	2)t	PROPN
iajs-2800	112	25	(	(	PUNCT
iajs-2800	112	26	)	)	PUNCT
iajs-2800	112	27	t	t	PROPN
iajs-2800	112	28	\θ	\θ	NOUN
iajs-2800	112	29	e	e	NOUN
iajs-2800	112	30	(	(	PUNCT
iajs-2800	112	31	i	i	NOUN
iajs-2800	112	32	n	n	PROPN
iajs-2800	112	33	1i	1i	NUM
iajs-2800	112	34			PUNCT
iajs-2800	112	35			VERB
iajs-2800	112	36			PROPN
iajs-2800	112	37			ADJ
iajs-2800	112	38	and	and	CCONJ
iajs-2800	112	39	posterior	posterior	ADJ
iajs-2800	112	40	variance	variance	NOUN
iajs-2800	112	41	is	be	AUX
iajs-2800	112	42	2)n	2)n	NUM
iajs-2800	112	43	(	(	PUNCT
iajs-2800	112	44	δ	δ	PROPN
iajs-2800	112	45	2)t	2)t	PROPN
iajs-2800	112	46	(	(	PUNCT
iajs-2800	112	47	)	)	PUNCT
iajs-2800	112	48	t	t	PROPN
iajs-2800	112	49	\θ	\θ	NOUN
iajs-2800	112	50	var	var	NOUN
iajs-2800	112	51	(	(	PUNCT
iajs-2800	112	52	i	i	NOUN
iajs-2800	112	53	n	n	VERB
iajs-2800	112	54	1i	1i	NUM
iajs-2800	112	55			PUNCT
iajs-2800	112	56			VERB
iajs-2800	112	57			PROPN
iajs-2800	112	58			NOUN
iajs-2800	112	59	.	.	PUNCT
iajs-2800	113	1	(	(	PUNCT
iajs-2800	113	2	b	b	NOUN
iajs-2800	113	3	)	)	PUNCT
iajs-2800	113	4	.	.	PUNCT
iajs-2800	114	1	posterior	posterior	ADJ
iajs-2800	114	2	distribution	distribution	NOUN
iajs-2800	114	3	under	under	ADP
iajs-2800	114	4	inverse	inverse	NOUN
iajs-2800	114	5	levy	levy	NOUN
iajs-2800	114	6	's	's	PART
iajs-2800	114	7	prior	prior	ADJ
iajs-2800	114	8	information	information	NOUN
iajs-2800	114	9	it	it	PRON
iajs-2800	114	10	is	be	AUX
iajs-2800	114	11	assumed	assume	VERB
iajs-2800	114	12	the	the	DET
iajs-2800	114	13	prior	prior	NOUN
iajs-2800	114	14	for	for	ADP
iajs-2800	114	15	an	an	DET
iajs-2800	114	16	unknown	unknown	ADJ
iajs-2800	114	17	parameter	parameter	NOUN
iajs-2800	114	18	θ	θ	PROPN
iajs-2800	114	19	is	be	AUX
iajs-2800	114	20	inverse	inverse	ADJ
iajs-2800	114	21	levy	levy	NOUN
iajs-2800	114	22	distribution	distribution	NOUN
iajs-2800	114	23	with	with	ADP
iajs-2800	114	24	hyperparameters	hyperparameter	NOUN
iajs-2800	114	25	(	(	PUNCT
iajs-2800	114	26	v	v	NOUN
iajs-2800	114	27	)	)	PUNCT
iajs-2800	114	28	as	as	SCONJ
iajs-2800	114	29	given	give	VERB
iajs-2800	114	30	below[9,12	below[9,12	PROPN
iajs-2800	114	31	]	]	PUNCT
iajs-2800	114	32	:	:	PUNCT
iajs-2800	114	33	(	(	PUNCT
iajs-2800	114	34	9	9	NUM
iajs-2800	114	35	)	)	PUNCT
iajs-2800	114	36	0	0	NUM
iajs-2800	114	37	v	v	NOUN
iajs-2800	114	38	,	,	PUNCT
iajs-2800	114	39	θth	θth	PROPN
iajs-2800	114	40	wi	wi	PROPN
iajs-2800	114	41	)	)	PUNCT
iajs-2800	115	1	θ	θ	PROPN
iajs-2800	115	2	2	2	NUM
iajs-2800	115	3	v	v	ADP
iajs-2800	115	4	exp(θ	exp(θ	PROPN
iajs-2800	115	5	2π	2π	PROPN
iajs-2800	115	6	v	v	NOUN
iajs-2800	115	7	)	)	PUNCT
iajs-2800	115	8	θ	θ	PROPN
iajs-2800	115	9	(	(	PUNCT
iajs-2800	115	10	k	k	NOUN
iajs-2800	115	11	2	2	NUM
iajs-2800	115	12	1	1	NUM
iajs-2800	115	13	2	2	NUM
iajs-2800	115	14			PROPN
iajs-2800	115	15			NOUN
iajs-2800	115	16	substituting	substitute	VERB
iajs-2800	115	17	equation	equation	NOUN
iajs-2800	115	18	(	(	PUNCT
iajs-2800	115	19	2	2	NUM
iajs-2800	115	20	)	)	PUNCT
iajs-2800	115	21	and	and	CCONJ
iajs-2800	115	22	equation	equation	NOUN
iajs-2800	115	23	(	(	PUNCT
iajs-2800	115	24	9	9	NUM
iajs-2800	115	25	)	)	PUNCT
iajs-2800	115	26	in	in	ADP
iajs-2800	115	27	equation	equation	NOUN
iajs-2800	115	28	(	(	PUNCT
iajs-2800	115	29	5	5	X
iajs-2800	115	30	)	)	PUNCT
iajs-2800	115	31	yields	yield	VERB
iajs-2800	115	32	the	the	DET
iajs-2800	115	33	posterior	posterior	ADJ
iajs-2800	115	34	probability	probability	NOUN
iajs-2800	115	35	density	density	NOUN
iajs-2800	115	36	function	function	NOUN
iajs-2800	115	37	of	of	ADP
iajs-2800	115	38	the	the	DET
iajs-2800	115	39	shape	shape	NOUN
iajs-2800	115	40	parameter	parameter	NOUN
iajs-2800	115	41	θ	θ	PROPN
iajs-2800	115	42	like	like	ADP
iajs-2800	115	43	the	the	DET
iajs-2800	115	44	following	following	NOUN
iajs-2800	115	45	:	:	PUNCT
iajs-2800	115	46	]	]	X
iajs-2800	116	1	dθ	dθ	NOUN
iajs-2800	116	2	)	)	PUNCT
iajs-2800	116	3	θ	θ	PROPN
iajs-2800	116	4	2	2	NUM
iajs-2800	116	5	v	v	NOUN
iajs-2800	116	6	exp(2	exp(2	NOUN
iajs-2800	116	7	1	1	NUM
iajs-2800	116	8	θ	θ	PROPN
iajs-2800	116	9	2π	2π	NUM
iajs-2800	116	10	v	v	ADP
iajs-2800	116	11	[	[	PUNCT
iajs-2800	116	12	t!n	t!n	NOUN
iajs-2800	116	13	1i	1i	NOUN
iajs-2800	116	14	π	π	NOUN
iajs-2800	116	15	i	i	PRON
iajs-2800	116	16	t	t	VERB
iajs-2800	116	17	θ	θ	PROPN
iajs-2800	116	18	θ)exp(-n	θ)exp(-n	NOUN
iajs-2800	116	19	0	0	NUM
iajs-2800	116	20	]	]	PUNCT
iajs-2800	116	21	)	)	PUNCT
iajs-2800	117	1	θ	θ	PROPN
iajs-2800	117	2	2	2	NUM
iajs-2800	117	3	v	v	NOUN
iajs-2800	117	4	exp(2	exp(2	NOUN
iajs-2800	117	5	1	1	NUM
iajs-2800	117	6	θ	θ	PROPN
iajs-2800	117	7	2π	2π	NUM
iajs-2800	117	8	v	v	ADP
iajs-2800	117	9	[	[	PUNCT
iajs-2800	117	10	t!n	t!n	NOUN
iajs-2800	117	11	1i	1i	NOUN
iajs-2800	118	1	π	π	NOUN
iajs-2800	118	2	i	i	PRON
iajs-2800	118	3	t	t	NOUN
iajs-2800	118	4	θ	θ	PROPN
iajs-2800	118	5	θ)exp(-n	θ)exp(-n	PROPN
iajs-2800	118	6	t	t	PROPN
iajs-2800	118	7	)	)	PUNCT
iajs-2800	118	8	\θ	\θ	NOUN
iajs-2800	118	9	(	(	PUNCT
iajs-2800	118	10	h	h	NOUN
iajs-2800	118	11	n	n	PROPN
iajs-2800	118	12	1i	1i	NUM
iajs-2800	118	13	n	n	NOUN
iajs-2800	118	14	1i	1i	NUM
iajs-2800	118	15	2	2	NUM
iajs-2800	118	16			NOUN
iajs-2800	118	17			NOUN
iajs-2800	118	18			X
iajs-2800	118	19			PUNCT
iajs-2800	118	20			VERB
iajs-2800	118	21			PROPN
iajs-2800	118	22			NOUN
iajs-2800	118	23			X
iajs-2800	119	1			NUM
iajs-2800	120	1			NUM
iajs-2800	120	2			PROPN
iajs-2800	120	3	ibn	ibn	PROPN
iajs-2800	120	4	al	al	PROPN
iajs-2800	120	5	-	-	PUNCT
iajs-2800	120	6	haitham	haitham	PROPN
iajs-2800	120	7	jour	jour	X
iajs-2800	120	8	.	.	PROPN
iajs-2800	121	1	for	for	ADP
iajs-2800	121	2	pure	pure	ADJ
iajs-2800	121	3	&	&	CCONJ
iajs-2800	121	4	appl	appl	PROPN
iajs-2800	121	5	.	.	PUNCT
iajs-2800	122	1	sci	sci	PROPN
iajs-2800	122	2	.	.	PROPN
iajs-2800	123	1	53	53	NUM
iajs-2800	123	2	(	(	PUNCT
iajs-2800	123	3	1)2022	1)2022	PROPN
iajs-2800	123	4	64	64	NUM
iajs-2800	123	5	)	)	PUNCT
iajs-2800	123	6	10	10	NUM
iajs-2800	123	7	(	(	PUNCT
iajs-2800	123	8	θ	θ	NOUN
iajs-2800	123	9	0	0	NUM
iajs-2800	123	10	)	)	PUNCT
iajs-2800	123	11	)	)	PUNCT
iajs-2800	124	1	dn	dn	ADP
iajs-2800	124	2	2	2	NUM
iajs-2800	124	3	v	v	NOUN
iajs-2800	124	4	(	(	PUNCT
iajs-2800	124	5	θ	θ	PROPN
iajs-2800	124	6	exp(2	exp(2	NOUN
iajs-2800	124	7	1	1	NUM
iajs-2800	125	1	i	i	PRON
iajs-2800	125	2	t	t	X
iajs-2800	125	3	θ	θ	PROPN
iajs-2800	125	4	)	)	PUNCT
iajs-2800	125	5	)	)	PUNCT
iajs-2800	126	1	n	n	CCONJ
iajs-2800	126	2	2	2	NUM
iajs-2800	126	3	v	v	NOUN
iajs-2800	126	4	(	(	PUNCT
iajs-2800	126	5	θ	θ	PROPN
iajs-2800	126	6	exp(2	exp(2	NOUN
iajs-2800	126	7	1	1	NUM
iajs-2800	127	1	i	i	PRON
iajs-2800	127	2	t	t	NOUN
iajs-2800	127	3	θ	θ	PROPN
iajs-2800	127	4	t	t	PROPN
iajs-2800	127	5	)	)	PUNCT
iajs-2800	127	6	\θ	\θ	NOUN
iajs-2800	127	7	(	(	PUNCT
iajs-2800	127	8	h	h	NOUN
iajs-2800	127	9	n	n	PROPN
iajs-2800	127	10	1i	1i	NUM
iajs-2800	127	11	n	n	NOUN
iajs-2800	127	12	1i	1i	NOUN
iajs-2800	127	13	2	2	NUM
iajs-2800	127	14			NOUN
iajs-2800	127	15			VERB
iajs-2800	127	16			NOUN
iajs-2800	128	1			X
iajs-2800	128	2			PROPN
iajs-2800	128	3			PROPN
iajs-2800	128	4			PROPN
iajs-2800	128	5			NUM
iajs-2800	128	6	rewrite	rewrite	PROPN
iajs-2800	128	7	1	1	NUM
iajs-2800	128	8	)	)	PUNCT
iajs-2800	128	9	2	2	NUM
iajs-2800	128	10	1	1	NUM
iajs-2800	128	11	t	t	PROPN
iajs-2800	128	12	(	(	PUNCT
iajs-2800	128	13	2	2	NUM
iajs-2800	128	14	1	1	NUM
iajs-2800	128	15	t	t	NOUN
iajs-2800	128	16	i	i	PRON
iajs-2800	128	17	n	n	CCONJ
iajs-2800	128	18	1ii	1ii	ADJ
iajs-2800	128	19	n	n	CCONJ
iajs-2800	128	20	1i	1i	NUM
iajs-2800	128	21			NOUN
iajs-2800	128	22			NUM
iajs-2800	128	23	and	and	CCONJ
iajs-2800	128	24	by	by	ADP
iajs-2800	128	25	multiplying	multiply	VERB
iajs-2800	128	26	the	the	DET
iajs-2800	128	27	integral	integral	ADJ
iajs-2800	128	28	in	in	ADP
iajs-2800	128	29	equation	equation	NOUN
iajs-2800	128	30	(	(	PUNCT
iajs-2800	128	31	10	10	NUM
iajs-2800	128	32	)	)	PUNCT
iajs-2800	128	33	by	by	ADP
iajs-2800	128	34	the	the	DET
iajs-2800	128	35	quantity	quantity	NOUN
iajs-2800	128	36	which	which	PRON
iajs-2800	128	37	equals	equal	VERB
iajs-2800	128	38	to	to	PART
iajs-2800	128	39	)	)	PUNCT
iajs-2800	129	1	i	i	PRON
iajs-2800	129	2	t	t	PROPN
iajs-2800	129	3	)	)	PUNCT
iajs-2800	130	1	n	n	CCONJ
iajs-2800	130	2	(	(	PUNCT
iajs-2800	130	3	0.5v	0.5v	NUM
iajs-2800	130	4	)	)	PUNCT
iajs-2800	130	5	5.0	5.0	NUM
iajs-2800	131	1	i	i	PRON
iajs-2800	131	2	tγ	tγ	VERB
iajs-2800	131	3	(	(	PUNCT
iajs-2800	131	4	(	(	PUNCT
iajs-2800	131	5	)	)	PUNCT
iajs-2800	131	6	)	)	PUNCT
iajs-2800	132	1	5.0	5.0	NUM
iajs-2800	133	1	i	i	PRON
iajs-2800	133	2	tγ	tγ	VERB
iajs-2800	133	3	(	(	PUNCT
iajs-2800	133	4	i	i	NOUN
iajs-2800	133	5	t	t	PROPN
iajs-2800	133	6	)	)	PUNCT
iajs-2800	133	7	n	n	CCONJ
iajs-2800	133	8	(	(	PUNCT
iajs-2800	133	9	0.5v	0.5v	NUM
iajs-2800	133	10	(	(	PUNCT
iajs-2800	133	11	)	)	PUNCT
iajs-2800	133	12	5.0n	5.0n	NUM
iajs-2800	133	13	1i	1i	NOUN
iajs-2800	133	14	(	(	PUNCT
iajs-2800	133	15	n	n	NOUN
iajs-2800	133	16	1i	1i	NOUN
iajs-2800	133	17	n	n	NOUN
iajs-2800	133	18	1i	1i	NOUN
iajs-2800	133	19	)	)	PUNCT
iajs-2800	134	1	5.0n	5.0n	NUM
iajs-2800	134	2	1i	1i	NOUN
iajs-2800	134	3	(	(	PUNCT
iajs-2800	134	4			VERB
iajs-2800	134	5			PROPN
iajs-2800	134	6			NUM
iajs-2800	134	7			NOUN
iajs-2800	134	8			ADV
iajs-2800	134	9			X
iajs-2800	134	10			X
iajs-2800	134	11			ADV
iajs-2800	134	12			NOUN
iajs-2800	134	13			PROPN
iajs-2800	134	14			X
iajs-2800	134	15			X
iajs-2800	134	16	,	,	PUNCT
iajs-2800	134	17	where	where	SCONJ
iajs-2800	134	18	)	)	PUNCT
iajs-2800	134	19	γ	γ	X
iajs-2800	134	20	(	(	PUNCT
iajs-2800	134	21	.	.	PUNCT
iajs-2800	134	22	is	be	AUX
iajs-2800	134	23	a	a	DET
iajs-2800	134	24	gamma	gamma	NOUN
iajs-2800	134	25	function	function	NOUN
iajs-2800	134	26	.after	.after	PUNCT
iajs-2800	135	1	some	some	DET
iajs-2800	135	2	simplification	simplification	NOUN
iajs-2800	135	3	,	,	PUNCT
iajs-2800	135	4	it	it	PRON
iajs-2800	135	5	yields	yield	VERB
iajs-2800	135	6	(	(	PUNCT
iajs-2800	135	7	11	11	NUM
iajs-2800	135	8	)	)	PUNCT
iajs-2800	135	9	)	)	PUNCT
iajs-2800	135	10	)	)	PUNCT
iajs-2800	136	1	n	n	CCONJ
iajs-2800	136	2	(	(	PUNCT
iajs-2800	136	3	0.5v	0.5v	NUM
iajs-2800	136	4	θ	θ	PROPN
iajs-2800	136	5	exp	exp	NOUN
iajs-2800	136	6	(	(	PUNCT
iajs-2800	136	7	θ	θ	PROPN
iajs-2800	136	8	θ),)a1(t	θ),)a1(t	ADV
iajs-2800	136	9	5.0	5.0	NUM
iajs-2800	137	1	i	i	PRON
iajs-2800	137	2	tγ	tγ	VERB
iajs-2800	137	3	(	(	PUNCT
iajs-2800	137	4	i	i	NOUN
iajs-2800	137	5	t	t	PROPN
iajs-2800	137	6	)	)	PUNCT
iajs-2800	137	7	n	n	CCONJ
iajs-2800	137	8	(	(	PUNCT
iajs-2800	137	9	0.5v	0.5v	NUM
iajs-2800	137	10	t	t	PROPN
iajs-2800	137	11	)	)	PUNCT
iajs-2800	137	12	\θ	\θ	NOUN
iajs-2800	137	13	(	(	PUNCT
iajs-2800	137	14	h	h	NOUN
iajs-2800	137	15	1)5.0	1)5.0	PROPN
iajs-2800	137	16	(	(	PUNCT
iajs-2800	137	17	n	n	NOUN
iajs-2800	137	18	)	)	PUNCT
iajs-2800	138	1	5.0n	5.0n	NUM
iajs-2800	138	2	(	(	PUNCT
iajs-2800	138	3	i	i	NOUN
iajs-2800	138	4	n	n	VERB
iajs-2800	138	5	1i	1i	NOUN
iajs-2800	138	6	t	t	NOUN
iajs-2800	138	7	1i	1i	NOUN
iajs-2800	138	8	1i	1i	NOUN
iajs-2800	138	9	2	2	NUM
iajs-2800	138	10			PROPN
iajs-2800	138	11			VERB
iajs-2800	138	12			X
iajs-2800	138	13			VERB
iajs-2800	138	14			PROPN
iajs-2800	138	15			PROPN
iajs-2800	138	16			X
iajs-2800	138	17			X
iajs-2800	139	1			NUM
iajs-2800	140	1			NUM
iajs-2800	140	2			INTJ
iajs-2800	140	3	where	where	SCONJ
iajs-2800	140	4	1dθ	1dθ	ADJ
iajs-2800	140	5	)	)	PUNCT
iajs-2800	140	6	)	)	PUNCT
iajs-2800	141	1	n	n	CCONJ
iajs-2800	141	2	(	(	PUNCT
iajs-2800	141	3	0.5v	0.5v	NUM
iajs-2800	141	4	θ	θ	PROPN
iajs-2800	141	5	exp	exp	NOUN
iajs-2800	141	6	(	(	PUNCT
iajs-2800	141	7	θ	θ	PROPN
iajs-2800	141	8	)	)	PUNCT
iajs-2800	141	9	5.0	5.0	NUM
iajs-2800	142	1	i	i	PRON
iajs-2800	142	2	tγ	tγ	VERB
iajs-2800	142	3	(	(	PUNCT
iajs-2800	142	4	i	i	NOUN
iajs-2800	142	5	t	t	PROPN
iajs-2800	142	6	)	)	PUNCT
iajs-2800	142	7	n	n	CCONJ
iajs-2800	142	8	(	(	PUNCT
iajs-2800	142	9	0.5v	0.5v	NUM
iajs-2800	142	10	0	0	NUM
iajs-2800	142	11	θ)a1(t	θ)a1(t	ADJ
iajs-2800	142	12	,	,	PUNCT
iajs-2800	142	13	1)5.0	1)5.0	PROPN
iajs-2800	142	14	(	(	PUNCT
iajs-2800	142	15	n	n	CCONJ
iajs-2800	142	16	)	)	PUNCT
iajs-2800	142	17	5.0n	5.0n	NUM
iajs-2800	142	18	(	(	PUNCT
iajs-2800	142	19	i	i	NOUN
iajs-2800	142	20	n	n	VERB
iajs-2800	142	21	1i	1i	NOUN
iajs-2800	142	22	t	t	NOUN
iajs-2800	143	1	1i	1i	NOUN
iajs-2800	143	2	1i	1i	NOUN
iajs-2800	143	3			VERB
iajs-2800	143	4			PROPN
iajs-2800	143	5			X
iajs-2800	143	6			X
iajs-2800	143	7			PUNCT
iajs-2800	143	8			VERB
iajs-2800	143	9			PRON
iajs-2800	143	10			PROPN
iajs-2800	143	11			X
iajs-2800	143	12			X
iajs-2800	144	1			NOUN
iajs-2800	145	1			ADJ
iajs-2800	145	2			ADJ
iajs-2800	145	3	.	.	PUNCT
iajs-2800	146	1	be	be	AUX
iajs-2800	146	2	the	the	DET
iajs-2800	146	3	integral	integral	ADJ
iajs-2800	146	4	of	of	ADP
iajs-2800	146	5	the	the	DET
iajs-2800	146	6	pdf	pdf	NOUN
iajs-2800	146	7	of	of	ADP
iajs-2800	146	8	gamma	gamma	NOUN
iajs-2800	146	9	distribution	distribution	NOUN
iajs-2800	146	10	[	[	X
iajs-2800	146	11	11	11	NUM
iajs-2800	146	12	]	]	PUNCT
iajs-2800	146	13	.	.	PUNCT
iajs-2800	147	1	then	then	ADV
iajs-2800	147	2	the	the	DET
iajs-2800	147	3	posterior	posterior	ADJ
iajs-2800	147	4	distribution	distribution	NOUN
iajs-2800	147	5	of	of	ADP
iajs-2800	147	6	θ	θ	PROPN
iajs-2800	147	7	is	be	AUX
iajs-2800	147	8	gamma	gamma	NOUN
iajs-2800	147	9	distribution	distribution	NOUN
iajs-2800	147	10	as	as	ADP
iajs-2800	147	11	(	(	PUNCT
iajs-2800	147	12	12	12	NUM
iajs-2800	147	13	)	)	PUNCT
iajs-2800	147	14	0n	0n	NOUN
iajs-2800	147	15	,	,	PUNCT
iajs-2800	147	16	v	v	NOUN
iajs-2800	147	17	,	,	PUNCT
iajs-2800	147	18	0θ	0θ	NOUN
iajs-2800	147	19	,	,	PUNCT
iajs-2800	147	20	)	)	PUNCT
iajs-2800	147	21	)	)	PUNCT
iajs-2800	148	1	n	n	CCONJ
iajs-2800	148	2	(	(	PUNCT
iajs-2800	148	3	0.5v	0.5v	NUM
iajs-2800	148	4	θ	θ	PROPN
iajs-2800	148	5	exp	exp	NOUN
iajs-2800	148	6	(	(	PUNCT
iajs-2800	148	7	θ	θ	PROPN
iajs-2800	148	8	)	)	PUNCT
iajs-2800	148	9	5.0	5.0	NUM
iajs-2800	148	10	i	i	PRON
iajs-2800	148	11	tγ	tγ	VERB
iajs-2800	148	12	(	(	PUNCT
iajs-2800	148	13	i	i	NOUN
iajs-2800	148	14	t	t	PROPN
iajs-2800	148	15	)	)	PUNCT
iajs-2800	148	16	n	n	CCONJ
iajs-2800	148	17	(	(	PUNCT
iajs-2800	148	18	0.5v	0.5v	NUM
iajs-2800	148	19	t	t	PROPN
iajs-2800	148	20	)	)	PUNCT
iajs-2800	148	21	\θ	\θ	NOUN
iajs-2800	148	22	(	(	PUNCT
iajs-2800	148	23	h	h	NOUN
iajs-2800	148	24	1)5.0	1)5.0	PROPN
iajs-2800	148	25	(	(	PUNCT
iajs-2800	148	26	n	n	NOUN
iajs-2800	148	27	)	)	PUNCT
iajs-2800	149	1	5.0n	5.0n	NUM
iajs-2800	149	2	(	(	PUNCT
iajs-2800	149	3	i	i	NOUN
iajs-2800	149	4	n	n	VERB
iajs-2800	149	5	1i	1i	NOUN
iajs-2800	149	6	t	t	NOUN
iajs-2800	149	7	1i	1i	NOUN
iajs-2800	149	8	1i	1i	NOUN
iajs-2800	149	9	2	2	NUM
iajs-2800	149	10			NOUN
iajs-2800	149	11			PROPN
iajs-2800	149	12			PROPN
iajs-2800	149	13			X
iajs-2800	149	14			VERB
iajs-2800	149	15			PROPN
iajs-2800	149	16			PROPN
iajs-2800	149	17			X
iajs-2800	149	18			X
iajs-2800	150	1			NUM
iajs-2800	151	1			NUM
iajs-2800	151	2			NOUN
iajs-2800	151	3	i.e.	i.e.	X
iajs-2800	151	4	)	)	PUNCT
iajs-2800	151	5	)	)	PUNCT
iajs-2800	152	1	n	n	CCONJ
iajs-2800	152	2	(	(	PUNCT
iajs-2800	152	3	0.5v),5.0tgamma	0.5v),5.0tgamma	PROPN
iajs-2800	152	4	(	(	PUNCT
iajs-2800	152	5	(	(	PUNCT
iajs-2800	152	6	)	)	PUNCT
iajs-2800	152	7	t	t	PROPN
iajs-2800	152	8	\θ	\θ	NOUN
iajs-2800	152	9	(	(	PUNCT
iajs-2800	152	10	i	i	NOUN
iajs-2800	152	11	n	n	VERB
iajs-2800	152	12	1i	1i	NUM
iajs-2800	152	13			ADP
iajs-2800	152	14			NOUN
iajs-2800	152	15	with	with	ADP
iajs-2800	152	16	posterior	posterior	ADJ
iajs-2800	152	17	mean	mean	NOUN
iajs-2800	152	18	is	be	AUX
iajs-2800	152	19	)	)	PUNCT
iajs-2800	152	20	n	n	CCONJ
iajs-2800	152	21	(	(	PUNCT
iajs-2800	152	22	0.5v	0.5v	NUM
iajs-2800	152	23	)	)	PUNCT
iajs-2800	152	24	5.0	5.0	NUM
iajs-2800	152	25	i	i	NOUN
iajs-2800	152	26	t	t	PROPN
iajs-2800	152	27	(	(	PUNCT
iajs-2800	152	28	)	)	PUNCT
iajs-2800	152	29	t	t	PROPN
iajs-2800	152	30	\θ	\θ	NOUN
iajs-2800	152	31	e	e	NOUN
iajs-2800	152	32	(	(	PUNCT
iajs-2800	152	33	n	n	PROPN
iajs-2800	152	34	1i	1i	NUM
iajs-2800	152	35			PUNCT
iajs-2800	152	36			VERB
iajs-2800	152	37			PROPN
iajs-2800	152	38			ADJ
iajs-2800	152	39	and	and	CCONJ
iajs-2800	152	40	posterior	posterior	ADJ
iajs-2800	152	41	variance	variance	NOUN
iajs-2800	152	42	is	be	AUX
iajs-2800	152	43	)	)	PUNCT
iajs-2800	152	44	n	n	CCONJ
iajs-2800	152	45	(	(	PUNCT
iajs-2800	152	46	0.5v	0.5v	NUM
iajs-2800	152	47	)	)	PUNCT
iajs-2800	152	48	5.0	5.0	NUM
iajs-2800	152	49	i	i	NOUN
iajs-2800	152	50	t	t	PROPN
iajs-2800	152	51	(	(	PUNCT
iajs-2800	152	52	)	)	PUNCT
iajs-2800	152	53	t	t	PROPN
iajs-2800	152	54	\θ	\θ	NOUN
iajs-2800	152	55	var	var	NOUN
iajs-2800	152	56	(	(	PUNCT
iajs-2800	152	57	2	2	NUM
iajs-2800	152	58	n	n	NUM
iajs-2800	152	59	1i	1i	NOUN
iajs-2800	152	60			PUNCT
iajs-2800	152	61			VERB
iajs-2800	152	62			PROPN
iajs-2800	152	63			NOUN
iajs-2800	152	64	.	.	PUNCT
iajs-2800	153	1	(	(	PUNCT
iajs-2800	153	2	c	c	NOUN
iajs-2800	153	3	)	)	PUNCT
iajs-2800	153	4	.	.	PUNCT
iajs-2800	154	1	posterior	posterior	ADJ
iajs-2800	154	2	distribution	distribution	NOUN
iajs-2800	154	3	under	under	ADP
iajs-2800	154	4	non	non	ADJ
iajs-2800	154	5	-	-	ADJ
iajs-2800	154	6	informative	informative	ADJ
iajs-2800	154	7	's	's	PART
iajs-2800	154	8	prior	prior	ADJ
iajs-2800	154	9	information	information	NOUN
iajs-2800	154	10	it	it	PRON
iajs-2800	154	11	is	be	AUX
iajs-2800	154	12	assumed	assume	VERB
iajs-2800	154	13	that	that	SCONJ
iajs-2800	154	14	the	the	DET
iajs-2800	154	15	prior	prior	NOUN
iajs-2800	154	16	for	for	ADP
iajs-2800	154	17	an	an	DET
iajs-2800	154	18	unknown	unknown	ADJ
iajs-2800	154	19	parameter	parameter	NOUN
iajs-2800	154	20	θ	θ	PROPN
iajs-2800	154	21	is	be	AUX
iajs-2800	154	22	non	non	ADJ
iajs-2800	154	23	-	-	ADJ
iajs-2800	154	24	informative	informative	ADJ
iajs-2800	154	25	with	with	ADP
iajs-2800	154	26	hyper	hyper	ADJ
iajs-2800	154	27	parameter	parameter	NOUN
iajs-2800	154	28	)	)	PUNCT
iajs-2800	155	1	c	c	NOUN
iajs-2800	155	2	(	(	PUNCT
iajs-2800	155	3	as	as	SCONJ
iajs-2800	155	4	given	give	VERB
iajs-2800	155	5	below[9	below[9	NOUN
iajs-2800	155	6	]	]	NOUN
iajs-2800	155	7	:	:	PUNCT
iajs-2800	155	8	(	(	PUNCT
iajs-2800	155	9	13	13	NUM
iajs-2800	155	10	)	)	PUNCT
iajs-2800	155	11	0	0	NUM
iajs-2800	155	12	c	c	NOUN
iajs-2800	155	13	θ	θ	PROPN
iajs-2800	155	14	,	,	PUNCT
iajs-2800	155	15	with	with	ADP
iajs-2800	155	16	cθ	cθ	ADP
iajs-2800	155	17	1	1	NUM
iajs-2800	155	18	)	)	PUNCT
iajs-2800	155	19	θ	θ	NOUN
iajs-2800	155	20	(	(	PUNCT
iajs-2800	155	21	k	k	PROPN
iajs-2800	155	22	α3	α3	PROPN
iajs-2800	155	23			ADJ
iajs-2800	155	24	substituting	substitute	VERB
iajs-2800	155	25	equation	equation	NOUN
iajs-2800	155	26	(	(	PUNCT
iajs-2800	155	27	2	2	NUM
iajs-2800	155	28	)	)	PUNCT
iajs-2800	155	29	and	and	CCONJ
iajs-2800	155	30	equation	equation	NOUN
iajs-2800	155	31	(	(	PUNCT
iajs-2800	155	32	13	13	NUM
iajs-2800	155	33	)	)	PUNCT
iajs-2800	155	34	in	in	ADP
iajs-2800	155	35	equation	equation	NOUN
iajs-2800	155	36	(	(	PUNCT
iajs-2800	155	37	5	5	X
iajs-2800	155	38	)	)	PUNCT
iajs-2800	155	39	yields	yield	VERB
iajs-2800	155	40	the	the	DET
iajs-2800	155	41	posterior	posterior	ADJ
iajs-2800	155	42	probability	probability	NOUN
iajs-2800	155	43	density	density	NOUN
iajs-2800	155	44	function	function	NOUN
iajs-2800	155	45	of	of	ADP
iajs-2800	155	46	the	the	DET
iajs-2800	155	47	shape	shape	NOUN
iajs-2800	155	48	parameter	parameter	NOUN
iajs-2800	155	49	θ	θ	PROPN
iajs-2800	155	50	like	like	ADP
iajs-2800	155	51	the	the	DET
iajs-2800	155	52	following	follow	VERB
iajs-2800	155	53	:	:	PUNCT
iajs-2800	155	54	ibn	ibn	PROPN
iajs-2800	155	55	al	al	PROPN
iajs-2800	155	56	-	-	PUNCT
iajs-2800	155	57	haitham	haitham	PROPN
iajs-2800	155	58	jour	jour	X
iajs-2800	155	59	.	.	PROPN
iajs-2800	156	1	for	for	ADP
iajs-2800	156	2	pure	pure	ADJ
iajs-2800	156	3	&	&	CCONJ
iajs-2800	156	4	appl	appl	PROPN
iajs-2800	156	5	.	.	PUNCT
iajs-2800	157	1	sci	sci	PROPN
iajs-2800	157	2	.	.	PROPN
iajs-2800	158	1	53	53	NUM
iajs-2800	158	2	(	(	PUNCT
iajs-2800	158	3	1)2022	1)2022	PROPN
iajs-2800	158	4	65	65	NUM
iajs-2800	158	5	)	)	PUNCT
iajs-2800	158	6	14	14	NUM
iajs-2800	158	7	(	(	PUNCT
iajs-2800	158	8	θ	θ	NOUN
iajs-2800	158	9	0	0	NUM
iajs-2800	158	10	)	)	PUNCT
iajs-2800	158	11	dn	dn	NOUN
iajs-2800	158	12	θ	θ	PROPN
iajs-2800	158	13	exp	exp	NOUN
iajs-2800	158	14	(	(	PUNCT
iajs-2800	158	15	c	c	NOUN
iajs-2800	158	16	i	i	PRON
iajs-2800	158	17	t	t	NOUN
iajs-2800	158	18	θ	θ	PROPN
iajs-2800	158	19	)	)	PUNCT
iajs-2800	158	20	n	n	CCONJ
iajs-2800	158	21	θ	θ	PROPN
iajs-2800	158	22	exp	exp	NOUN
iajs-2800	158	23	(	(	PUNCT
iajs-2800	158	24	c	c	NOUN
iajs-2800	159	1	i	i	PRON
iajs-2800	159	2	t	t	NOUN
iajs-2800	159	3	θ	θ	X
iajs-2800	159	4	]	]	X
iajs-2800	159	5	dθ	dθ	PROPN
iajs-2800	159	6	cθ	cθ	ADP
iajs-2800	159	7	1	1	NUM
iajs-2800	159	8	[	[	PUNCT
iajs-2800	159	9	t!n	t!n	NOUN
iajs-2800	159	10	1i	1i	NOUN
iajs-2800	160	1	π	π	NOUN
iajs-2800	160	2	i	i	PRON
iajs-2800	160	3	t	t	VERB
iajs-2800	160	4	θ	θ	PROPN
iajs-2800	160	5	θ)exp(-n	θ)exp(-n	NOUN
iajs-2800	160	6	0	0	NUM
iajs-2800	160	7	]	]	PUNCT
iajs-2800	160	8	cθ	cθ	ADP
iajs-2800	160	9	1	1	NUM
iajs-2800	160	10	[	[	PUNCT
iajs-2800	160	11	t!n	t!n	NOUN
iajs-2800	160	12	1i	1i	NOUN
iajs-2800	160	13	π	π	NOUN
iajs-2800	161	1	i	i	PRON
iajs-2800	161	2	t	t	NOUN
iajs-2800	161	3	θ	θ	PROPN
iajs-2800	161	4	θ)exp(-n	θ)exp(-n	PROPN
iajs-2800	161	5	t	t	PROPN
iajs-2800	161	6	)	)	PUNCT
iajs-2800	161	7	\θ	\θ	NOUN
iajs-2800	161	8	(	(	PUNCT
iajs-2800	161	9	h	h	NOUN
iajs-2800	161	10	n	n	CCONJ
iajs-2800	161	11	n	n	CCONJ
iajs-2800	161	12	n	n	PROPN
iajs-2800	161	13	1i	1i	NUM
iajs-2800	161	14	n	n	NUM
iajs-2800	161	15	1i	1i	NOUN
iajs-2800	161	16	1i	1i	NOUN
iajs-2800	161	17	1i	1i	NOUN
iajs-2800	161	18	3	3	NUM
iajs-2800	161	19			NOUN
iajs-2800	161	20			VERB
iajs-2800	161	21			PROPN
iajs-2800	161	22			PRON
iajs-2800	161	23			PROPN
iajs-2800	161	24			PRON
iajs-2800	161	25			PROPN
iajs-2800	161	26			ADJ
iajs-2800	161	27			X
iajs-2800	161	28			PUNCT
iajs-2800	161	29			VERB
iajs-2800	161	30			PRON
iajs-2800	161	31			X
iajs-2800	162	1			NUM
iajs-2800	163	1			NUM
iajs-2800	163	2			PRON
iajs-2800	164	1			NUM
iajs-2800	164	2			PROPN
iajs-2800	164	3	rewrite	rewrite	PROPN
iajs-2800	164	4	11)ct(ct	11)ct(ct	NUM
iajs-2800	165	1	i	i	NOUN
iajs-2800	165	2	n	n	CCONJ
iajs-2800	165	3	1ii	1ii	ADJ
iajs-2800	165	4	n	n	CCONJ
iajs-2800	165	5	1i	1i	NUM
iajs-2800	165	6			PROPN
iajs-2800	165	7			NUM
iajs-2800	165	8	and	and	CCONJ
iajs-2800	165	9	by	by	ADP
iajs-2800	165	10	multiplying	multiply	VERB
iajs-2800	165	11	the	the	DET
iajs-2800	165	12	integral	integral	ADJ
iajs-2800	165	13	in	in	ADP
iajs-2800	165	14	equation	equation	NOUN
iajs-2800	165	15	(	(	PUNCT
iajs-2800	165	16	14	14	NUM
iajs-2800	165	17	)	)	PUNCT
iajs-2800	165	18	by	by	ADP
iajs-2800	165	19	the	the	DET
iajs-2800	165	20	quantity	quantity	NOUN
iajs-2800	165	21	which	which	PRON
iajs-2800	165	22	equals	equal	VERB
iajs-2800	165	23	to	to	PART
iajs-2800	165	24	)	)	PUNCT
iajs-2800	166	1	i	i	PRON
iajs-2800	166	2	t	t	PROPN
iajs-2800	166	3	)	)	PUNCT
iajs-2800	167	1	n	n	CCONJ
iajs-2800	167	2	(	(	PUNCT
iajs-2800	167	3	1)c	1)c	NUM
iajs-2800	167	4	i	i	PRON
iajs-2800	167	5	tγ	tγ	VERB
iajs-2800	167	6	(	(	PUNCT
iajs-2800	167	7	(	(	PUNCT
iajs-2800	167	8	)	)	PUNCT
iajs-2800	167	9	1)c	1)c	NOUN
iajs-2800	168	1	i	i	PRON
iajs-2800	168	2	tγ	tγ	VERB
iajs-2800	168	3	(	(	PUNCT
iajs-2800	169	1	i	i	NOUN
iajs-2800	169	2	t	t	PROPN
iajs-2800	169	3	)	)	PUNCT
iajs-2800	169	4	n	n	CCONJ
iajs-2800	169	5	(	(	PUNCT
iajs-2800	169	6	(	(	PUNCT
iajs-2800	169	7	1)cn	1)cn	NUM
iajs-2800	169	8	(	(	PUNCT
iajs-2800	169	9	n	n	NOUN
iajs-2800	169	10	n	n	PRON
iajs-2800	169	11	1)cn	1)cn	NUM
iajs-2800	169	12	(	(	PUNCT
iajs-2800	169	13	1i	1i	NOUN
iajs-2800	169	14	1i	1i	NOUN
iajs-2800	169	15	1i	1i	NOUN
iajs-2800	169	16	1i	1i	NOUN
iajs-2800	169	17			PROPN
iajs-2800	169	18			PROPN
iajs-2800	169	19			X
iajs-2800	169	20			PROPN
iajs-2800	169	21			PROPN
iajs-2800	169	22			X
iajs-2800	170	1			NUM
iajs-2800	171	1			NUM
iajs-2800	172	1			ADJ
iajs-2800	173	1			INTJ
iajs-2800	173	2	,	,	PUNCT
iajs-2800	173	3	where	where	SCONJ
iajs-2800	173	4	)	)	PUNCT
iajs-2800	173	5	γ	γ	X
iajs-2800	173	6	(	(	PUNCT
iajs-2800	173	7	.	.	PUNCT
iajs-2800	173	8	is	be	AUX
iajs-2800	173	9	a	a	DET
iajs-2800	173	10	gamma	gamma	NOUN
iajs-2800	173	11	function	function	NOUN
iajs-2800	173	12	.after	.after	PUNCT
iajs-2800	174	1	some	some	DET
iajs-2800	174	2	simplification	simplification	NOUN
iajs-2800	174	3	,	,	PUNCT
iajs-2800	174	4	it	it	PRON
iajs-2800	174	5	yields	yield	VERB
iajs-2800	174	6	(	(	PUNCT
iajs-2800	174	7	15	15	NUM
iajs-2800	174	8	)	)	PUNCT
iajs-2800	174	9	)	)	PUNCT
iajs-2800	175	1	n	n	CCONJ
iajs-2800	175	2	θ	θ	PROPN
iajs-2800	175	3	exp	exp	NOUN
iajs-2800	175	4	(	(	PUNCT
iajs-2800	175	5	θ	θ	NOUN
iajs-2800	175	6	θ),1)a2(t	θ),1)a2(t	NOUN
iajs-2800	175	7	c	c	NOUN
iajs-2800	176	1	i	i	PRON
iajs-2800	176	2	tγ	tγ	VERB
iajs-2800	176	3	(	(	PUNCT
iajs-2800	177	1	i	i	NOUN
iajs-2800	177	2	t	t	PROPN
iajs-2800	177	3	)	)	PUNCT
iajs-2800	177	4	(	(	PUNCT
iajs-2800	177	5	n	n	PROPN
iajs-2800	177	6	t	t	PROPN
iajs-2800	177	7	)	)	PUNCT
iajs-2800	177	8	\θ	\θ	NOUN
iajs-2800	177	9	(	(	PUNCT
iajs-2800	177	10	h	h	NOUN
iajs-2800	177	11	11)c	11)c	NUM
iajs-2800	177	12	(	(	PUNCT
iajs-2800	177	13	n	n	PROPN
iajs-2800	177	14	1)cn	1)cn	NUM
iajs-2800	178	1	(	(	PUNCT
iajs-2800	178	2	i	i	NOUN
iajs-2800	178	3	n	n	VERB
iajs-2800	178	4	1i	1i	NUM
iajs-2800	178	5	t	t	NOUN
iajs-2800	178	6	1i	1i	NOUN
iajs-2800	178	7	1i	1i	NOUN
iajs-2800	178	8	3	3	NUM
iajs-2800	178	9			PROPN
iajs-2800	178	10			PROPN
iajs-2800	178	11			X
iajs-2800	178	12			PROPN
iajs-2800	178	13			NOUN
iajs-2800	178	14			PROPN
iajs-2800	178	15			X
iajs-2800	179	1			NUM
iajs-2800	180	1			NUM
iajs-2800	180	2			INTJ
iajs-2800	180	3	where	where	SCONJ
iajs-2800	180	4	1dθ	1dθ	ADJ
iajs-2800	180	5	)	)	PUNCT
iajs-2800	180	6	n	n	CCONJ
iajs-2800	180	7	θ	θ	PROPN
iajs-2800	180	8	exp	exp	NOUN
iajs-2800	180	9	(	(	PUNCT
iajs-2800	180	10	θ	θ	PROPN
iajs-2800	180	11	1))c	1))c	NUM
iajs-2800	181	1	i	i	PRON
iajs-2800	181	2	tγ	tγ	VERB
iajs-2800	181	3	(	(	PUNCT
iajs-2800	181	4	i	i	NOUN
iajs-2800	181	5	t	t	PROPN
iajs-2800	181	6	)	)	PUNCT
iajs-2800	181	7	(	(	PUNCT
iajs-2800	181	8	n	n	NOUN
iajs-2800	181	9	0	0	NUM
iajs-2800	181	10	θ)a2(t	θ)a2(t	PROPN
iajs-2800	181	11	,	,	PUNCT
iajs-2800	181	12	11)c	11)c	NUM
iajs-2800	181	13	(	(	PUNCT
iajs-2800	181	14	n	n	PROPN
iajs-2800	181	15	1)cn	1)cn	NUM
iajs-2800	181	16	(	(	PUNCT
iajs-2800	181	17	i	i	NOUN
iajs-2800	181	18	n	n	VERB
iajs-2800	181	19	1i	1i	NUM
iajs-2800	181	20	t	t	NOUN
iajs-2800	181	21	1i	1i	NUM
iajs-2800	181	22	1i	1i	NOUN
iajs-2800	181	23			PROPN
iajs-2800	181	24			PROPN
iajs-2800	181	25			X
iajs-2800	181	26			PUNCT
iajs-2800	181	27			VERB
iajs-2800	181	28			NUM
iajs-2800	181	29			NOUN
iajs-2800	181	30			PROPN
iajs-2800	181	31			X
iajs-2800	182	1			NUM
iajs-2800	183	1			ADJ
iajs-2800	183	2			ADJ
iajs-2800	183	3	.	.	PUNCT
iajs-2800	184	1	be	be	AUX
iajs-2800	184	2	the	the	DET
iajs-2800	184	3	integral	integral	ADJ
iajs-2800	184	4	of	of	ADP
iajs-2800	184	5	the	the	DET
iajs-2800	184	6	pdf	pdf	NOUN
iajs-2800	184	7	of	of	ADP
iajs-2800	184	8	gamma	gamma	NOUN
iajs-2800	184	9	distribution	distribution	NOUN
iajs-2800	184	10	[	[	X
iajs-2800	184	11	11	11	NUM
iajs-2800	184	12	]	]	PUNCT
iajs-2800	184	13	.	.	PUNCT
iajs-2800	185	1	then	then	ADV
iajs-2800	185	2	the	the	DET
iajs-2800	185	3	posterior	posterior	ADJ
iajs-2800	185	4	distribution	distribution	NOUN
iajs-2800	185	5	of	of	ADP
iajs-2800	185	6	θ	θ	PROPN
iajs-2800	185	7	is	be	AUX
iajs-2800	185	8	gamma	gamma	NOUN
iajs-2800	185	9	distribution	distribution	NOUN
iajs-2800	185	10	as	as	ADP
iajs-2800	185	11	(	(	PUNCT
iajs-2800	185	12	16	16	NUM
iajs-2800	185	13	)	)	PUNCT
iajs-2800	185	14	0n	0n	NOUN
iajs-2800	185	15	,	,	PUNCT
iajs-2800	185	16	1c	1c	NUM
iajs-2800	185	17	,	,	PUNCT
iajs-2800	185	18	0θ	0θ	NOUN
iajs-2800	185	19	,	,	PUNCT
iajs-2800	185	20	)	)	PUNCT
iajs-2800	185	21	n	n	CCONJ
iajs-2800	185	22	θ	θ	PROPN
iajs-2800	185	23	exp	exp	NOUN
iajs-2800	185	24	(	(	PUNCT
iajs-2800	185	25	θ	θ	PROPN
iajs-2800	185	26	1)c	1)c	NUM
iajs-2800	186	1	i	i	PRON
iajs-2800	186	2	tγ	tγ	VERB
iajs-2800	186	3	(	(	PUNCT
iajs-2800	186	4	t	t	NOUN
iajs-2800	186	5	)	)	PUNCT
iajs-2800	186	6	(	(	PUNCT
iajs-2800	186	7	n	n	PROPN
iajs-2800	186	8	t	t	PROPN
iajs-2800	186	9	)	)	PUNCT
iajs-2800	186	10	\θ	\θ	NOUN
iajs-2800	186	11	(	(	PUNCT
iajs-2800	186	12	h	h	NOUN
iajs-2800	186	13	11)c	11)c	NUM
iajs-2800	186	14	(	(	PUNCT
iajs-2800	186	15	n	n	PROPN
iajs-2800	186	16	1)cn	1)cn	NUM
iajs-2800	186	17	(	(	PUNCT
iajs-2800	186	18	i	i	NOUN
iajs-2800	186	19	n	n	VERB
iajs-2800	186	20	1i	1i	NOUN
iajs-2800	186	21	t	t	NOUN
iajs-2800	186	22	1i	1i	NOUN
iajs-2800	186	23	i1i	i1i	ADP
iajs-2800	186	24	3	3	NUM
iajs-2800	186	25			NOUN
iajs-2800	186	26			PROPN
iajs-2800	186	27			X
iajs-2800	186	28			PROPN
iajs-2800	186	29			NOUN
iajs-2800	187	1			PROPN
iajs-2800	187	2			X
iajs-2800	188	1			NUM
iajs-2800	189	1			NUM
iajs-2800	189	2			NOUN
iajs-2800	189	3	i.e.	i.e.	X
iajs-2800	189	4	)	)	PUNCT
iajs-2800	189	5	)	)	PUNCT
iajs-2800	190	1	(	(	PUNCT
iajs-2800	190	2	n	n	PROPN
iajs-2800	190	3	1),ctgamma	1),ctgamma	NUM
iajs-2800	190	4	(	(	PUNCT
iajs-2800	190	5	(	(	PUNCT
iajs-2800	190	6	)	)	PUNCT
iajs-2800	190	7	t	t	PROPN
iajs-2800	190	8	\θ	\θ	NOUN
iajs-2800	190	9	(	(	PUNCT
iajs-2800	190	10	i	i	NOUN
iajs-2800	190	11	n	n	NOUN
iajs-2800	190	12	1i	1i	NOUN
iajs-2800	190	13			PROPN
iajs-2800	190	14			NUM
iajs-2800	190	15	with	with	ADP
iajs-2800	190	16	posterior	posterior	ADJ
iajs-2800	190	17	mean	mean	NOUN
iajs-2800	190	18	is	be	AUX
iajs-2800	190	19	1cfor	1cfor	NUM
iajs-2800	190	20	n	n	NUM
iajs-2800	190	21	1)c	1)c	NUM
iajs-2800	191	1	i	i	PRON
iajs-2800	191	2	t	t	PROPN
iajs-2800	191	3	(	(	PUNCT
iajs-2800	191	4	)	)	PUNCT
iajs-2800	191	5	t	t	PROPN
iajs-2800	191	6	\θ	\θ	NOUN
iajs-2800	191	7	e	e	NOUN
iajs-2800	191	8	(	(	PUNCT
iajs-2800	191	9	n	n	CCONJ
iajs-2800	191	10	1i	1i	NOUN
iajs-2800	191	11			VERB
iajs-2800	191	12			ADV
iajs-2800	191	13			PROPN
iajs-2800	191	14			NUM
iajs-2800	191	15	and	and	CCONJ
iajs-2800	191	16	posterior	posterior	ADJ
iajs-2800	191	17	variance	variance	NOUN
iajs-2800	191	18	is	be	AUX
iajs-2800	191	19	1cfor	1cfor	NUM
iajs-2800	191	20	n	n	NUM
iajs-2800	191	21	1)c	1)c	NUM
iajs-2800	192	1	i	i	PRON
iajs-2800	192	2	t	t	PROPN
iajs-2800	192	3	(	(	PUNCT
iajs-2800	192	4	)	)	PUNCT
iajs-2800	192	5	t	t	PROPN
iajs-2800	192	6	\θ	\θ	NOUN
iajs-2800	192	7	var	var	NOUN
iajs-2800	192	8	(	(	PUNCT
iajs-2800	192	9	2	2	NUM
iajs-2800	192	10	n	n	NOUN
iajs-2800	192	11	1i	1i	NOUN
iajs-2800	192	12			VERB
iajs-2800	192	13			ADP
iajs-2800	192	14			PROPN
iajs-2800	192	15			NOUN
iajs-2800	192	16	.	.	PUNCT
iajs-2800	193	1	2.2.2	2.2.2	NUM
iajs-2800	193	2	bayes	bayes	PROPN
iajs-2800	193	3	estimation	estimation	NOUN
iajs-2800	193	4	under	under	ADP
iajs-2800	193	5	squared	square	VERB
iajs-2800	193	6	error	error	NOUN
iajs-2800	193	7	loss	loss	NOUN
iajs-2800	193	8	function	function	NOUN
iajs-2800	193	9	we	we	PRON
iajs-2800	193	10	derive	derive	VERB
iajs-2800	193	11	bayes	bayes	PROPN
iajs-2800	193	12	estimation	estimation	NOUN
iajs-2800	193	13	under	under	ADP
iajs-2800	193	14	the	the	DET
iajs-2800	193	15	squared	square	VERB
iajs-2800	193	16	error	error	NOUN
iajs-2800	193	17	loss	loss	NOUN
iajs-2800	193	18	function	function	NOUN
iajs-2800	193	19	assuming	assume	VERB
iajs-2800	193	20	different	different	ADJ
iajs-2800	193	21	priors	prior	NOUN
iajs-2800	193	22	'	'	PART
iajs-2800	193	23	informative	informative	ADJ
iajs-2800	193	24	priors	prior	NOUN
iajs-2800	193	25	such	such	ADJ
iajs-2800	193	26	as	as	ADP
iajs-2800	193	27	erlang	erlang	NOUN
iajs-2800	193	28	and	and	CCONJ
iajs-2800	193	29	levy	levy	NOUN
iajs-2800	193	30	and	and	CCONJ
iajs-2800	193	31	non	non	ADJ
iajs-2800	193	32	-	-	ADJ
iajs-2800	193	33	informative	informative	ADJ
iajs-2800	193	34	prior	prior	ADV
iajs-2800	193	35	.	.	PUNCT
iajs-2800	194	1	then	then	ADV
iajs-2800	194	2	,	,	PUNCT
iajs-2800	194	3	the	the	DET
iajs-2800	194	4	risk	risk	NOUN
iajs-2800	194	5	function	function	NOUN
iajs-2800	194	6	is	be	AUX
iajs-2800	194	7	denoted	denote	VERB
iajs-2800	194	8	by	by	ADP
iajs-2800	194	9	]	]	SYM
iajs-2800	194	10	θ	θ	NOUN
iajs-2800	194	11	)	)	PUNCT
iajs-2800	194	12	θ	θ	NOUN
iajs-2800	194	13	(	(	PUNCT
iajs-2800	194	14	l	l	NOUN
iajs-2800	194	15	e[θ	e[θ	NOUN
iajs-2800	194	16	)	)	PUNCT
iajs-2800	194	17	,	,	PUNCT
iajs-2800	194	18	θ	θ	PROPN
iajs-2800	194	19	(	(	PUNCT
iajs-2800	194	20	r	r	NOUN
iajs-2800	194	21	2	2	NUM
iajs-2800	194	22	11	11	NUM
iajs-2800	194	23	^^	^^	SYM
iajs-2800	194	24			NUM
iajs-2800	194	25	,	,	PUNCT
iajs-2800	194	26	t	t	PROPN
iajs-2800	194	27	)	)	PUNCT
iajs-2800	194	28	\θ	\θ	NOUN
iajs-2800	194	29	e(t	e(t	NOUN
iajs-2800	194	30	)	)	PUNCT
iajs-2800	194	31	\θ	\θ	NOUN
iajs-2800	194	32	e(θ2	e(θ2	NOUN
iajs-2800	194	33	θ	θ	NOUN
iajs-2800	194	34	θ)θ	θ)θ	PUNCT
iajs-2800	194	35	(	(	PUNCT
iajs-2800	194	36	r	r	NOUN
iajs-2800	194	37	2	2	NUM
iajs-2800	194	38	^	^	SYM
iajs-2800	194	39	2	2	NUM
iajs-2800	194	40	^	^	SYM
iajs-2800	194	41	1	1	NUM
iajs-2800	194	42	^	^	SYM
iajs-2800	194	43			NUM
iajs-2800	194	44	.the	.the	PRON
iajs-2800	194	45	value	value	NOUN
iajs-2800	194	46	of	of	ADP
iajs-2800	194	47	θ	θ	PROPN
iajs-2800	194	48	minimizes	minimize	VERB
iajs-2800	194	49	the	the	DET
iajs-2800	194	50	risk	risk	NOUN
iajs-2800	194	51	function	function	NOUN
iajs-2800	194	52	under	under	ADP
iajs-2800	194	53	squared	square	VERB
iajs-2800	194	54	error	error	NOUN
iajs-2800	194	55	loss	loss	NOUN
iajs-2800	194	56	function	function	NOUN
iajs-2800	194	57	which	which	PRON
iajs-2800	194	58	satisfies	satisfy	VERB
iajs-2800	194	59	the	the	DET
iajs-2800	194	60	following	follow	VERB
iajs-2800	194	61	ibn	ibn	PROPN
iajs-2800	194	62	al	al	PROPN
iajs-2800	194	63	-	-	PUNCT
iajs-2800	194	64	haitham	haitham	PROPN
iajs-2800	194	65	jour	jour	X
iajs-2800	194	66	.	.	PROPN
iajs-2800	195	1	for	for	ADP
iajs-2800	195	2	pure	pure	ADJ
iajs-2800	195	3	&	&	CCONJ
iajs-2800	195	4	appl	appl	PROPN
iajs-2800	195	5	.	.	PUNCT
iajs-2800	196	1	sci	sci	PROPN
iajs-2800	196	2	.	.	PROPN
iajs-2800	197	1	53	53	NUM
iajs-2800	197	2	(	(	PUNCT
iajs-2800	197	3	1)2022	1)2022	NOUN
iajs-2800	197	4	66	66	NUM
iajs-2800	197	5	condition	condition	NOUN
iajs-2800	197	6	0	0	NUM
iajs-2800	197	7	θ)θ	θ)θ	NOUN
iajs-2800	197	8	r	r	X
iajs-2800	197	9	(	(	PUNCT
iajs-2800	197	10	^	^	PUNCT
iajs-2800	197	11	^	^	PUNCT
iajs-2800	197	12	θ	θ	PROPN
iajs-2800	197	13			NUM
iajs-2800	197	14			ADJ
iajs-2800	197	15			PROPN
iajs-2800	197	16	;	;	PUNCT
iajs-2800	197	17	we	we	PRON
iajs-2800	197	18	get	get	VERB
iajs-2800	197	19	bayes	bayes	PROPN
iajs-2800	197	20	estimator	estimator	NOUN
iajs-2800	197	21	of	of	ADP
iajs-2800	197	22	θ	θ	PROPN
iajs-2800	197	23	denoted	denote	VERB
iajs-2800	197	24	by	by	ADP
iajs-2800	197	25	θ	θ	PROPN
iajs-2800	197	26	^	^	PUNCT
iajs-2800	197	27	for	for	SCONJ
iajs-2800	197	28	each	each	PRON
iajs-2800	197	29	of	of	ADP
iajs-2800	197	30	the	the	DET
iajs-2800	197	31	previous	previous	ADJ
iajs-2800	197	32	priors	prior	NOUN
iajs-2800	197	33	as	as	SCONJ
iajs-2800	197	34	follows	follow	VERB
iajs-2800	197	35	)	)	PUNCT
iajs-2800	197	36	(	(	PUNCT
iajs-2800	197	37	17	17	NUM
iajs-2800	197	38	dθ	dθ	PROPN
iajs-2800	197	39	t	t	PROPN
iajs-2800	197	40	)	)	PUNCT
iajs-2800	197	41	\θ	\θ	NOUN
iajs-2800	197	42	(	(	PUNCT
iajs-2800	197	43	h	h	NOUN
iajs-2800	197	44	θt	θt	NOUN
iajs-2800	197	45	)	)	PUNCT
iajs-2800	197	46	\θ	\θ	NOUN
iajs-2800	197	47	e(θ	e(θ	NOUN
iajs-2800	197	48	0	0	NUM
iajs-2800	197	49	^	^	SYM
iajs-2800	197	50			PUNCT
iajs-2800	197	51			VERB
iajs-2800	197	52			NUM
iajs-2800	197	53	i.e.	i.e.	X
iajs-2800	197	54	,	,	PUNCT
iajs-2800	197	55	t	t	NOUN
iajs-2800	197	56	)	)	PUNCT
iajs-2800	197	57	\θ	\θ	NOUN
iajs-2800	197	58	e(θ	e(θ	NOUN
iajs-2800	197	59	^	^	PUNCT
iajs-2800	197	60			PROPN
iajs-2800	197	61	is	be	AUX
iajs-2800	197	62	equal	equal	ADJ
iajs-2800	197	63	to	to	ADP
iajs-2800	197	64	the	the	DET
iajs-2800	197	65	posterior	posterior	ADJ
iajs-2800	197	66	mean	mean	NOUN
iajs-2800	197	67	for	for	ADP
iajs-2800	197	68	different	different	ADJ
iajs-2800	197	69	priors	prior	NOUN
iajs-2800	197	70	informative	informative	ADJ
iajs-2800	197	71	priors	prior	NOUN
iajs-2800	197	72	(	(	PUNCT
iajs-2800	197	73	erlang	erlang	NOUN
iajs-2800	197	74	and	and	CCONJ
iajs-2800	197	75	levy	levy	NOUN
iajs-2800	197	76	)	)	PUNCT
iajs-2800	197	77	and	and	CCONJ
iajs-2800	197	78	non	non	ADJ
iajs-2800	197	79	-	-	ADJ
iajs-2800	197	80	informative	informative	ADJ
iajs-2800	197	81	prior	prior	ADV
iajs-2800	197	82	as	as	SCONJ
iajs-2800	197	83	have	have	AUX
iajs-2800	197	84	been	be	AUX
iajs-2800	197	85	derived	derive	VERB
iajs-2800	197	86	in	in	ADP
iajs-2800	197	87	section	section	NOUN
iajs-2800	197	88	4.1	4.1	NUM
iajs-2800	197	89	.	.	PUNCT
iajs-2800	198	1	2.2.3	2.2.3	NUM
iajs-2800	198	2	bayes	bayes	NOUN
iajs-2800	198	3	estimation	estimation	NOUN
iajs-2800	198	4	under	under	ADP
iajs-2800	198	5	the	the	DET
iajs-2800	198	6	proposed	propose	VERB
iajs-2800	198	7	exponential	exponential	ADJ
iajs-2800	198	8	loss	loss	NOUN
iajs-2800	198	9	function	function	NOUN
iajs-2800	198	10	we	we	PRON
iajs-2800	198	11	derive	derive	VERB
iajs-2800	198	12	bayes	bayes	PROPN
iajs-2800	198	13	estimation	estimation	NOUN
iajs-2800	198	14	under	under	ADP
iajs-2800	198	15	the	the	DET
iajs-2800	198	16	proposed	propose	VERB
iajs-2800	198	17	exponential	exponential	ADJ
iajs-2800	198	18	loss	loss	NOUN
iajs-2800	198	19	function	function	NOUN
iajs-2800	198	20	assuming	assume	VERB
iajs-2800	198	21	different	different	ADJ
iajs-2800	198	22	priors	prior	NOUN
iajs-2800	198	23	'	'	PART
iajs-2800	198	24	informative	informative	ADJ
iajs-2800	198	25	priors	prior	NOUN
iajs-2800	198	26	such	such	ADJ
iajs-2800	198	27	as	as	ADP
iajs-2800	198	28	erlang	erlang	NOUN
iajs-2800	198	29	,	,	PUNCT
iajs-2800	198	30	levy	levy	NOUN
iajs-2800	198	31	and	and	CCONJ
iajs-2800	198	32	non	non	ADJ
iajs-2800	198	33	-	-	ADJ
iajs-2800	198	34	informative	informative	ADJ
iajs-2800	198	35	prior	prior	ADV
iajs-2800	198	36	.	.	PUNCT
iajs-2800	199	1	then	then	ADV
iajs-2800	199	2	,	,	PUNCT
iajs-2800	199	3	the	the	DET
iajs-2800	199	4	risk	risk	NOUN
iajs-2800	199	5	function	function	NOUN
iajs-2800	199	6	is	be	AUX
iajs-2800	199	7	denoted	denote	VERB
iajs-2800	199	8	by	by	ADP
iajs-2800	199	9	]	]	X
iajs-2800	199	10	θ	θ	NOUN
iajs-2800	199	11	)	)	PUNCT
iajs-2800	199	12	)	)	PUNCT
iajs-2800	199	13	(	(	PUNCT
iajs-2800	199	14	exp	exp	NOUN
iajs-2800	199	15	)	)	PUNCT
iajs-2800	199	16	θ	θ	PROPN
iajs-2800	199	17	(	(	PUNCT
iajs-2800	199	18	exp(l	exp(l	NOUN
iajs-2800	199	19	e[θ	e[θ	NOUN
iajs-2800	199	20	)	)	PUNCT
iajs-2800	199	21	,	,	PUNCT
iajs-2800	199	22	θ	θ	PROPN
iajs-2800	199	23	(	(	PUNCT
iajs-2800	199	24	r	r	NOUN
iajs-2800	199	25	2	2	NUM
iajs-2800	199	26	^	^	SYM
iajs-2800	199	27	2	2	NUM
iajs-2800	199	28	^	^	SYM
iajs-2800	199	29	2	2	NUM
iajs-2800	199	30			NOUN
iajs-2800	199	31	,	,	PUNCT
iajs-2800	199	32	t	t	NOUN
iajs-2800	199	33	)	)	PUNCT
iajs-2800	199	34	\θ	\θ	NOUN
iajs-2800	199	35	)	)	PUNCT
iajs-2800	199	36	e(exp(2	e(exp(2	ADP
iajs-2800	199	37	t	t	NOUN
iajs-2800	199	38	)	)	PUNCT
iajs-2800	199	39	\θ	\θ	NOUN
iajs-2800	199	40	)	)	PUNCT
iajs-2800	199	41	exp	exp	NOUN
iajs-2800	199	42	(	(	PUNCT
iajs-2800	199	43	)	)	PUNCT
iajs-2800	199	44	e(θ2exp()θ2exp	e(θ2exp()θ2exp	PROPN
iajs-2800	199	45	(	(	PUNCT
iajs-2800	199	46	θ	θ	NOUN
iajs-2800	199	47	)	)	PUNCT
iajs-2800	199	48	,	,	PUNCT
iajs-2800	199	49	θ	θ	PROPN
iajs-2800	199	50	(	(	PUNCT
iajs-2800	199	51	r	r	NOUN
iajs-2800	199	52	^^	^^	SYM
iajs-2800	199	53	2	2	NUM
iajs-2800	199	54	^	^	SYM
iajs-2800	199	55			NUM
iajs-2800	199	56	.the	.the	DET
iajs-2800	199	57	value	value	NOUN
iajs-2800	199	58	of	of	ADP
iajs-2800	199	59	θ	θ	PROPN
iajs-2800	199	60	minimizes	minimize	VERB
iajs-2800	199	61	the	the	DET
iajs-2800	199	62	risk	risk	NOUN
iajs-2800	199	63	function	function	NOUN
iajs-2800	199	64	under	under	ADP
iajs-2800	199	65	the	the	DET
iajs-2800	199	66	proposed	propose	VERB
iajs-2800	199	67	exponential	exponential	ADJ
iajs-2800	199	68	loss	loss	NOUN
iajs-2800	199	69	function	function	NOUN
iajs-2800	199	70	which	which	PRON
iajs-2800	199	71	satisfies	satisfy	VERB
iajs-2800	199	72	the	the	DET
iajs-2800	199	73	following	follow	VERB
iajs-2800	199	74	condition	condition	NOUN
iajs-2800	199	75	0	0	NUM
iajs-2800	199	76	θ)θ	θ)θ	NOUN
iajs-2800	200	1	r	r	X
iajs-2800	200	2	(	(	PUNCT
iajs-2800	200	3	^	^	PUNCT
iajs-2800	200	4	^	^	PUNCT
iajs-2800	200	5	θ	θ	PROPN
iajs-2800	200	6			NUM
iajs-2800	200	7			ADJ
iajs-2800	200	8			PROPN
iajs-2800	200	9	;	;	PUNCT
iajs-2800	200	10	we	we	PRON
iajs-2800	200	11	get	get	VERB
iajs-2800	200	12	bayes	bayes	PROPN
iajs-2800	200	13	estimator	estimator	NOUN
iajs-2800	200	14	of	of	ADP
iajs-2800	200	15	θ	θ	PROPN
iajs-2800	200	16	denoted	denote	VERB
iajs-2800	200	17	by	by	ADP
iajs-2800	200	18	θ	θ	PROPN
iajs-2800	200	19	^	^	PUNCT
iajs-2800	200	20	for	for	ADP
iajs-2800	200	21	each	each	PRON
iajs-2800	200	22	of	of	ADP
iajs-2800	200	23	the	the	DET
iajs-2800	200	24	previous	previous	ADJ
iajs-2800	200	25	priors	prior	NOUN
iajs-2800	200	26	)	)	PUNCT
iajs-2800	200	27	(	(	PUNCT
iajs-2800	200	28	18	18	NUM
iajs-2800	200	29	)	)	PUNCT
iajs-2800	200	30	dθ	dθ	PROPN
iajs-2800	200	31	t	t	PROPN
iajs-2800	200	32	)	)	PUNCT
iajs-2800	200	33	\θ	\θ	NOUN
iajs-2800	200	34	h	h	NOUN
iajs-2800	200	35	(	(	PUNCT
iajs-2800	200	36	)	)	PUNCT
iajs-2800	200	37	exp(θln(t	exp(θln(t	NOUN
iajs-2800	200	38	)	)	PUNCT
iajs-2800	200	39	\θ	\θ	NOUN
iajs-2800	200	40	)	)	PUNCT
iajs-2800	200	41	exp	exp	NOUN
iajs-2800	200	42	(	(	PUNCT
iajs-2800	200	43	e(lnθ	e(lnθ	PROPN
iajs-2800	200	44	0	0	NUM
iajs-2800	200	45	^	^	SYM
iajs-2800	200	46			PUNCT
iajs-2800	200	47			VERB
iajs-2800	200	48			NUM
iajs-2800	200	49	(	(	PUNCT
iajs-2800	200	50	a	a	NOUN
iajs-2800	200	51	)	)	PUNCT
iajs-2800	200	52	.	.	PUNCT
iajs-2800	201	1	the	the	DET
iajs-2800	201	2	bayes	bayes	PROPN
iajs-2800	201	3	estimator	estimator	NOUN
iajs-2800	201	4	for	for	ADP
iajs-2800	201	5	parameter	parameter	NOUN
iajs-2800	201	6	under	under	ADP
iajs-2800	201	7	erlang	erlang	PROPN
iajs-2800	201	8	prior	prior	ADV
iajs-2800	201	9	can	can	AUX
iajs-2800	201	10	be	be	AUX
iajs-2800	201	11	derived	derive	VERB
iajs-2800	201	12	as	as	SCONJ
iajs-2800	201	13	follows	follow	VERB
iajs-2800	201	14	)	)	PUNCT
iajs-2800	201	15	(	(	PUNCT
iajs-2800	201	16	18	18	NUM
iajs-2800	201	17	)	)	PUNCT
iajs-2800	201	18	dθ	dθ	PROPN
iajs-2800	201	19	t	t	PROPN
iajs-2800	201	20	)	)	PUNCT
iajs-2800	201	21	\θ	\θ	NOUN
iajs-2800	201	22	(	(	PUNCT
iajs-2800	201	23	h	h	NOUN
iajs-2800	201	24	θ	θ	NOUN
iajs-2800	201	25	)	)	PUNCT
iajs-2800	201	26	exp(ln(t	exp(ln(t	PROPN
iajs-2800	201	27	)	)	PUNCT
iajs-2800	201	28	\θ	\θ	NOUN
iajs-2800	201	29	)	)	PUNCT
iajs-2800	201	30	exp	exp	NOUN
iajs-2800	201	31	(	(	PUNCT
iajs-2800	201	32	lne(θ	lne(θ	VERB
iajs-2800	201	33	1	1	NUM
iajs-2800	201	34	0	0	NUM
iajs-2800	201	35	^	^	PUNCT
iajs-2800	201	36			PUNCT
iajs-2800	201	37			NOUN
iajs-2800	201	38			NUM
iajs-2800	201	39	)	)	PUNCT
iajs-2800	201	40	(	(	PUNCT
iajs-2800	201	41	19	19	NUM
iajs-2800	201	42	)	)	PUNCT
iajs-2800	201	43	dθ	dθ	NOUN
iajs-2800	201	44	)	)	PUNCT
iajs-2800	201	45	)	)	PUNCT
iajs-2800	202	1	1	1	NUM
iajs-2800	202	2	-	-	SYM
iajs-2800	202	3	n	n	CCONJ
iajs-2800	202	4	(	(	PUNCT
iajs-2800	202	5	δ	δ	PROPN
iajs-2800	202	6	θ	θ	PROPN
iajs-2800	202	7	exp	exp	NOUN
iajs-2800	202	8	(	(	PUNCT
iajs-2800	202	9	θ	θ	PROPN
iajs-2800	202	10	)	)	PUNCT
iajs-2800	202	11	2tγ	2tγ	NOUN
iajs-2800	202	12	(	(	PUNCT
iajs-2800	202	13	t	t	PROPN
iajs-2800	202	14	)	)	PUNCT
iajs-2800	202	15	n	n	CCONJ
iajs-2800	202	16	(	(	PUNCT
iajs-2800	202	17	δ	δ	PROPN
iajs-2800	202	18	0	0	NUM
iajs-2800	203	1	ln	ln	PROPN
iajs-2800	203	2	(	(	PUNCT
iajs-2800	203	3	θ	θ	PROPN
iajs-2800	203	4	)	)	PUNCT
iajs-2800	203	5	dθ	dθ	PROPN
iajs-2800	203	6	)	)	PUNCT
iajs-2800	203	7	)	)	PUNCT
iajs-2800	204	1	n	n	CCONJ
iajs-2800	204	2	(	(	PUNCT
iajs-2800	204	3	δ	δ	PROPN
iajs-2800	204	4	θ	θ	PROPN
iajs-2800	204	5	exp	exp	NOUN
iajs-2800	204	6	(	(	PUNCT
iajs-2800	204	7	θ	θ	PROPN
iajs-2800	204	8	)	)	PUNCT
iajs-2800	204	9	2tγ	2tγ	NOUN
iajs-2800	204	10	(	(	PUNCT
iajs-2800	204	11	t	t	PROPN
iajs-2800	204	12	)	)	PUNCT
iajs-2800	204	13	n	n	CCONJ
iajs-2800	204	14	(	(	PUNCT
iajs-2800	204	15	δ	δ	PROPN
iajs-2800	204	16	θ	θ	PROPN
iajs-2800	204	17	)	)	PUNCT
iajs-2800	204	18	exp(ln(θ	exp(ln(θ	PROPN
iajs-2800	204	19	1)2	1)2	NUM
iajs-2800	204	20	(	(	PUNCT
iajs-2800	204	21	n	n	NUM
iajs-2800	204	22	2)n	2)n	NUM
iajs-2800	204	23	(	(	PUNCT
iajs-2800	204	24	1)2	1)2	NUM
iajs-2800	204	25	(	(	PUNCT
iajs-2800	204	26	n	n	NUM
iajs-2800	204	27	2)n	2)n	NUM
iajs-2800	204	28	(	(	PUNCT
iajs-2800	204	29	i	i	NOUN
iajs-2800	204	30	n	n	VERB
iajs-2800	204	31	1i	1i	NOUN
iajs-2800	204	32	i	i	PRON
iajs-2800	204	33	n	n	VERB
iajs-2800	204	34	1i	1i	NUM
iajs-2800	204	35	t	t	NOUN
iajs-2800	205	1	i1i	i1i	ADP
iajs-2800	205	2	i1i^	i1i^	NOUN
iajs-2800	205	3	t	t	NOUN
iajs-2800	205	4	i1i	i1i	ADP
iajs-2800	205	5	i1i	i1i	ADP
iajs-2800	205	6	0	0	NUM
iajs-2800	205	7	^	^	PUNCT
iajs-2800	205	8			PROPN
iajs-2800	205	9			PROPN
iajs-2800	205	10			X
iajs-2800	205	11			PUNCT
iajs-2800	205	12			PUNCT
iajs-2800	205	13			VERB
iajs-2800	205	14			PROPN
iajs-2800	205	15			PROPN
iajs-2800	205	16			PROPN
iajs-2800	205	17			X
iajs-2800	205	18			VERB
iajs-2800	205	19			PROPN
iajs-2800	205	20			PROPN
iajs-2800	205	21			ADJ
iajs-2800	205	22			PROPN
iajs-2800	205	23			PUNCT
iajs-2800	205	24			X
iajs-2800	206	1			NUM
iajs-2800	207	1			NUM
iajs-2800	207	2			X
iajs-2800	208	1			NUM
iajs-2800	208	2			PROPN
iajs-2800	208	3			NUM
iajs-2800	208	4			PROPN
iajs-2800	208	5	by	by	ADP
iajs-2800	208	6	multiplying	multiply	VERB
iajs-2800	208	7	the	the	DET
iajs-2800	208	8	integral	integral	ADJ
iajs-2800	208	9	in	in	ADP
iajs-2800	208	10	equation	equation	NOUN
iajs-2800	208	11	(	(	PUNCT
iajs-2800	208	12	19	19	NUM
iajs-2800	208	13	)	)	PUNCT
iajs-2800	208	14	by	by	ADP
iajs-2800	208	15	the	the	DET
iajs-2800	208	16	quantity	quantity	NOUN
iajs-2800	208	17	which	which	PRON
iajs-2800	208	18	equals	equal	VERB
iajs-2800	208	19	to	to	ADP
iajs-2800	208	20	t	t	PROPN
iajs-2800	208	21	)	)	PUNCT
iajs-2800	208	22	1	1	NUM
iajs-2800	208	23	-	-	SYM
iajs-2800	208	24	n	n	PRON
iajs-2800	208	25	(	(	PUNCT
iajs-2800	208	26	δ	δ	PROPN
iajs-2800	208	27	t	t	PROPN
iajs-2800	208	28	)	)	PUNCT
iajs-2800	208	29	1	1	NUM
iajs-2800	208	30	-	-	SYM
iajs-2800	208	31	n	n	PRON
iajs-2800	208	32	(	(	PUNCT
iajs-2800	208	33	δ	δ	PROPN
iajs-2800	208	34	2)n	2)n	NUM
iajs-2800	208	35	(	(	PUNCT
iajs-2800	208	36	2)n	2)n	NUM
iajs-2800	208	37	(	(	PUNCT
iajs-2800	208	38	i1i	i1i	ADP
iajs-2800	208	39	i1i	i1i	PROPN
iajs-2800	208	40			ADV
iajs-2800	208	41			VERB
iajs-2800	208	42			X
iajs-2800	208	43			VERB
iajs-2800	208	44			X
iajs-2800	208	45			PROPN
iajs-2800	209	1			PROPN
iajs-2800	209	2			ADJ
iajs-2800	209	3	,	,	PUNCT
iajs-2800	209	4	it	it	PRON
iajs-2800	209	5	yields	yield	VERB
iajs-2800	209	6	)	)	PUNCT
iajs-2800	210	1	θ)b(t	θ)b(t	PROPN
iajs-2800	210	2	,	,	PUNCT
iajs-2800	210	3	t	t	NOUN
iajs-2800	210	4	)	)	PUNCT
iajs-2800	210	5	1	1	NUM
iajs-2800	210	6	-	-	SYM
iajs-2800	210	7	n	n	PRON
iajs-2800	210	8	(	(	PUNCT
iajs-2800	210	9	δ	δ	PROPN
iajs-2800	210	10	t	t	PROPN
iajs-2800	210	11	)	)	PUNCT
iajs-2800	210	12	n	n	CCONJ
iajs-2800	210	13	(	(	PUNCT
iajs-2800	210	14	δ	δ	PROPN
iajs-2800	210	15	ln	ln	PROPN
iajs-2800	210	16	(	(	PUNCT
iajs-2800	210	17	θ	θ	PROPN
iajs-2800	210	18	2)n	2)n	NUM
iajs-2800	210	19	(	(	PUNCT
iajs-2800	210	20	2)n	2)n	NUM
iajs-2800	210	21	(	(	PUNCT
iajs-2800	210	22	i1i	i1i	ADP
iajs-2800	210	23	i1i^	i1i^	PROPN
iajs-2800	210	24			ADV
iajs-2800	210	25			VERB
iajs-2800	210	26			X
iajs-2800	210	27			VERB
iajs-2800	210	28			X
iajs-2800	210	29			PROPN
iajs-2800	211	1			PROPN
iajs-2800	211	2			NUM
iajs-2800	211	3			NOUN
iajs-2800	211	4	,	,	PUNCT
iajs-2800	211	5	where	where	SCONJ
iajs-2800	211	6	ibn	ibn	PROPN
iajs-2800	211	7	al	al	PROPN
iajs-2800	211	8	-	-	PUNCT
iajs-2800	211	9	haitham	haitham	PROPN
iajs-2800	211	10	jour	jour	X
iajs-2800	211	11	.	.	PROPN
iajs-2800	212	1	for	for	ADP
iajs-2800	212	2	pure	pure	ADJ
iajs-2800	212	3	&	&	CCONJ
iajs-2800	212	4	appl	appl	PROPN
iajs-2800	212	5	.	.	PUNCT
iajs-2800	213	1	sci	sci	PROPN
iajs-2800	213	2	.	.	PROPN
iajs-2800	214	1	53	53	NUM
iajs-2800	214	2	(	(	PUNCT
iajs-2800	214	3	1)2022	1)2022	NOUN
iajs-2800	214	4	67	67	NUM
iajs-2800	214	5	1	1	NUM
iajs-2800	214	6	dθ	dθ	NOUN
iajs-2800	214	7	)	)	PUNCT
iajs-2800	214	8	)	)	PUNCT
iajs-2800	214	9	1	1	NUM
iajs-2800	214	10	-	-	SYM
iajs-2800	214	11	n	n	CCONJ
iajs-2800	214	12	(	(	PUNCT
iajs-2800	214	13	δ	δ	PROPN
iajs-2800	214	14	θ	θ	PROPN
iajs-2800	214	15	exp	exp	NOUN
iajs-2800	214	16	(	(	PUNCT
iajs-2800	214	17	θ	θ	PROPN
iajs-2800	214	18	)	)	PUNCT
iajs-2800	214	19	2	2	NUM
iajs-2800	214	20	t	t	NOUN
iajs-2800	214	21	γ	γ	X
iajs-2800	214	22	(	(	PUNCT
iajs-2800	214	23	t	t	PROPN
iajs-2800	214	24	)	)	PUNCT
iajs-2800	214	25	1	1	NUM
iajs-2800	214	26	-	-	SYM
iajs-2800	214	27	n	n	CCONJ
iajs-2800	214	28	(	(	PUNCT
iajs-2800	214	29	δ	δ	PROPN
iajs-2800	214	30	0	0	NUM
iajs-2800	214	31	)	)	PUNCT
iajs-2800	214	32	θ	θ	PROPN
iajs-2800	214	33	t	t	PROPN
iajs-2800	214	34	,	,	PUNCT
iajs-2800	214	35	b	b	PROPN
iajs-2800	214	36	(	(	PUNCT
iajs-2800	214	37	1)2	1)2	NUM
iajs-2800	214	38	(	(	PUNCT
iajs-2800	214	39	n	n	NUM
iajs-2800	214	40	2)n	2)n	NUM
iajs-2800	215	1	(	(	PUNCT
iajs-2800	216	1	i	i	NOUN
iajs-2800	216	2	n	n	VERB
iajs-2800	216	3	1i	1i	NOUN
iajs-2800	216	4	t	t	NOUN
iajs-2800	216	5	i1i	i1i	X
iajs-2800	216	6	i1i	i1i	AUX
iajs-2800	216	7			VERB
iajs-2800	216	8			PROPN
iajs-2800	216	9			X
iajs-2800	216	10			X
iajs-2800	216	11			PUNCT
iajs-2800	216	12			VERB
iajs-2800	216	13			PRON
iajs-2800	216	14			PROPN
iajs-2800	216	15			X
iajs-2800	216	16			X
iajs-2800	217	1			NUM
iajs-2800	218	1			NUM
iajs-2800	218	2			NOUN
iajs-2800	218	3	,	,	PUNCT
iajs-2800	218	4	be	be	AUX
iajs-2800	218	5	the	the	DET
iajs-2800	218	6	integral	integral	ADJ
iajs-2800	218	7	of	of	ADP
iajs-2800	218	8	the	the	DET
iajs-2800	218	9	pdf	pdf	NOUN
iajs-2800	218	10	of	of	ADP
iajs-2800	218	11	gamma	gamma	NOUN
iajs-2800	218	12	distribution	distribution	NOUN
iajs-2800	218	13	[	[	X
iajs-2800	218	14	11	11	NUM
iajs-2800	218	15	]	]	PUNCT
iajs-2800	218	16	,	,	PUNCT
iajs-2800	218	17	i.e.	i.e.	X
iajs-2800	218	18	)	)	PUNCT
iajs-2800	218	19	20	20	NUM
iajs-2800	218	20	....	....	PUNCT
iajs-2800	218	21	(	(	PUNCT
iajs-2800	218	22	t	t	NOUN
iajs-2800	218	23	)	)	PUNCT
iajs-2800	218	24	1	1	NUM
iajs-2800	218	25	-	-	PUNCT
iajs-2800	218	26	n	n	CCONJ
iajs-2800	218	27	δ	δ	PROPN
iajs-2800	218	28	n	n	PRON
iajs-2800	218	29	δ	δ	PROPN
iajs-2800	218	30	(	(	PUNCT
iajs-2800	218	31	ln	ln	PROPN
iajs-2800	218	32	θ	θ	PROPN
iajs-2800	218	33	)	)	PUNCT
iajs-2800	218	34	t	t	NOUN
iajs-2800	218	35	)	)	PUNCT
iajs-2800	218	36	1	1	NUM
iajs-2800	218	37	-	-	SYM
iajs-2800	218	38	n	n	PRON
iajs-2800	218	39	(	(	PUNCT
iajs-2800	218	40	δ	δ	PROPN
iajs-2800	218	41	t	t	PROPN
iajs-2800	218	42	)	)	PUNCT
iajs-2800	218	43	n	n	CCONJ
iajs-2800	218	44	(	(	PUNCT
iajs-2800	218	45	δ	δ	PROPN
iajs-2800	218	46	ln(θ	ln(θ	X
iajs-2800	218	47	2)n	2)n	NUM
iajs-2800	218	48	(	(	PUNCT
iajs-2800	218	49	2)n	2)n	NUM
iajs-2800	218	50	(	(	PUNCT
iajs-2800	218	51	2)n	2)n	NUM
iajs-2800	218	52	(	(	PUNCT
iajs-2800	218	53	i1i	i1i	ADJ
iajs-2800	218	54	^	^	PUNCT
iajs-2800	218	55	i1i	i1i	ADP
iajs-2800	218	56	i1i^	i1i^	PROPN
iajs-2800	218	57			ADV
iajs-2800	218	58			VERB
iajs-2800	218	59			PUNCT
iajs-2800	218	60			X
iajs-2800	218	61			ADV
iajs-2800	218	62			PUNCT
iajs-2800	218	63			PROPN
iajs-2800	218	64			PROPN
iajs-2800	218	65			VERB
iajs-2800	218	66			X
iajs-2800	218	67			PROPN
iajs-2800	219	1			PROPN
iajs-2800	219	2			ADJ
iajs-2800	219	3			NUM
iajs-2800	219	4			NOUN
iajs-2800	219	5	(	(	PUNCT
iajs-2800	219	6	b	b	NOUN
iajs-2800	219	7	)	)	PUNCT
iajs-2800	219	8	.	.	PUNCT
iajs-2800	220	1	the	the	DET
iajs-2800	220	2	bayes	bayes	PROPN
iajs-2800	220	3	estimator	estimator	NOUN
iajs-2800	220	4	for	for	ADP
iajs-2800	220	5	parameter	parameter	NOUN
iajs-2800	220	6	under	under	ADP
iajs-2800	220	7	inverse	inverse	NOUN
iajs-2800	220	8	levy	levy	NOUN
iajs-2800	220	9	prior	prior	ADV
iajs-2800	220	10	can	can	AUX
iajs-2800	220	11	be	be	AUX
iajs-2800	220	12	derived	derive	VERB
iajs-2800	220	13	as	as	SCONJ
iajs-2800	220	14	follows	follow	VERB
iajs-2800	220	15	)	)	PUNCT
iajs-2800	220	16	(	(	PUNCT
iajs-2800	220	17	18	18	NUM
iajs-2800	220	18	)	)	PUNCT
iajs-2800	220	19	dθ	dθ	PROPN
iajs-2800	220	20	t	t	PROPN
iajs-2800	220	21	)	)	PUNCT
iajs-2800	220	22	\θ	\θ	NOUN
iajs-2800	220	23	(	(	PUNCT
iajs-2800	220	24	h	h	NOUN
iajs-2800	220	25	θ	θ	NOUN
iajs-2800	220	26	)	)	PUNCT
iajs-2800	220	27	exp(ln(t	exp(ln(t	PROPN
iajs-2800	220	28	)	)	PUNCT
iajs-2800	220	29	\θ	\θ	NOUN
iajs-2800	220	30	)	)	PUNCT
iajs-2800	220	31	exp	exp	NOUN
iajs-2800	220	32	(	(	PUNCT
iajs-2800	220	33	lne(θ	lne(θ	VERB
iajs-2800	220	34	2	2	NUM
iajs-2800	220	35	0	0	NUM
iajs-2800	220	36	^	^	PUNCT
iajs-2800	220	37			PUNCT
iajs-2800	220	38			NOUN
iajs-2800	220	39			NUM
iajs-2800	220	40	)	)	PUNCT
iajs-2800	221	1	(	(	PUNCT
iajs-2800	221	2	21	21	NUM
iajs-2800	221	3	)	)	PUNCT
iajs-2800	221	4	dθ	dθ	PROPN
iajs-2800	221	5	1))-n	1))-n	NUM
iajs-2800	221	6	(	(	PUNCT
iajs-2800	221	7	0.5v	0.5v	NUM
iajs-2800	221	8	θ	θ	PROPN
iajs-2800	221	9	exp	exp	NOUN
iajs-2800	221	10	(	(	PUNCT
iajs-2800	221	11	θ	θ	PROPN
iajs-2800	221	12	)	)	PUNCT
iajs-2800	221	13	5.0tγ	5.0tγ	NUM
iajs-2800	221	14	(	(	PUNCT
iajs-2800	221	15	t	t	PROPN
iajs-2800	221	16	)	)	PUNCT
iajs-2800	221	17	n	n	CCONJ
iajs-2800	221	18	(	(	PUNCT
iajs-2800	221	19	0.5v	0.5v	NUM
iajs-2800	221	20	0	0	X
iajs-2800	221	21	ln	ln	ADJ
iajs-2800	221	22	(	(	PUNCT
iajs-2800	221	23	θ	θ	PROPN
iajs-2800	221	24	)	)	PUNCT
iajs-2800	221	25	dθ	dθ	PROPN
iajs-2800	221	26	)	)	PUNCT
iajs-2800	221	27	)	)	PUNCT
iajs-2800	222	1	n	n	CCONJ
iajs-2800	222	2	(	(	PUNCT
iajs-2800	222	3	0.5v	0.5v	NUM
iajs-2800	222	4	θ	θ	PROPN
iajs-2800	222	5	exp	exp	NOUN
iajs-2800	222	6	(	(	PUNCT
iajs-2800	222	7	θ	θ	PROPN
iajs-2800	222	8	)	)	PUNCT
iajs-2800	223	1	5.0tγ	5.0tγ	NUM
iajs-2800	223	2	(	(	PUNCT
iajs-2800	223	3	t	t	PROPN
iajs-2800	223	4	)	)	PUNCT
iajs-2800	223	5	n	n	CCONJ
iajs-2800	223	6	(	(	PUNCT
iajs-2800	223	7	0.5v	0.5v	NUM
iajs-2800	223	8	θ	θ	NOUN
iajs-2800	223	9	)	)	PUNCT
iajs-2800	223	10	exp(ln(θ	exp(ln(θ	PROPN
iajs-2800	223	11	1)5.0	1)5.0	PROPN
iajs-2800	223	12	(	(	PUNCT
iajs-2800	223	13	n	n	NOUN
iajs-2800	223	14	)	)	PUNCT
iajs-2800	223	15	5.0n	5.0n	PROPN
iajs-2800	223	16	(	(	PUNCT
iajs-2800	223	17	1)5.0	1)5.0	PROPN
iajs-2800	223	18	(	(	PUNCT
iajs-2800	223	19	n	n	NOUN
iajs-2800	223	20	)	)	PUNCT
iajs-2800	223	21	5.0n	5.0n	NUM
iajs-2800	223	22	(	(	PUNCT
iajs-2800	223	23	i	i	NOUN
iajs-2800	223	24	n	n	VERB
iajs-2800	223	25	1i	1i	NOUN
iajs-2800	224	1	i	i	PRON
iajs-2800	224	2	n	n	VERB
iajs-2800	224	3	1i	1i	NUM
iajs-2800	224	4	t	t	NOUN
iajs-2800	225	1	i1i	i1i	ADP
iajs-2800	225	2	i1i^	i1i^	NOUN
iajs-2800	225	3	t	t	NOUN
iajs-2800	225	4	i1i	i1i	ADP
iajs-2800	225	5	i1i	i1i	ADP
iajs-2800	225	6	0	0	NUM
iajs-2800	225	7	^	^	PUNCT
iajs-2800	225	8			PROPN
iajs-2800	225	9			PROPN
iajs-2800	225	10			X
iajs-2800	225	11			PUNCT
iajs-2800	225	12			PUNCT
iajs-2800	225	13			VERB
iajs-2800	225	14			PROPN
iajs-2800	225	15			PROPN
iajs-2800	225	16			PROPN
iajs-2800	225	17			X
iajs-2800	225	18			VERB
iajs-2800	225	19			PROPN
iajs-2800	225	20			PROPN
iajs-2800	225	21			ADJ
iajs-2800	225	22			PROPN
iajs-2800	225	23			PUNCT
iajs-2800	225	24			X
iajs-2800	226	1			NUM
iajs-2800	227	1			NUM
iajs-2800	227	2			X
iajs-2800	228	1			NUM
iajs-2800	228	2			VERB
iajs-2800	229	1			NUM
iajs-2800	229	2			NOUN
iajs-2800	229	3			PUNCT
iajs-2800	229	4	by	by	ADP
iajs-2800	229	5	multiplying	multiply	VERB
iajs-2800	229	6	the	the	DET
iajs-2800	229	7	integral	integral	ADJ
iajs-2800	229	8	in	in	ADP
iajs-2800	229	9	equation	equation	NOUN
iajs-2800	229	10	(	(	PUNCT
iajs-2800	229	11	21	21	NUM
iajs-2800	229	12	)	)	PUNCT
iajs-2800	229	13	by	by	ADP
iajs-2800	229	14	the	the	DET
iajs-2800	229	15	quantity	quantity	NOUN
iajs-2800	229	16	which	which	PRON
iajs-2800	229	17	equals	equal	VERB
iajs-2800	229	18	to	to	ADP
iajs-2800	229	19	t	t	PROPN
iajs-2800	229	20	)	)	PUNCT
iajs-2800	229	21	1	1	NUM
iajs-2800	229	22	-	-	SYM
iajs-2800	229	23	n	n	PRON
iajs-2800	229	24	(	(	PUNCT
iajs-2800	229	25	0.5v	0.5v	NOUN
iajs-2800	229	26	t	t	NOUN
iajs-2800	229	27	)	)	PUNCT
iajs-2800	229	28	1	1	NUM
iajs-2800	229	29	-	-	SYM
iajs-2800	229	30	n	n	PRON
iajs-2800	229	31	(	(	PUNCT
iajs-2800	229	32	0.5v	0.5v	X
iajs-2800	229	33	)	)	PUNCT
iajs-2800	229	34	5.0n	5.0n	NUM
iajs-2800	229	35	(	(	PUNCT
iajs-2800	229	36	)	)	PUNCT
iajs-2800	229	37	5.0n	5.0n	NUM
iajs-2800	229	38	(	(	PUNCT
iajs-2800	229	39	i1i	i1i	ADP
iajs-2800	229	40	i1i	i1i	PROPN
iajs-2800	229	41			ADV
iajs-2800	229	42			VERB
iajs-2800	229	43			X
iajs-2800	229	44			VERB
iajs-2800	229	45			X
iajs-2800	229	46			PROPN
iajs-2800	230	1			PROPN
iajs-2800	230	2			ADJ
iajs-2800	230	3	,	,	PUNCT
iajs-2800	230	4	it	it	PRON
iajs-2800	230	5	yields	yield	VERB
iajs-2800	230	6	)	)	PUNCT
iajs-2800	230	7	)	)	PUNCT
iajs-2800	231	1	θ	θ	PROPN
iajs-2800	231	2	t	t	PROPN
iajs-2800	231	3	,	,	PUNCT
iajs-2800	231	4	b1	b1	PROPN
iajs-2800	231	5	(	(	PUNCT
iajs-2800	231	6	t	t	PROPN
iajs-2800	231	7	)	)	PUNCT
iajs-2800	231	8	1	1	NUM
iajs-2800	231	9	-	-	SYM
iajs-2800	231	10	n	n	PRON
iajs-2800	231	11	(	(	PUNCT
iajs-2800	231	12	0.5v	0.5v	NOUN
iajs-2800	231	13	t	t	PROPN
iajs-2800	231	14	)	)	PUNCT
iajs-2800	231	15	n	n	CCONJ
iajs-2800	231	16	(	(	PUNCT
iajs-2800	231	17	0.5v	0.5v	NUM
iajs-2800	231	18	ln	ln	ADJ
iajs-2800	231	19	(	(	PUNCT
iajs-2800	231	20	θ	θ	PROPN
iajs-2800	231	21	)	)	PUNCT
iajs-2800	231	22	5.0n	5.0n	NUM
iajs-2800	231	23	(	(	PUNCT
iajs-2800	231	24	)	)	PUNCT
iajs-2800	231	25	5.0n	5.0n	NUM
iajs-2800	231	26	(	(	PUNCT
iajs-2800	231	27	i1i	i1i	INTJ
iajs-2800	231	28	i1i^	i1i^	PROPN
iajs-2800	231	29			ADV
iajs-2800	231	30			VERB
iajs-2800	231	31			X
iajs-2800	231	32			VERB
iajs-2800	231	33			X
iajs-2800	231	34			PROPN
iajs-2800	231	35			PROPN
iajs-2800	232	1			ADJ
iajs-2800	232	2			NOUN
iajs-2800	232	3	,	,	PUNCT
iajs-2800	232	4	where	where	SCONJ
iajs-2800	232	5	1	1	NUM
iajs-2800	232	6	dθ	dθ	PROPN
iajs-2800	232	7	1))-n	1))-n	NUM
iajs-2800	232	8	(	(	PUNCT
iajs-2800	232	9	0.5v	0.5v	NUM
iajs-2800	232	10	θ	θ	PROPN
iajs-2800	232	11	exp	exp	NOUN
iajs-2800	232	12	(	(	PUNCT
iajs-2800	232	13	θ	θ	PROPN
iajs-2800	232	14	)	)	PUNCT
iajs-2800	232	15	5.0tγ	5.0tγ	NUM
iajs-2800	232	16	(	(	PUNCT
iajs-2800	232	17	t	t	PROPN
iajs-2800	232	18	1)-n	1)-n	NUM
iajs-2800	232	19	(	(	PUNCT
iajs-2800	232	20	0.5v	0.5v	NOUN
iajs-2800	232	21	0	0	NUM
iajs-2800	232	22	)	)	PUNCT
iajs-2800	232	23	θ	θ	PROPN
iajs-2800	232	24	t	t	PROPN
iajs-2800	232	25	,	,	PUNCT
iajs-2800	232	26	b1	b1	PROPN
iajs-2800	232	27	(	(	PUNCT
iajs-2800	232	28	1)5.0	1)5.0	PROPN
iajs-2800	232	29	(	(	PUNCT
iajs-2800	232	30	n	n	NOUN
iajs-2800	232	31	)	)	PUNCT
iajs-2800	232	32	5.0n	5.0n	NUM
iajs-2800	232	33	(	(	PUNCT
iajs-2800	232	34	i	i	NOUN
iajs-2800	232	35	n	n	VERB
iajs-2800	232	36	1i	1i	NOUN
iajs-2800	232	37	t	t	NOUN
iajs-2800	233	1	i1i	i1i	AUX
iajs-2800	233	2	i1i	i1i	AUX
iajs-2800	233	3			VERB
iajs-2800	233	4			PROPN
iajs-2800	233	5			X
iajs-2800	233	6			X
iajs-2800	233	7			PUNCT
iajs-2800	233	8			VERB
iajs-2800	233	9			PRON
iajs-2800	233	10			PROPN
iajs-2800	233	11			X
iajs-2800	233	12			X
iajs-2800	234	1			NUM
iajs-2800	235	1			NUM
iajs-2800	235	2			NOUN
iajs-2800	235	3	,	,	PUNCT
iajs-2800	235	4	be	be	AUX
iajs-2800	235	5	the	the	DET
iajs-2800	235	6	integral	integral	ADJ
iajs-2800	235	7	of	of	ADP
iajs-2800	235	8	the	the	DET
iajs-2800	235	9	pdf	pdf	NOUN
iajs-2800	235	10	of	of	ADP
iajs-2800	235	11	gamma	gamma	NOUN
iajs-2800	235	12	distribution	distribution	NOUN
iajs-2800	235	13	[	[	X
iajs-2800	235	14	11	11	NUM
iajs-2800	235	15	]	]	PUNCT
iajs-2800	235	16	,	,	PUNCT
iajs-2800	235	17	i.e.	i.e.	X
iajs-2800	235	18	)	)	PUNCT
iajs-2800	235	19	22	22	NUM
iajs-2800	235	20	....	....	PUNCT
iajs-2800	235	21	(	(	PUNCT
iajs-2800	235	22	t	t	NOUN
iajs-2800	235	23	)	)	PUNCT
iajs-2800	235	24	1	1	NUM
iajs-2800	235	25	-	-	NUM
iajs-2800	235	26	n5.0	n5.0	NOUN
iajs-2800	235	27	n	n	NOUN
iajs-2800	235	28	0.5v	0.5v	NUM
iajs-2800	235	29	(	(	PUNCT
iajs-2800	235	30	ln	ln	PROPN
iajs-2800	235	31	θ	θ	PROPN
iajs-2800	235	32	)	)	PUNCT
iajs-2800	235	33	t	t	NOUN
iajs-2800	235	34	)	)	PUNCT
iajs-2800	235	35	1	1	NUM
iajs-2800	235	36	-	-	PUNCT
iajs-2800	235	37	n(0.5v	n(0.5v	X
iajs-2800	235	38	t	t	NOUN
iajs-2800	235	39	)	)	PUNCT
iajs-2800	235	40	n	n	CCONJ
iajs-2800	235	41	(	(	PUNCT
iajs-2800	235	42	0.5v	0.5v	INTJ
iajs-2800	235	43	ln(θ	ln(θ	NOUN
iajs-2800	235	44	)	)	PUNCT
iajs-2800	235	45	5.0n	5.0n	X
iajs-2800	235	46	(	(	PUNCT
iajs-2800	235	47	)	)	PUNCT
iajs-2800	235	48	5.0n	5.0n	NUM
iajs-2800	235	49	(	(	PUNCT
iajs-2800	235	50	)	)	PUNCT
iajs-2800	235	51	5.0n	5.0n	PROPN
iajs-2800	235	52	(	(	PUNCT
iajs-2800	235	53	i1i	i1i	ADJ
iajs-2800	235	54	^	^	PUNCT
iajs-2800	235	55	i1i	i1i	ADP
iajs-2800	235	56	i1i^	i1i^	PROPN
iajs-2800	235	57			ADV
iajs-2800	235	58			VERB
iajs-2800	235	59			PUNCT
iajs-2800	235	60			X
iajs-2800	235	61			ADV
iajs-2800	235	62			PUNCT
iajs-2800	235	63			PROPN
iajs-2800	235	64			PROPN
iajs-2800	235	65			VERB
iajs-2800	235	66			X
iajs-2800	235	67			PROPN
iajs-2800	236	1			PROPN
iajs-2800	236	2			NUM
iajs-2800	237	1			NUM
iajs-2800	237	2			NUM
iajs-2800	237	3	v	v	NOUN
iajs-2800	237	4	(	(	PUNCT
iajs-2800	237	5	c	c	NOUN
iajs-2800	237	6	)	)	PUNCT
iajs-2800	237	7	.	.	PUNCT
iajs-2800	238	1	the	the	DET
iajs-2800	238	2	bayes	bayes	PROPN
iajs-2800	238	3	estimator	estimator	NOUN
iajs-2800	238	4	for	for	ADP
iajs-2800	238	5	parameter	parameter	NOUN
iajs-2800	238	6	under	under	ADP
iajs-2800	238	7	non	non	ADJ
iajs-2800	238	8	-	-	ADJ
iajs-2800	238	9	informative	informative	ADJ
iajs-2800	238	10	prior	prior	ADV
iajs-2800	238	11	can	can	AUX
iajs-2800	238	12	be	be	AUX
iajs-2800	238	13	derived	derive	VERB
iajs-2800	238	14	as	as	SCONJ
iajs-2800	238	15	follows	follow	VERB
iajs-2800	238	16	)	)	PUNCT
iajs-2800	238	17	(	(	PUNCT
iajs-2800	238	18	18	18	NUM
iajs-2800	238	19	)	)	PUNCT
iajs-2800	238	20	dθ	dθ	PROPN
iajs-2800	238	21	t	t	PROPN
iajs-2800	238	22	)	)	PUNCT
iajs-2800	238	23	\θ	\θ	NOUN
iajs-2800	238	24	(	(	PUNCT
iajs-2800	238	25	h	h	NOUN
iajs-2800	238	26	θ	θ	NOUN
iajs-2800	238	27	)	)	PUNCT
iajs-2800	238	28	exp(ln(t	exp(ln(t	PROPN
iajs-2800	238	29	)	)	PUNCT
iajs-2800	238	30	\θ	\θ	NOUN
iajs-2800	238	31	)	)	PUNCT
iajs-2800	238	32	exp	exp	NOUN
iajs-2800	238	33	(	(	PUNCT
iajs-2800	238	34	lne(θ	lne(θ	PROPN
iajs-2800	238	35	3	3	NUM
iajs-2800	238	36	0	0	NUM
iajs-2800	238	37	^	^	SYM
iajs-2800	238	38			PUNCT
iajs-2800	238	39			NOUN
iajs-2800	238	40			NUM
iajs-2800	238	41	)	)	PUNCT
iajs-2800	238	42	(	(	PUNCT
iajs-2800	238	43	23	23	X
iajs-2800	238	44	)	)	PUNCT
iajs-2800	238	45	dθ	dθ	PROPN
iajs-2800	238	46	)	)	PUNCT
iajs-2800	238	47	1)-(n	1)-(n	NUM
iajs-2800	238	48	θ	θ	NOUN
iajs-2800	238	49	exp	exp	NOUN
iajs-2800	238	50	(	(	PUNCT
iajs-2800	238	51	θ	θ	PROPN
iajs-2800	238	52	1)ctγ	1)ctγ	NUM
iajs-2800	238	53	(	(	PUNCT
iajs-2800	238	54	t	t	PROPN
iajs-2800	238	55	)	)	PUNCT
iajs-2800	238	56	(	(	PUNCT
iajs-2800	238	57	n	n	NOUN
iajs-2800	238	58	0	0	NUM
iajs-2800	238	59	ln	ln	ADJ
iajs-2800	238	60	(	(	PUNCT
iajs-2800	238	61	θ	θ	PROPN
iajs-2800	238	62	)	)	PUNCT
iajs-2800	238	63	dθ	dθ	PROPN
iajs-2800	238	64	)	)	PUNCT
iajs-2800	238	65	n	n	PROPN
iajs-2800	238	66	θ	θ	PROPN
iajs-2800	238	67	exp	exp	NOUN
iajs-2800	238	68	(	(	PUNCT
iajs-2800	238	69	θ	θ	PROPN
iajs-2800	238	70	1)ctγ	1)ctγ	NUM
iajs-2800	238	71	(	(	PUNCT
iajs-2800	238	72	t	t	PROPN
iajs-2800	238	73	)	)	PUNCT
iajs-2800	238	74	(	(	PUNCT
iajs-2800	238	75	n	n	X
iajs-2800	238	76	θ	θ	NOUN
iajs-2800	238	77	)	)	PUNCT
iajs-2800	238	78	exp(ln(θ	exp(ln(θ	PRON
iajs-2800	238	79	11)c	11)c	NUM
iajs-2800	238	80	(	(	PUNCT
iajs-2800	238	81	n	n	PROPN
iajs-2800	238	82	1)cn	1)cn	NUM
iajs-2800	238	83	(	(	PUNCT
iajs-2800	238	84	11)c	11)c	NUM
iajs-2800	238	85	(	(	PUNCT
iajs-2800	238	86	n	n	PROPN
iajs-2800	238	87	1)cn	1)cn	NUM
iajs-2800	238	88	(	(	PUNCT
iajs-2800	238	89	i	i	NOUN
iajs-2800	238	90	n	n	VERB
iajs-2800	238	91	1i	1i	NOUN
iajs-2800	239	1	i	i	PRON
iajs-2800	239	2	n	n	VERB
iajs-2800	239	3	1i	1i	NUM
iajs-2800	239	4	t	t	NOUN
iajs-2800	240	1	i1i	i1i	ADP
iajs-2800	240	2	i1i^	i1i^	NOUN
iajs-2800	240	3	t	t	NOUN
iajs-2800	240	4	i1i	i1i	ADP
iajs-2800	240	5	i1i	i1i	ADV
iajs-2800	240	6	0	0	NUM
iajs-2800	240	7	^	^	PUNCT
iajs-2800	240	8			PROPN
iajs-2800	240	9			PROPN
iajs-2800	240	10			X
iajs-2800	240	11			PUNCT
iajs-2800	240	12			VERB
iajs-2800	240	13			PRON
iajs-2800	240	14			PROPN
iajs-2800	240	15			PROPN
iajs-2800	240	16			X
iajs-2800	240	17			PROPN
iajs-2800	240	18			NOUN
iajs-2800	240	19			PROPN
iajs-2800	240	20			NOUN
iajs-2800	240	21			PROPN
iajs-2800	240	22			X
iajs-2800	241	1			NUM
iajs-2800	241	2			NUM
iajs-2800	241	3			X
iajs-2800	242	1			NUM
iajs-2800	242	2			PROPN
iajs-2800	242	3			NUM
iajs-2800	242	4			PROPN
iajs-2800	242	5	ibn	ibn	PROPN
iajs-2800	242	6	al	al	PROPN
iajs-2800	242	7	-	-	PUNCT
iajs-2800	242	8	haitham	haitham	PROPN
iajs-2800	242	9	jour	jour	X
iajs-2800	242	10	.	.	PROPN
iajs-2800	242	11	for	for	ADP
iajs-2800	242	12	pure	pure	ADJ
iajs-2800	242	13	&	&	CCONJ
iajs-2800	242	14	appl	appl	PROPN
iajs-2800	242	15	.	.	PUNCT
iajs-2800	243	1	sci	sci	PROPN
iajs-2800	243	2	.	.	PROPN
iajs-2800	244	1	53	53	NUM
iajs-2800	244	2	(	(	PUNCT
iajs-2800	244	3	1)2022	1)2022	PROPN
iajs-2800	244	4	68	68	NUM
iajs-2800	244	5	by	by	ADP
iajs-2800	244	6	multiplying	multiply	VERB
iajs-2800	244	7	the	the	DET
iajs-2800	244	8	integral	integral	ADJ
iajs-2800	244	9	in	in	ADP
iajs-2800	244	10	equation	equation	NOUN
iajs-2800	244	11	(	(	PUNCT
iajs-2800	244	12	23	23	NUM
iajs-2800	244	13	)	)	PUNCT
iajs-2800	244	14	by	by	ADP
iajs-2800	244	15	the	the	DET
iajs-2800	244	16	quantity	quantity	NOUN
iajs-2800	244	17	which	which	PRON
iajs-2800	244	18	equals	equal	VERB
iajs-2800	244	19	to	to	ADP
iajs-2800	244	20	t	t	PROPN
iajs-2800	244	21	)	)	PUNCT
iajs-2800	244	22	1-(n	1-(n	NUM
iajs-2800	244	23	t	t	NOUN
iajs-2800	244	24	)	)	PUNCT
iajs-2800	244	25	1-(n	1-(n	NUM
iajs-2800	245	1	1)cn	1)cn	NUM
iajs-2800	245	2	(	(	PUNCT
iajs-2800	245	3	1)cn	1)cn	NUM
iajs-2800	245	4	(	(	PUNCT
iajs-2800	245	5	i1i	i1i	ADP
iajs-2800	245	6	i1i	i1i	ADP
iajs-2800	245	7			PROPN
iajs-2800	245	8			PROPN
iajs-2800	245	9			X
iajs-2800	245	10			X
iajs-2800	246	1			ADV
iajs-2800	246	2			INTJ
iajs-2800	246	3	,	,	PUNCT
iajs-2800	246	4	it	it	PRON
iajs-2800	246	5	yields	yield	VERB
iajs-2800	246	6	)	)	PUNCT
iajs-2800	246	7	)	)	PUNCT
iajs-2800	247	1	θ	θ	PROPN
iajs-2800	247	2	t	t	PROPN
iajs-2800	247	3	,	,	PUNCT
iajs-2800	247	4	b2	b2	NOUN
iajs-2800	247	5	(	(	PUNCT
iajs-2800	247	6	t	t	PROPN
iajs-2800	247	7	)	)	PUNCT
iajs-2800	247	8	1-(n	1-(n	NUM
iajs-2800	247	9	t	t	NOUN
iajs-2800	247	10	)	)	PUNCT
iajs-2800	247	11	(	(	PUNCT
iajs-2800	247	12	n	n	NUM
iajs-2800	247	13	ln	ln	ADJ
iajs-2800	247	14	(	(	PUNCT
iajs-2800	247	15	θ	θ	PROPN
iajs-2800	247	16	1)cn	1)cn	PROPN
iajs-2800	247	17	(	(	PUNCT
iajs-2800	247	18	1)cn	1)cn	NUM
iajs-2800	247	19	(	(	PUNCT
iajs-2800	247	20	i1i	i1i	ADP
iajs-2800	247	21	i1i^	i1i^	NOUN
iajs-2800	247	22			PROPN
iajs-2800	247	23			PROPN
iajs-2800	247	24			X
iajs-2800	247	25			X
iajs-2800	248	1			NUM
iajs-2800	249	1			NUM
iajs-2800	249	2			NOUN
iajs-2800	249	3	,	,	PUNCT
iajs-2800	249	4	where	where	SCONJ
iajs-2800	249	5	1dθ	1dθ	ADJ
iajs-2800	249	6	)	)	PUNCT
iajs-2800	249	7	1)-(n	1)-(n	NUM
iajs-2800	249	8	θ	θ	NOUN
iajs-2800	249	9	exp	exp	NOUN
iajs-2800	249	10	(	(	PUNCT
iajs-2800	249	11	θ	θ	PROPN
iajs-2800	249	12	1)ctγ	1)ctγ	NUM
iajs-2800	249	13	(	(	PUNCT
iajs-2800	249	14	t	t	PROPN
iajs-2800	249	15	)	)	PUNCT
iajs-2800	249	16	1-(n	1-(n	NUM
iajs-2800	249	17	0	0	NUM
iajs-2800	249	18	)	)	PUNCT
iajs-2800	249	19	θ	θ	PROPN
iajs-2800	249	20	t	t	PROPN
iajs-2800	249	21	,	,	PUNCT
iajs-2800	249	22	b2	b2	NOUN
iajs-2800	249	23	(	(	PUNCT
iajs-2800	249	24	11)c	11)c	NUM
iajs-2800	249	25	(	(	PUNCT
iajs-2800	249	26	n	n	PROPN
iajs-2800	249	27	1)cn	1)cn	NUM
iajs-2800	249	28	(	(	PUNCT
iajs-2800	249	29	i	i	NOUN
iajs-2800	249	30	n	n	VERB
iajs-2800	249	31	1i	1i	NOUN
iajs-2800	249	32	t	t	NOUN
iajs-2800	250	1	i1i	i1i	X
iajs-2800	250	2	i1i	i1i	ADP
iajs-2800	250	3			PROPN
iajs-2800	250	4			PROPN
iajs-2800	250	5			X
iajs-2800	250	6			PUNCT
iajs-2800	250	7			VERB
iajs-2800	250	8			NUM
iajs-2800	250	9			NOUN
iajs-2800	250	10			PROPN
iajs-2800	250	11			X
iajs-2800	251	1			NUM
iajs-2800	252	1			NUM
iajs-2800	252	2			NOUN
iajs-2800	252	3	,	,	PUNCT
iajs-2800	252	4	be	be	AUX
iajs-2800	252	5	the	the	DET
iajs-2800	252	6	integral	integral	ADJ
iajs-2800	252	7	of	of	ADP
iajs-2800	252	8	the	the	DET
iajs-2800	252	9	pdf	pdf	NOUN
iajs-2800	252	10	of	of	ADP
iajs-2800	252	11	gamma	gamma	NOUN
iajs-2800	252	12	distribution	distribution	NOUN
iajs-2800	252	13	[	[	X
iajs-2800	252	14	11	11	NUM
iajs-2800	252	15	]	]	PUNCT
iajs-2800	252	16	,	,	PUNCT
iajs-2800	252	17	i.e.	i.e.	X
iajs-2800	252	18	)	)	PUNCT
iajs-2800	252	19	24	24	NUM
iajs-2800	252	20	...	...	PUNCT
iajs-2800	252	21	(	(	PUNCT
iajs-2800	252	22	)	)	PUNCT
iajs-2800	252	23	1	1	NUM
iajs-2800	252	24	-	-	PUNCT
iajs-2800	252	25	n	n	CCONJ
iajs-2800	252	26	n	n	CCONJ
iajs-2800	252	27	(	(	PUNCT
iajs-2800	252	28	ln	ln	ADJ
iajs-2800	252	29	θ	θ	PROPN
iajs-2800	252	30	)	)	PUNCT
iajs-2800	252	31	t	t	PROPN
iajs-2800	252	32	)	)	PUNCT
iajs-2800	252	33	1-(n	1-(n	NUM
iajs-2800	252	34	t	t	NOUN
iajs-2800	252	35	)	)	PUNCT
iajs-2800	252	36	n	n	CCONJ
iajs-2800	252	37	(	(	PUNCT
iajs-2800	252	38	ln(θ	ln(θ	X
iajs-2800	252	39	1)c	1)c	NUM
iajs-2800	252	40	(	(	PUNCT
iajs-2800	252	41	1)cn	1)cn	NUM
iajs-2800	252	42	(	(	PUNCT
iajs-2800	252	43	1)cn	1)cn	NUM
iajs-2800	252	44	(	(	PUNCT
iajs-2800	252	45	i	i	NOUN
iajs-2800	252	46	n	n	VERB
iajs-2800	252	47	1i	1i	NUM
iajs-2800	252	48	t	t	NOUN
iajs-2800	252	49	^	^	PUNCT
iajs-2800	253	1	i1i	i1i	ADP
iajs-2800	253	2	i1i^	i1i^	NOUN
iajs-2800	253	3			PROPN
iajs-2800	253	4			PROPN
iajs-2800	253	5			PROPN
iajs-2800	253	6			X
iajs-2800	254	1			NUM
iajs-2800	254	2			NUM
iajs-2800	254	3			NOUN
iajs-2800	254	4			X
iajs-2800	254	5			X
iajs-2800	254	6			NUM
iajs-2800	254	7	3	3	NUM
iajs-2800	254	8	.	.	X
iajs-2800	254	9	simulation	simulation	NOUN
iajs-2800	254	10	study	study	NOUN
iajs-2800	254	11	we	we	PRON
iajs-2800	254	12	perform	perform	VERB
iajs-2800	254	13	a	a	DET
iajs-2800	254	14	simulation	simulation	NOUN
iajs-2800	254	15	study	study	NOUN
iajs-2800	254	16	to	to	PART
iajs-2800	254	17	compare	compare	VERB
iajs-2800	254	18	the	the	DET
iajs-2800	254	19	accuracy	accuracy	NOUN
iajs-2800	254	20	of	of	ADP
iajs-2800	254	21	the	the	DET
iajs-2800	254	22	different	different	ADJ
iajs-2800	254	23	estimates	estimate	NOUN
iajs-2800	254	24	of	of	ADP
iajs-2800	254	25	the	the	DET
iajs-2800	254	26	parameter	parameter	NOUN
iajs-2800	254	27	θ	θ	PROPN
iajs-2800	254	28	of	of	ADP
iajs-2800	254	29	the	the	DET
iajs-2800	254	30	poisson	poisson	NOUN
iajs-2800	254	31	distribution	distribution	NOUN
iajs-2800	254	32	.	.	PUNCT
iajs-2800	255	1	the	the	DET
iajs-2800	255	2	experiments	experiment	NOUN
iajs-2800	255	3	have	have	AUX
iajs-2800	255	4	been	be	AUX
iajs-2800	255	5	repeated	repeat	VERB
iajs-2800	255	6	3000)(r	3000)(r	NUM
iajs-2800	255	7			NOUN
iajs-2800	255	8	with	with	ADP
iajs-2800	255	9	different	different	ADJ
iajs-2800	255	10	sample	sample	NOUN
iajs-2800	255	11	sizes	size	NOUN
iajs-2800	255	12	(	(	PUNCT
iajs-2800	255	13	n	n	NOUN
iajs-2800	255	14	=	=	SYM
iajs-2800	255	15	25	25	NUM
iajs-2800	255	16	,	,	PUNCT
iajs-2800	255	17	50	50	NUM
iajs-2800	255	18	,	,	PUNCT
iajs-2800	255	19	and100	and100	PROPN
iajs-2800	255	20	)	)	PUNCT
iajs-2800	255	21	.	.	PUNCT
iajs-2800	256	1	assuming	assume	VERB
iajs-2800	256	2	different	different	ADJ
iajs-2800	256	3	values	value	NOUN
iajs-2800	256	4	for	for	ADP
iajs-2800	256	5	the	the	DET
iajs-2800	256	6	true	true	ADJ
iajs-2800	256	7	value	value	NOUN
iajs-2800	256	8	of	of	ADP
iajs-2800	256	9	the	the	DET
iajs-2800	256	10	parameter	parameter	NOUN
iajs-2800	256	11	θ	θ	PROPN
iajs-2800	256	12	and	and	CCONJ
iajs-2800	256	13	the	the	DET
iajs-2800	256	14	hyper	hyper	ADJ
iajs-2800	256	15	parameters	parameter	NOUN
iajs-2800	256	16	(	(	PUNCT
iajs-2800	256	17	δ	δ	PROPN
iajs-2800	256	18	,	,	PUNCT
iajs-2800	256	19	v	v	INTJ
iajs-2800	256	20	,	,	PUNCT
iajs-2800	256	21	c	c	NOUN
iajs-2800	256	22	)	)	PUNCT
iajs-2800	256	23	as	as	ADP
iajs-2800	256	24	combinations	combination	NOUN
iajs-2800	256	25	to	to	PART
iajs-2800	256	26	compare	compare	VERB
iajs-2800	256	27	the	the	DET
iajs-2800	256	28	accuracy	accuracy	NOUN
iajs-2800	256	29	of	of	ADP
iajs-2800	256	30	the	the	DET
iajs-2800	256	31	different	different	ADJ
iajs-2800	256	32	estimates	estimate	NOUN
iajs-2800	256	33	for	for	ADP
iajs-2800	256	34	θ	θ	PROPN
iajs-2800	256	35	as	as	SCONJ
iajs-2800	256	36	follows	follow	VERB
iajs-2800	256	37	:	:	PUNCT
iajs-2800	256	38			PRON
iajs-2800	256	39	a	a	DET
iajs-2800	256	40	data	data	NOUN
iajs-2800	256	41	is	be	AUX
iajs-2800	256	42	generated	generate	VERB
iajs-2800	256	43	from	from	ADP
iajs-2800	256	44	the	the	DET
iajs-2800	256	45	poisson	poisson	NOUN
iajs-2800	256	46	distribution	distribution	NOUN
iajs-2800	256	47	,	,	PUNCT
iajs-2800	256	48	for	for	ADP
iajs-2800	256	49	several	several	ADJ
iajs-2800	256	50	values	value	NOUN
iajs-2800	256	51	assumed	assume	VERB
iajs-2800	256	52	to	to	ADP
iajs-2800	256	53	the	the	DET
iajs-2800	256	54	true	true	ADJ
iajs-2800	256	55	value	value	NOUN
iajs-2800	256	56	of	of	ADP
iajs-2800	256	57	the	the	DET
iajs-2800	256	58	parameter	parameter	NOUN
iajs-2800	256	59	θ	θ	PROPN
iajs-2800	256	60	will	will	AUX
iajs-2800	256	61	be	be	AUX
iajs-2800	256	62	1,3,9θ	1,3,9θ	NUM
iajs-2800	256	63			NOUN
iajs-2800	256	64	.	.	PUNCT
iajs-2800	257	1			X
iajs-2800	258	1	the	the	DET
iajs-2800	258	2	value	value	NOUN
iajs-2800	258	3	for	for	ADP
iajs-2800	258	4	a	a	DET
iajs-2800	258	5	parameter	parameter	NOUN
iajs-2800	258	6	of	of	ADP
iajs-2800	258	7	the	the	DET
iajs-2800	258	8	erlang	erlang	PROPN
iajs-2800	258	9	prior	prior	ADV
iajs-2800	258	10	can	can	AUX
iajs-2800	258	11	be	be	AUX
iajs-2800	258	12	chosen	choose	VERB
iajs-2800	258	13	arbitrarily	arbitrarily	ADV
iajs-2800	258	14	as	as	SCONJ
iajs-2800	258	15	2,3,5δ	2,3,5δ	NUM
iajs-2800	258	16			NUM
iajs-2800	258	17	.	.	PUNCT
iajs-2800	259	1			X
iajs-2800	260	1	the	the	DET
iajs-2800	260	2	value	value	NOUN
iajs-2800	260	3	for	for	ADP
iajs-2800	260	4	a	a	DET
iajs-2800	260	5	parameter	parameter	NOUN
iajs-2800	260	6	of	of	ADP
iajs-2800	260	7	the	the	DET
iajs-2800	260	8	inverse	inverse	NOUN
iajs-2800	260	9	levy	levy	NOUN
iajs-2800	260	10	prior	prior	ADV
iajs-2800	260	11	is	be	AUX
iajs-2800	260	12	chosen	choose	VERB
iajs-2800	260	13	arbitrarily	arbitrarily	ADV
iajs-2800	260	14	as	as	ADP
iajs-2800	260	15	5,3,1v	5,3,1v	NUM
iajs-2800	260	16			NUM
iajs-2800	260	17	.	.	PUNCT
iajs-2800	261	1			X
iajs-2800	262	1	the	the	DET
iajs-2800	262	2	value	value	NOUN
iajs-2800	262	3	for	for	ADP
iajs-2800	262	4	a	a	DET
iajs-2800	262	5	parameter	parameter	NOUN
iajs-2800	262	6	of	of	ADP
iajs-2800	262	7	the	the	DET
iajs-2800	262	8	noninformative	noninformative	PROPN
iajs-2800	262	9	prior	prior	NOUN
iajs-2800	262	10	is	be	AUX
iajs-2800	262	11	chosen	choose	VERB
iajs-2800	262	12	arbitrarily	arbitrarily	ADV
iajs-2800	262	13	as	as	ADP
iajs-2800	262	14	5,3,2c	5,3,2c	NUM
iajs-2800	262	15			NUM
iajs-2800	262	16	.	.	PUNCT
iajs-2800	263	1	to	to	PART
iajs-2800	263	2	compare	compare	VERB
iajs-2800	263	3	between	between	ADP
iajs-2800	263	4	the	the	DET
iajs-2800	263	5	estimates	estimate	NOUN
iajs-2800	263	6	,	,	PUNCT
iajs-2800	263	7	we	we	PRON
iajs-2800	263	8	depend	depend	VERB
iajs-2800	263	9	on	on	ADP
iajs-2800	263	10	the	the	DET
iajs-2800	263	11	root	root	NOUN
iajs-2800	263	12	mean	mean	ADJ
iajs-2800	263	13	square	square	ADJ
iajs-2800	263	14	error	error	NOUN
iajs-2800	263	15	criterion	criterion	NOUN
iajs-2800	263	16	,	,	PUNCT
iajs-2800	263	17	i.e.	i.e.	X
iajs-2800	263	18	the	the	DET
iajs-2800	263	19	estimates	estimate	NOUN
iajs-2800	263	20	with	with	ADP
iajs-2800	263	21	the	the	DET
iajs-2800	263	22	smallest	small	ADJ
iajs-2800	263	23	rmse	rmse	NOUN
iajs-2800	263	24	's	's	PART
iajs-2800	263	25	will	will	AUX
iajs-2800	263	26	be	be	AUX
iajs-2800	263	27	the	the	DET
iajs-2800	263	28	best	good	ADJ
iajs-2800	263	29	estimates	estimate	NOUN
iajs-2800	263	30	.	.	PUNCT
iajs-2800	263	31	)	)	PUNCT
iajs-2800	264	1	25	25	NUM
iajs-2800	264	2	(	(	PUNCT
iajs-2800	264	3	θ))r	θ))r	PROPN
iajs-2800	264	4	(	(	PUNCT
iajs-2800	264	5	^	^	PUNCT
iajs-2800	264	6	θ	θ	NOUN
iajs-2800	264	7	(	(	PUNCT
iajs-2800	264	8	3000	3000	NUM
iajs-2800	264	9	1r3000	1r3000	NUM
iajs-2800	264	10	1	1	NUM
iajs-2800	264	11	rmse	rmse	NOUN
iajs-2800	264	12	2	2	NUM
iajs-2800	264	13			X
iajs-2800	265	1			NUM
iajs-2800	266	1			INTJ
iajs-2800	266	2	we	we	PRON
iajs-2800	266	3	obtain	obtain	VERB
iajs-2800	266	4	the	the	DET
iajs-2800	266	5	results	result	NOUN
iajs-2800	266	6	by	by	ADP
iajs-2800	266	7	using	use	VERB
iajs-2800	266	8	matlab	matlab	PROPN
iajs-2800	266	9	-	-	PUNCT
iajs-2800	266	10	r2018a	r2018a	NOUN
iajs-2800	266	11	program	program	NOUN
iajs-2800	266	12	.	.	PUNCT
iajs-2800	267	1	the	the	DET
iajs-2800	267	2	results	result	NOUN
iajs-2800	267	3	were	be	AUX
iajs-2800	267	4	summarized	summarize	VERB
iajs-2800	267	5	and	and	CCONJ
iajs-2800	267	6	tabulated	tabulate	VERB
iajs-2800	267	7	in	in	ADP
iajs-2800	267	8	the	the	DET
iajs-2800	267	9	following	follow	VERB
iajs-2800	267	10	tables	table	NOUN
iajs-2800	267	11	for	for	ADP
iajs-2800	267	12	each	each	DET
iajs-2800	267	13	estimator	estimator	NOUN
iajs-2800	267	14	and	and	CCONJ
iajs-2800	267	15	for	for	ADP
iajs-2800	267	16	all	all	DET
iajs-2800	267	17	sample	sample	NOUN
iajs-2800	267	18	sizes	size	NOUN
iajs-2800	267	19	.	.	PUNCT
iajs-2800	268	1	table	table	NOUN
iajs-2800	268	2	1.estimated	1.estimated	NUM
iajs-2800	268	3	values	value	NOUN
iajs-2800	268	4	)	)	PUNCT
iajs-2800	269	1	θ	θ	PROPN
iajs-2800	269	2	(	(	PUNCT
iajs-2800	269	3	^	^	PUNCT
iajs-2800	269	4	and	and	CCONJ
iajs-2800	269	5	rmse	rmse	PROPN
iajs-2800	269	6	’s	’s	X
iajs-2800	269	7	for	for	ADP
iajs-2800	269	8	the	the	DET
iajs-2800	269	9	estimators	estimator	NOUN
iajs-2800	269	10	of	of	ADP
iajs-2800	269	11	the	the	DET
iajs-2800	269	12	poisson	poisson	NOUN
iajs-2800	269	13	distribution	distribution	NOUN
iajs-2800	269	14	under	under	ADP
iajs-2800	269	15	the	the	DET
iajs-2800	269	16	self	self	NOUN
iajs-2800	269	17	,	,	PUNCT
iajs-2800	269	18	based	base	VERB
iajs-2800	269	19	on	on	ADP
iajs-2800	269	20	different	different	ADJ
iajs-2800	269	21	priors	prior	NOUN
iajs-2800	269	22	.	.	PUNCT
iajs-2800	270	1	true	true	ADJ
iajs-2800	270	2	value	value	NOUN
iajs-2800	270	3	)	)	PUNCT
iajs-2800	270	4	θ	θ	PROPN
iajs-2800	270	5	(	(	PUNCT
iajs-2800	270	6	sample	sample	NOUN
iajs-2800	270	7	size	size	NOUN
iajs-2800	270	8	(	(	PUNCT
iajs-2800	270	9	n	n	CCONJ
iajs-2800	270	10	)	)	PUNCT
iajs-2800	270	11	method	method	NOUN
iajs-2800	270	12	mle	mle	PROPN
iajs-2800	270	13	bayes	bayes	PROPN
iajs-2800	270	14	under	under	ADP
iajs-2800	270	15	criteria	criterion	NOUN
iajs-2800	270	16	)	)	PUNCT
iajs-2800	270	17	δ	δ	PROPN
iajs-2800	270	18	erlang	erlang	PROPN
iajs-2800	270	19	(	(	PUNCT
iajs-2800	270	20	prior	prior	ADJ
iajs-2800	270	21	)	)	PUNCT
iajs-2800	270	22	vlevy	vlevy	PROPN
iajs-2800	270	23	(	(	PUNCT
iajs-2800	270	24	inverse	inverse	NOUN
iajs-2800	270	25	prior	prior	ADV
iajs-2800	270	26	2δ	2δ	NUM
iajs-2800	271	1			NUM
iajs-2800	271	2	3δ	3δ	NUM
iajs-2800	271	3			NUM
iajs-2800	271	4	5δ	5δ	NOUN
iajs-2800	271	5			NUM
iajs-2800	271	6	1	1	NUM
iajs-2800	271	7	v	v	NOUN
iajs-2800	271	8			NUM
iajs-2800	271	9	3	3	NUM
iajs-2800	271	10	v	v	NOUN
iajs-2800	271	11			NUM
iajs-2800	271	12	5	5	NUM
iajs-2800	271	13	v	v	ADP
iajs-2800	271	14			NUM
iajs-2800	271	15	1θ	1θ	NUM
iajs-2800	271	16			NUM
iajs-2800	271	17	25	25	NUM
iajs-2800	271	18	est	est	X
iajs-2800	271	19	.	.	PUNCT
iajs-2800	272	1	values	value	NOUN
iajs-2800	272	2	rmse	rmse	VERB
iajs-2800	272	3	1.0004	1.0004	NUM
iajs-2800	272	4	0.1973	0.1973	NUM
iajs-2800	272	5	1.0004	1.0004	NUM
iajs-2800	272	6	0.18268	0.18268	NUM
iajs-2800	272	7	0.96467	0.96467	NUM
iajs-2800	272	8	0.17967	0.17967	NUM
iajs-2800	273	1	0.90036	0.90036	NUM
iajs-2800	273	2	0.19225	0.19225	NUM
iajs-2800	273	3	1.0004	1.0004	NUM
iajs-2800	273	4	0.19343	0.19343	NUM
iajs-2800	273	5	0.96267	0.96267	NUM
iajs-2800	273	6	0.18984	0.18984	NUM
iajs-2800	273	7	0.92766	0.92766	NUM
iajs-2800	273	8	0.1934	0.1934	NUM
iajs-2800	273	9	50	50	NUM
iajs-2800	273	10	est	est	NOUN
iajs-2800	273	11	.	.	PUNCT
iajs-2800	274	1	values	value	NOUN
iajs-2800	274	2	rmse	rmse	VERB
iajs-2800	274	3	0.99681	0.99681	NUM
iajs-2800	274	4	0.1428	0.1428	NUM
iajs-2800	274	5	0.99694	0.99694	NUM
iajs-2800	274	6	0.1373	0.1373	NUM
iajs-2800	274	7	0.97813	0.97813	NUM
iajs-2800	274	8	0.13645	0.13645	NUM
iajs-2800	274	9	0.94256	0.94256	NUM
iajs-2800	274	10	0.14193	0.14193	NUM
iajs-2800	274	11	0.99684	0.99684	NUM
iajs-2800	274	12	0.14138	0.14138	NUM
iajs-2800	274	13	0.97749	0.97749	NUM
iajs-2800	274	14	0.14042	0.14042	NUM
iajs-2800	274	15	0.95887	0.95887	NUM
iajs-2800	274	16	0.14205	0.14205	NUM
iajs-2800	274	17	100	100	NUM
iajs-2800	274	18	est	est	X
iajs-2800	274	19	.	.	PUNCT
iajs-2800	275	1	values	value	NOUN
iajs-2800	275	2	rmse	rmse	VERB
iajs-2800	275	3	0.9994	0.9994	NUM
iajs-2800	275	4	0.0983	0.0983	NUM
iajs-2800	276	1	0.9994	0.9994	NUM
iajs-2800	276	2	0.0964	0.0964	NUM
iajs-2800	276	3	0.98971	0.98971	NUM
iajs-2800	276	4	0.09601	0.09601	NUM
iajs-2800	276	5	0.97086	0.97086	NUM
iajs-2800	276	6	0.09807	0.09807	NUM
iajs-2800	276	7	0.9994	0.9994	NUM
iajs-2800	276	8	0.0978	0.0978	NUM
iajs-2800	276	9	0.98956	0.98956	NUM
iajs-2800	276	10	0.09743	0.09743	NUM
iajs-2800	276	11	0.9799	0.9799	NUM
iajs-2800	276	12	0.09801	0.09801	NUM
iajs-2800	276	13	ibn	ibn	PROPN
iajs-2800	276	14	al	al	PROPN
iajs-2800	276	15	-	-	PUNCT
iajs-2800	276	16	haitham	haitham	PROPN
iajs-2800	276	17	jour	jour	X
iajs-2800	276	18	.	.	PROPN
iajs-2800	276	19	for	for	ADP
iajs-2800	276	20	pure	pure	ADJ
iajs-2800	276	21	&	&	CCONJ
iajs-2800	276	22	appl	appl	PROPN
iajs-2800	276	23	.	.	PUNCT
iajs-2800	277	1	sci	sci	PROPN
iajs-2800	277	2	.	.	PROPN
iajs-2800	278	1	53	53	NUM
iajs-2800	278	2	(	(	PUNCT
iajs-2800	278	3	1)2022	1)2022	PROPN
iajs-2800	278	4	69	69	NUM
iajs-2800	278	5	3θ	3θ	NUM
iajs-2800	278	6			NUM
iajs-2800	278	7	25	25	NUM
iajs-2800	278	8	est	est	X
iajs-2800	278	9	.	.	PUNCT
iajs-2800	279	1	values	value	NOUN
iajs-2800	279	2	rmse	rmse	VERB
iajs-2800	280	1	2.9999	2.9999	NUM
iajs-2800	280	2	0.33873	0.33873	NUM
iajs-2800	280	3	2.8518	2.8518	NUM
iajs-2800	280	4	0.3469	0.3469	NUM
iajs-2800	280	5	2.7499	2.7499	NUM
iajs-2800	280	6	0.39243	0.39243	NUM
iajs-2800	280	7	2.5666	2.5666	NUM
iajs-2800	280	8	0.51721	0.51721	NUM
iajs-2800	281	1	2.9607	2.9607	NUM
iajs-2800	281	2	0.33441	0.33441	NUM
iajs-2800	281	3	2.849	2.849	NUM
iajs-2800	281	4	0.35344	0.35344	NUM
iajs-2800	281	5	2.7454	2.7454	NUM
iajs-2800	281	6	0.39956	0.39956	NUM
iajs-2800	281	7	50	50	NUM
iajs-2800	281	8	est	est	NOUN
iajs-2800	281	9	.	.	PUNCT
iajs-2800	282	1	values	value	NOUN
iajs-2800	282	2	rmse	rmse	VERB
iajs-2800	282	3	3.003	3.003	NUM
iajs-2800	282	4	0.24378	0.24378	NUM
iajs-2800	282	5	2.926	2.926	NUM
iajs-2800	282	6	0.24579	0.24579	NUM
iajs-2800	282	7	2.8708	2.8708	NUM
iajs-2800	282	8	0.26378	0.26378	NUM
iajs-2800	282	9	2.7664	2.7664	NUM
iajs-2800	282	10	0.322	0.322	NUM
iajs-2800	282	11	2.9832	2.9832	NUM
iajs-2800	282	12	0.24193	0.24193	NUM
iajs-2800	282	13	2.9253	2.9253	NUM
iajs-2800	282	14	0.24818	0.24818	NUM
iajs-2800	282	15	2.8695	2.8695	NUM
iajs-2800	282	16	0.26629	0.26629	NUM
iajs-2800	282	17	100	100	NUM
iajs-2800	282	18	est	est	X
iajs-2800	282	19	.	.	PUNCT
iajs-2800	283	1	values	value	NOUN
iajs-2800	283	2	rmse	rmse	VERB
iajs-2800	283	3	3.0008	3.0008	NUM
iajs-2800	283	4	0.17482	0.17482	NUM
iajs-2800	283	5	2.9615	2.9615	NUM
iajs-2800	283	6	0.17566	0.17566	NUM
iajs-2800	283	7	2.9328	2.9328	NUM
iajs-2800	283	8	0.18256	0.18256	NUM
iajs-2800	283	9	2.8769	2.8769	NUM
iajs-2800	283	10	0.20705	0.20705	NUM
iajs-2800	283	11	2.9908	2.9908	NUM
iajs-2800	283	12	0.1742	0.1742	NUM
iajs-2800	283	13	2.9613	2.9613	NUM
iajs-2800	283	14	0.17652	0.17652	NUM
iajs-2800	283	15	2.9325	2.9325	NUM
iajs-2800	283	16	0.18345	0.18345	NUM
iajs-2800	283	17	9θ	9θ	NUM
iajs-2800	283	18			NUM
iajs-2800	283	19	25	25	NUM
iajs-2800	283	20	est	est	X
iajs-2800	283	21	.	.	PUNCT
iajs-2800	284	1	values	value	NOUN
iajs-2800	284	2	rmse	rmse	VERB
iajs-2800	285	1	9.0033	9.0033	NUM
iajs-2800	285	2	0.58613	0.58613	NUM
iajs-2800	285	3	8.4104	8.4104	NUM
iajs-2800	285	4	0.80132	0.80132	NUM
iajs-2800	285	5	8.1101	8.1101	NUM
iajs-2800	285	6	1.0324	1.0324	NUM
iajs-2800	285	7	7.5694	7.5694	NUM
iajs-2800	285	8	1.5117	1.5117	NUM
iajs-2800	285	9	8.8464	8.8464	NUM
iajs-2800	285	10	0.59482	0.59482	NUM
iajs-2800	285	11	8.5125	8.5125	NUM
iajs-2800	285	12	0.73714	0.73714	NUM
iajs-2800	285	13	8.203	8.203	NUM
iajs-2800	285	14	0.95873	0.95873	NUM
iajs-2800	285	15	50	50	NUM
iajs-2800	285	16	est	est	NOUN
iajs-2800	285	17	.	.	PUNCT
iajs-2800	286	1	values	value	NOUN
iajs-2800	286	2	rmse	rmse	VERB
iajs-2800	286	3	9.0036	9.0036	NUM
iajs-2800	286	4	0.4215	0.4215	NUM
iajs-2800	286	5	8.6957	8.6957	NUM
iajs-2800	286	6	0.50678	0.50678	NUM
iajs-2800	286	7	8.5317	8.5317	NUM
iajs-2800	286	8	0.61437	0.61437	NUM
iajs-2800	286	9	8.2214	8.2214	NUM
iajs-2800	286	10	0.86776	0.86776	NUM
iajs-2800	286	11	8.9243	8.9243	NUM
iajs-2800	286	12	0.42412	0.42412	NUM
iajs-2800	286	13	8.751	8.751	NUM
iajs-2800	286	14	0.479	0.479	NUM
iajs-2800	286	15	8.5843	8.5843	NUM
iajs-2800	286	16	0.57785	0.57785	NUM
iajs-2800	286	17	100	100	NUM
iajs-2800	286	18	est	est	X
iajs-2800	286	19	.	.	PUNCT
iajs-2800	287	1	values	value	NOUN
iajs-2800	287	2	rmse	rmse	VERB
iajs-2800	287	3	8.9985	8.9985	NUM
iajs-2800	287	4	0.30358	0.30358	NUM
iajs-2800	287	5	8.8417	8.8417	NUM
iajs-2800	287	6	0.3371	0.3371	NUM
iajs-2800	287	7	8.7559	8.7559	NUM
iajs-2800	287	8	0.38272	0.38272	NUM
iajs-2800	287	9	8.5891	8.5891	NUM
iajs-2800	287	10	0.50244	0.50244	NUM
iajs-2800	287	11	8.9587	8.9587	NUM
iajs-2800	287	12	0.30487	0.30487	NUM
iajs-2800	287	13	8.8705	8.8705	NUM
iajs-2800	287	14	0.32593	0.32593	NUM
iajs-2800	287	15	8.7839	8.7839	NUM
iajs-2800	287	16	0.36661	0.36661	NUM
iajs-2800	287	17	note	note	NOUN
iajs-2800	287	18	:	:	PUNCT
iajs-2800	287	19	the	the	DET
iajs-2800	287	20	shadow	shadow	NOUN
iajs-2800	287	21	cells	cell	NOUN
iajs-2800	287	22	represent	represent	VERB
iajs-2800	287	23	the	the	DET
iajs-2800	287	24	smallest	small	ADJ
iajs-2800	287	25	value	value	NOUN
iajs-2800	287	26	of	of	ADP
iajs-2800	287	27	rmse	rmse	NOUN
iajs-2800	287	28	.	.	PUNCT
iajs-2800	288	1	continue	continue	VERB
iajs-2800	288	2	table	table	NOUN
iajs-2800	288	3	1	1	NUM
iajs-2800	288	4	true	true	ADJ
iajs-2800	288	5	value	value	NOUN
iajs-2800	288	6	)	)	PUNCT
iajs-2800	289	1	θ	θ	PROPN
iajs-2800	289	2	(	(	PUNCT
iajs-2800	289	3	sample	sample	NOUN
iajs-2800	289	4	size	size	NOUN
iajs-2800	289	5	(	(	PUNCT
iajs-2800	289	6	n	n	CCONJ
iajs-2800	289	7	)	)	PUNCT
iajs-2800	289	8	method	method	NOUN
iajs-2800	289	9	mle	mle	PROPN
iajs-2800	289	10	bayes	bayes	PROPN
iajs-2800	289	11	under	under	ADP
iajs-2800	289	12	criteria	criterion	NOUN
iajs-2800	289	13	)	)	PUNCT
iajs-2800	289	14	c	c	PROPN
iajs-2800	289	15	e(informativnon	e(informativnon	NOUN
iajs-2800	289	16	prior	prior	ADJ
iajs-2800	289	17	2c	2c	NUM
iajs-2800	289	18			NOUN
iajs-2800	289	19	3c	3c	NUM
iajs-2800	289	20			NUM
iajs-2800	289	21	5c	5c	NUM
iajs-2800	290	1			NUM
iajs-2800	290	2	1θ	1θ	NUM
iajs-2800	290	3			NUM
iajs-2800	290	4	25	25	NUM
iajs-2800	290	5	est	est	X
iajs-2800	290	6	.	.	PUNCT
iajs-2800	291	1	values	value	NOUN
iajs-2800	291	2	rmse	rmse	VERB
iajs-2800	291	3	1.0004	1.0004	NUM
iajs-2800	291	4	0.1973	0.1973	NUM
iajs-2800	291	5	0.96043	0.96043	NUM
iajs-2800	291	6	0.20123	0.20123	NUM
iajs-2800	291	7	0.92043	0.92043	NUM
iajs-2800	291	8	0.21274	0.21274	NUM
iajs-2800	291	9	0.84043	0.84043	NUM
iajs-2800	291	10	0.25375	0.25375	NUM
iajs-2800	291	11	50	50	NUM
iajs-2800	291	12	est	est	NOUN
iajs-2800	291	13	.	.	PUNCT
iajs-2800	292	1	values	value	NOUN
iajs-2800	292	2	rmse	rmse	VERB
iajs-2800	292	3	0.99681	0.99681	NUM
iajs-2800	292	4	0.1428	0.1428	NUM
iajs-2800	293	1	0.97681	0.97681	NUM
iajs-2800	293	2	0.14463	0.14463	NUM
iajs-2800	293	3	0.95681	0.95681	NUM
iajs-2800	293	4	0.14915	0.14915	NUM
iajs-2800	293	5	0.91681	0.91681	NUM
iajs-2800	293	6	0.16523	0.16523	NUM
iajs-2800	293	7	100	100	NUM
iajs-2800	293	8	est	est	X
iajs-2800	293	9	.	.	PUNCT
iajs-2800	294	1	values	value	NOUN
iajs-2800	294	2	rmse	rmse	VERB
iajs-2800	294	3	0.9994	0.9994	NUM
iajs-2800	294	4	0.0983	0.0983	NUM
iajs-2800	294	5	0.9894	0.9894	NUM
iajs-2800	295	1	0.09889	0.09889	NUM
iajs-2800	295	2	0.9794	0.9794	NUM
iajs-2800	295	3	0.10046	0.10046	NUM
iajs-2800	295	4	0.9594	0.9594	NUM
iajs-2800	295	5	0.10638	0.10638	NUM
iajs-2800	295	6	3θ	3θ	NUM
iajs-2800	295	7			NUM
iajs-2800	295	8	25	25	NUM
iajs-2800	295	9	est	est	X
iajs-2800	295	10	.	.	PUNCT
iajs-2800	296	1	values	value	NOUN
iajs-2800	296	2	rmse	rmse	VERB
iajs-2800	296	3	2.9999	2.9999	NUM
iajs-2800	296	4	0.33873	0.33873	NUM
iajs-2800	296	5	2.9599	2.9599	NUM
iajs-2800	296	6	0.3411	0.3411	NUM
iajs-2800	296	7	2.9199	2.9199	NUM
iajs-2800	296	8	0.34807	0.34807	NUM
iajs-2800	296	9	2.8399	2.8399	NUM
iajs-2800	296	10	0.37465	0.37465	NUM
iajs-2800	296	11	50	50	NUM
iajs-2800	296	12	est	est	NOUN
iajs-2800	296	13	.	.	PUNCT
iajs-2800	297	1	values	value	NOUN
iajs-2800	297	2	rmse	rmse	VERB
iajs-2800	297	3	3.003	3.003	NUM
iajs-2800	297	4	0.24378	0.24378	NUM
iajs-2800	297	5	2.983	2.983	NUM
iajs-2800	297	6	0.24435	0.24435	NUM
iajs-2800	297	7	2.963	2.963	NUM
iajs-2800	297	8	0.24655	0.24655	NUM
iajs-2800	297	9	2.923	2.923	NUM
iajs-2800	297	10	0.25562	0.25562	NUM
iajs-2800	297	11	100	100	NUM
iajs-2800	297	12	est	est	X
iajs-2800	297	13	.	.	PUNCT
iajs-2800	298	1	values	value	NOUN
iajs-2800	298	2	rmse	rmse	VERB
iajs-2800	298	3	3.0008	3.0008	NUM
iajs-2800	298	4	0.17482	0.17482	NUM
iajs-2800	298	5	2.9908	2.9908	NUM
iajs-2800	298	6	0.17507	0.17507	NUM
iajs-2800	298	7	2.9808	2.9808	NUM
iajs-2800	298	8	0.17588	0.17588	NUM
iajs-2800	298	9	2.9608	2.9608	NUM
iajs-2800	298	10	0.17917	0.17917	NUM
iajs-2800	298	11	9θ	9θ	NUM
iajs-2800	298	12			NUM
iajs-2800	298	13	25	25	NUM
iajs-2800	298	14	est	est	X
iajs-2800	298	15	.	.	PUNCT
iajs-2800	299	1	values	value	NOUN
iajs-2800	299	2	rmse	rmse	VERB
iajs-2800	299	3	9.0033	9.0033	NUM
iajs-2800	299	4	0.58613	0.58613	NUM
iajs-2800	299	5	8.9633	8.9633	NUM
iajs-2800	299	6	0.58727	0.58727	NUM
iajs-2800	299	7	8.9233	8.9233	NUM
iajs-2800	299	8	0.59112	0.59112	NUM
iajs-2800	299	9	8.8433	8.8433	NUM
iajs-2800	299	10	0.60672	0.60672	NUM
iajs-2800	299	11	50	50	NUM
iajs-2800	299	12	est	est	NOUN
iajs-2800	299	13	.	.	PUNCT
iajs-2800	300	1	values	value	NOUN
iajs-2800	300	2	rmse	rmse	VERB
iajs-2800	301	1	9.0036	9.0036	NUM
iajs-2800	301	2	0.4215	0.4215	NUM
iajs-2800	301	3	8.9836	8.9836	NUM
iajs-2800	301	4	0.42181	0.42181	NUM
iajs-2800	301	5	8.9636	8.9636	NUM
iajs-2800	301	6	0.42306	0.42306	NUM
iajs-2800	301	7	8.9236	8.9236	NUM
iajs-2800	301	8	0.42836	0.42836	NUM
iajs-2800	301	9	100	100	NUM
iajs-2800	301	10	est	est	X
iajs-2800	301	11	.	.	PUNCT
iajs-2800	302	1	values	value	NOUN
iajs-2800	302	2	rmse	rmse	VERB
iajs-2800	302	3	8.9985	8.9985	NUM
iajs-2800	302	4	0.30358	0.30358	NUM
iajs-2800	302	5	8.9885	8.9885	NUM
iajs-2800	302	6	0.30379	0.30379	NUM
iajs-2800	302	7	8.9785	8.9785	NUM
iajs-2800	302	8	0.30433	0.30433	NUM
iajs-2800	302	9	8.9585	8.9585	NUM
iajs-2800	302	10	0.30639	0.30639	NUM
iajs-2800	302	11	note	note	NOUN
iajs-2800	302	12	:	:	PUNCT
iajs-2800	302	13	the	the	DET
iajs-2800	302	14	shadow	shadow	NOUN
iajs-2800	302	15	cells	cell	NOUN
iajs-2800	302	16	represent	represent	VERB
iajs-2800	302	17	the	the	DET
iajs-2800	302	18	smallest	small	ADJ
iajs-2800	302	19	value	value	NOUN
iajs-2800	302	20	of	of	ADP
iajs-2800	302	21	rmse	rmse	NOUN
iajs-2800	302	22	.	.	PUNCT
iajs-2800	303	1	table	table	NOUN
iajs-2800	303	2	2	2	NUM
iajs-2800	303	3	.	.	PUNCT
iajs-2800	304	1	estimated	estimate	VERB
iajs-2800	304	2	values	value	NOUN
iajs-2800	304	3	)	)	PUNCT
iajs-2800	305	1	θ	θ	PROPN
iajs-2800	305	2	(	(	PUNCT
iajs-2800	305	3	^	^	PUNCT
iajs-2800	305	4	and	and	CCONJ
iajs-2800	305	5	rmse	rmse	PROPN
iajs-2800	305	6	’s	’s	X
iajs-2800	305	7	for	for	ADP
iajs-2800	305	8	the	the	DET
iajs-2800	305	9	estimators	estimator	NOUN
iajs-2800	305	10	of	of	ADP
iajs-2800	305	11	the	the	DET
iajs-2800	305	12	poisson	poisson	NOUN
iajs-2800	305	13	distribution	distribution	NOUN
iajs-2800	305	14	under	under	ADP
iajs-2800	305	15	the	the	DET
iajs-2800	305	16	proposed	propose	VERB
iajs-2800	305	17	exponential	exponential	ADJ
iajs-2800	305	18	loss	loss	NOUN
iajs-2800	305	19	function	function	NOUN
iajs-2800	305	20	,	,	PUNCT
iajs-2800	305	21	based	base	VERB
iajs-2800	305	22	on	on	ADP
iajs-2800	305	23	different	different	ADJ
iajs-2800	305	24	prior	prior	ADV
iajs-2800	305	25	.	.	PUNCT
iajs-2800	306	1	true	true	ADJ
iajs-2800	306	2	value	value	NOUN
iajs-2800	306	3	)	)	PUNCT
iajs-2800	306	4	θ	θ	PROPN
iajs-2800	306	5	(	(	PUNCT
iajs-2800	306	6	sample	sample	NOUN
iajs-2800	306	7	size	size	NOUN
iajs-2800	306	8	(	(	PUNCT
iajs-2800	306	9	n	n	CCONJ
iajs-2800	306	10	)	)	PUNCT
iajs-2800	306	11	method	method	NOUN
iajs-2800	306	12	mle	mle	PROPN
iajs-2800	306	13	bayes	bayes	PROPN
iajs-2800	306	14	under	under	ADP
iajs-2800	306	15	criteria	criterion	NOUN
iajs-2800	306	16	)	)	PUNCT
iajs-2800	306	17	δ	δ	PROPN
iajs-2800	306	18	erlang	erlang	PROPN
iajs-2800	306	19	(	(	PUNCT
iajs-2800	306	20	prior	prior	ADJ
iajs-2800	306	21	)	)	PUNCT
iajs-2800	306	22	vlevy	vlevy	PROPN
iajs-2800	306	23	(	(	PUNCT
iajs-2800	306	24	inverse	inverse	NOUN
iajs-2800	306	25	prior	prior	ADV
iajs-2800	306	26	2δ	2δ	NUM
iajs-2800	307	1			NUM
iajs-2800	307	2	3δ	3δ	NUM
iajs-2800	307	3			NUM
iajs-2800	307	4	5δ	5δ	NOUN
iajs-2800	307	5			NUM
iajs-2800	307	6	1	1	NUM
iajs-2800	307	7	v	v	NOUN
iajs-2800	307	8			NUM
iajs-2800	307	9	3	3	NUM
iajs-2800	307	10	v	v	NOUN
iajs-2800	307	11			NUM
iajs-2800	307	12	5	5	NUM
iajs-2800	307	13	v	v	ADP
iajs-2800	307	14			NUM
iajs-2800	307	15	1θ	1θ	NUM
iajs-2800	307	16			NUM
iajs-2800	307	17	25	25	NUM
iajs-2800	307	18	est	est	X
iajs-2800	307	19	.	.	PUNCT
iajs-2800	308	1	values	value	NOUN
iajs-2800	308	2	rmse	rmse	VERB
iajs-2800	308	3	1.0004	1.0004	NUM
iajs-2800	308	4	0.1973	0.1973	NUM
iajs-2800	308	5	1.0194	1.0194	NUM
iajs-2800	308	6	0.18716	0.18716	NUM
iajs-2800	308	7	0.98231	0.98231	NUM
iajs-2800	308	8	0.18025	0.18025	NUM
iajs-2800	308	9	0.9157	0.9157	NUM
iajs-2800	308	10	0.18726	0.18726	NUM
iajs-2800	308	11	1.0206	1.0206	NUM
iajs-2800	308	12	0.19839	0.19839	NUM
iajs-2800	308	13	0.9813	0.9813	NUM
iajs-2800	308	14	0.19065	0.19065	NUM
iajs-2800	308	15	0.94495	0.94495	NUM
iajs-2800	308	16	0.19082	0.19082	NUM
iajs-2800	308	17	50	50	NUM
iajs-2800	308	18	est	est	NOUN
iajs-2800	308	19	.	.	PUNCT
iajs-2800	309	1	values	value	NOUN
iajs-2800	309	2	rmse	rmse	VERB
iajs-2800	310	1	0.99681	0.99681	NUM
iajs-2800	310	2	0.1428	0.1428	NUM
iajs-2800	310	3	1.0066	1.0066	NUM
iajs-2800	310	4	0.13877	0.13877	NUM
iajs-2800	310	5	0.98747	0.98747	NUM
iajs-2800	310	6	0.13654	0.13654	NUM
iajs-2800	310	7	0.95123	0.95123	NUM
iajs-2800	310	8	0.13976	0.13976	NUM
iajs-2800	310	9	1.0068	1.0068	NUM
iajs-2800	310	10	0.14293	0.14293	NUM
iajs-2800	310	11	0.9871	0.9871	NUM
iajs-2800	310	12	0.14056	0.14056	NUM
iajs-2800	310	13	0.96812	0.96812	NUM
iajs-2800	310	14	0.14093	0.14093	NUM
iajs-2800	310	15	100	100	NUM
iajs-2800	310	16	est	est	X
iajs-2800	310	17	.	.	PUNCT
iajs-2800	311	1	values	value	NOUN
iajs-2800	311	2	rmse	rmse	VERB
iajs-2800	311	3	0.9994	0.9994	NUM
iajs-2800	312	1	0.0983	0.0983	NUM
iajs-2800	312	2	1.0043	1.0043	NUM
iajs-2800	312	3	0.09697	0.09697	NUM
iajs-2800	312	4	0.99454	0.99454	NUM
iajs-2800	312	5	0.09608	0.09608	NUM
iajs-2800	312	6	0.97551	0.97551	NUM
iajs-2800	312	7	0.09722	0.09722	NUM
iajs-2800	312	8	1.0044	1.0044	NUM
iajs-2800	312	9	0.09842	0.09842	NUM
iajs-2800	312	10	0.99446	0.99446	NUM
iajs-2800	312	11	0.09751	0.09751	NUM
iajs-2800	312	12	0.98471	0.98471	NUM
iajs-2800	312	13	0.09760	0.09760	NUM
iajs-2800	312	14	3θ	3θ	NUM
iajs-2800	312	15			NUM
iajs-2800	312	16	25	25	NUM
iajs-2800	312	17	est	est	X
iajs-2800	312	18	.	.	PUNCT
iajs-2800	313	1	values	value	NOUN
iajs-2800	313	2	rmse	rmse	VERB
iajs-2800	313	3	2.9999	2.9999	NUM
iajs-2800	313	4	0.33873	0.33873	NUM
iajs-2800	313	5	2.9059	2.9059	NUM
iajs-2800	313	6	0.33315	0.33315	NUM
iajs-2800	313	7	2.8002	2.8002	NUM
iajs-2800	313	8	0.36708	0.36708	NUM
iajs-2800	313	9	2.6104	2.6104	NUM
iajs-2800	313	10	0.48398	0.48398	NUM
iajs-2800	314	1	3.0203	3.0203	NUM
iajs-2800	314	2	0.33939	0.33939	NUM
iajs-2800	314	3	2.9041	2.9041	NUM
iajs-2800	314	4	0.33956	0.33956	NUM
iajs-2800	314	5	2.7966	2.7966	NUM
iajs-2800	314	6	0.37388	0.37388	NUM
iajs-2800	314	7	50	50	NUM
iajs-2800	314	8	est	est	NOUN
iajs-2800	314	9	.	.	PUNCT
iajs-2800	315	1	values	value	NOUN
iajs-2800	315	2	rmse	rmse	VERB
iajs-2800	315	3	3.003	3.003	NUM
iajs-2800	315	4	0.24378	0.24378	NUM
iajs-2800	315	5	2.9545	2.9545	NUM
iajs-2800	315	6	0.241	0.241	NUM
iajs-2800	315	7	2.8982	2.8982	NUM
iajs-2800	315	8	0.25349	0.25349	NUM
iajs-2800	315	9	2.7918	2.7918	NUM
iajs-2800	315	10	0.30552	0.30552	NUM
iajs-2800	315	11	3.0131	3.0131	NUM
iajs-2800	315	12	0.24412	0.24412	NUM
iajs-2800	315	13	2.954	2.954	NUM
iajs-2800	315	14	0.24336	0.24336	NUM
iajs-2800	315	15	2.8972	2.8972	NUM
iajs-2800	315	16	0.25593	0.25593	NUM
iajs-2800	315	17	ibn	ibn	PROPN
iajs-2800	315	18	al	al	PROPN
iajs-2800	315	19	-	-	PUNCT
iajs-2800	315	20	haitham	haitham	PROPN
iajs-2800	315	21	jour	jour	X
iajs-2800	315	22	.	.	PROPN
iajs-2800	316	1	for	for	ADP
iajs-2800	316	2	pure	pure	ADJ
iajs-2800	316	3	&	&	CCONJ
iajs-2800	316	4	appl	appl	PROPN
iajs-2800	316	5	.	.	PUNCT
iajs-2800	317	1	sci	sci	PROPN
iajs-2800	317	2	.	.	PROPN
iajs-2800	318	1	53	53	NUM
iajs-2800	318	2	(	(	PUNCT
iajs-2800	318	3	1)2022	1)2022	PROPN
iajs-2800	318	4	70	70	NUM
iajs-2800	318	5	100	100	NUM
iajs-2800	318	6	est	est	X
iajs-2800	318	7	.	.	PUNCT
iajs-2800	319	1	values	value	NOUN
iajs-2800	319	2	rmse	rmse	VERB
iajs-2800	319	3	3.0008	3.0008	NUM
iajs-2800	319	4	0.17482	0.17482	NUM
iajs-2800	319	5	2.9761	2.9761	NUM
iajs-2800	319	6	0.17388	0.17388	NUM
iajs-2800	319	7	2.9471	2.9471	NUM
iajs-2800	319	8	0.17857	0.17857	NUM
iajs-2800	319	9	2.8907	2.8907	NUM
iajs-2800	319	10	0.19983	0.19983	NUM
iajs-2800	319	11	3.0058	3.0058	NUM
iajs-2800	319	12	0.17492	0.17492	NUM
iajs-2800	319	13	2.976	2.976	NUM
iajs-2800	319	14	0.17474	0.17474	NUM
iajs-2800	319	15	2.9469	2.9469	NUM
iajs-2800	319	16	0.17945	0.17945	NUM
iajs-2800	319	17	9θ	9θ	NOUN
iajs-2800	319	18			NUM
iajs-2800	319	19	25	25	NUM
iajs-2800	319	20	est	est	X
iajs-2800	319	21	.	.	PUNCT
iajs-2800	320	1	values	value	NOUN
iajs-2800	320	2	rmse	rmse	VERB
iajs-2800	320	3	9.0033	9.0033	NUM
iajs-2800	320	4	0.58613	0.58613	NUM
iajs-2800	320	5	8.5701	8.5701	NUM
iajs-2800	320	6	0.70043	0.70043	NUM
iajs-2800	320	7	8.2584	8.2584	NUM
iajs-2800	320	8	0.91318	0.91318	NUM
iajs-2800	320	9	7.6984	7.6984	NUM
iajs-2800	320	10	1.3931	1.3931	NUM
iajs-2800	320	11	9.0245	9.0245	NUM
iajs-2800	320	12	0.58671	0.58671	NUM
iajs-2800	320	13	8.6773	8.6773	NUM
iajs-2800	320	14	0.64949	0.64949	NUM
iajs-2800	320	15	8.3558	8.3558	NUM
iajs-2800	320	16	0.84234	0.84234	NUM
iajs-2800	320	17	50	50	NUM
iajs-2800	320	18	est	est	NOUN
iajs-2800	320	19	.	.	PUNCT
iajs-2800	321	1	values	value	NOUN
iajs-2800	321	2	rmse	rmse	VERB
iajs-2800	321	3	9.0036	9.0036	NUM
iajs-2800	321	4	0.4215	0.4215	NUM
iajs-2800	322	1	8.7804	8.7804	NUM
iajs-2800	322	2	0.46441	0.46441	NUM
iajs-2800	322	3	8.6132	8.6132	NUM
iajs-2800	322	4	0.55747	0.55747	NUM
iajs-2800	322	5	8.2971	8.2971	NUM
iajs-2800	322	6	0.80227	0.80227	NUM
iajs-2800	323	1	9.0139	9.0139	NUM
iajs-2800	323	2	0.42173	0.42173	NUM
iajs-2800	323	3	8.8371	8.8371	NUM
iajs-2800	323	4	0.44418	0.44418	NUM
iajs-2800	323	5	8.6672	8.6672	NUM
iajs-2800	323	6	0.52445	0.52445	NUM
iajs-2800	323	7	100	100	NUM
iajs-2800	323	8	est	est	X
iajs-2800	323	9	.	.	PUNCT
iajs-2800	324	1	values	value	NOUN
iajs-2800	324	2	rmse	rmse	VERB
iajs-2800	324	3	8.9985	8.9985	NUM
iajs-2800	324	4	0.30358	0.30358	NUM
iajs-2800	324	5	8.8853	8.8853	NUM
iajs-2800	324	6	0.32032	0.32032	NUM
iajs-2800	324	7	8.7986	8.7986	NUM
iajs-2800	324	8	0.35814	0.35814	NUM
iajs-2800	324	9	8.6302	8.6302	NUM
iajs-2800	324	10	0.47023	0.47023	NUM
iajs-2800	324	11	9.0036	9.0036	NUM
iajs-2800	324	12	0.3036	0.3036	NUM
iajs-2800	324	13	8.9145	8.9145	NUM
iajs-2800	324	14	0.3125	0.3125	NUM
iajs-2800	324	15	8.8271	8.8271	NUM
iajs-2800	324	16	0.34422	0.34422	NUM
iajs-2800	324	17	note	note	NOUN
iajs-2800	324	18	:	:	PUNCT
iajs-2800	324	19	the	the	DET
iajs-2800	324	20	shadow	shadow	NOUN
iajs-2800	324	21	cells	cell	NOUN
iajs-2800	324	22	represent	represent	VERB
iajs-2800	324	23	the	the	DET
iajs-2800	324	24	smallest	small	ADJ
iajs-2800	324	25	value	value	NOUN
iajs-2800	324	26	of	of	ADP
iajs-2800	324	27	rmse	rmse	NOUN
iajs-2800	324	28	.	.	PUNCT
iajs-2800	325	1	continue	continue	VERB
iajs-2800	325	2	table	table	NOUN
iajs-2800	325	3	2	2	NUM
iajs-2800	325	4	true	true	ADJ
iajs-2800	325	5	value	value	NOUN
iajs-2800	325	6	)	)	PUNCT
iajs-2800	326	1	θ	θ	PROPN
iajs-2800	326	2	(	(	PUNCT
iajs-2800	326	3	sample	sample	NOUN
iajs-2800	326	4	size	size	NOUN
iajs-2800	326	5	(	(	PUNCT
iajs-2800	326	6	n	n	CCONJ
iajs-2800	326	7	)	)	PUNCT
iajs-2800	326	8	method	method	NOUN
iajs-2800	326	9	mle	mle	PROPN
iajs-2800	326	10	bayes	bayes	PROPN
iajs-2800	326	11	under	under	ADP
iajs-2800	326	12	criteria	criterion	NOUN
iajs-2800	326	13	)	)	PUNCT
iajs-2800	327	1	c	c	PROPN
iajs-2800	327	2	e(informativnon	e(informativnon	PROPN
iajs-2800	327	3	prio	prio	PROPN
iajs-2800	327	4	2c	2c	PROPN
iajs-2800	327	5			PROPN
iajs-2800	327	6	3c	3c	NUM
iajs-2800	328	1			NUM
iajs-2800	328	2	5c	5c	NUM
iajs-2800	329	1			NUM
iajs-2800	329	2	1θ	1θ	NUM
iajs-2800	329	3			NUM
iajs-2800	329	4	25	25	NUM
iajs-2800	329	5	est	est	X
iajs-2800	329	6	.	.	PUNCT
iajs-2800	330	1	values	value	NOUN
iajs-2800	330	2	rmse	rmse	VERB
iajs-2800	330	3	1.0004	1.0004	NUM
iajs-2800	330	4	0.1973	0.1973	NUM
iajs-2800	330	5	0.98016	0.98016	NUM
iajs-2800	330	6	0.20233	0.20233	NUM
iajs-2800	330	7	0.93934	0.93934	NUM
iajs-2800	330	8	0.21029	0.21029	NUM
iajs-2800	330	9	0.8577	0.8577	NUM
iajs-2800	330	10	0.24656	0.24656	NUM
iajs-2800	330	11	50	50	NUM
iajs-2800	330	12	est	est	NOUN
iajs-2800	330	13	.	.	PUNCT
iajs-2800	331	1	values	value	NOUN
iajs-2800	331	2	rmse	rmse	VERB
iajs-2800	332	1	0.99681	0.99681	NUM
iajs-2800	332	2	0.1428	0.1428	NUM
iajs-2800	332	3	0.98671	0.98671	NUM
iajs-2800	332	4	0.14482	0.14482	NUM
iajs-2800	332	5	0.96651	0.96651	NUM
iajs-2800	332	6	0.14805	0.14805	NUM
iajs-2800	332	7	0.92611	0.92611	NUM
iajs-2800	332	8	0.16204	0.16204	NUM
iajs-2800	332	9	100	100	NUM
iajs-2800	332	10	est	est	X
iajs-2800	332	11	.	.	PUNCT
iajs-2800	333	1	values	value	NOUN
iajs-2800	333	2	rmse	rmse	VERB
iajs-2800	333	3	0.9994	0.9994	NUM
iajs-2800	333	4	0.0983	0.0983	NUM
iajs-2800	334	1	0.99438	0.99438	NUM
iajs-2800	334	2	0.09898	0.09898	NUM
iajs-2800	334	3	0.98433	0.98433	NUM
iajs-2800	334	4	0.10006	0.10006	NUM
iajs-2800	334	5	0.96423	0.96423	NUM
iajs-2800	334	6	0.1051	0.1051	NUM
iajs-2800	334	7	3θ	3θ	NUM
iajs-2800	334	8			PROPN
iajs-2800	334	9	25	25	NUM
iajs-2800	334	10	est	est	X
iajs-2800	334	11	.	.	PUNCT
iajs-2800	335	1	values	value	NOUN
iajs-2800	335	2	rmse	rmse	VERB
iajs-2800	335	3	2.9999	2.9999	NUM
iajs-2800	335	4	0.33873	0.33873	NUM
iajs-2800	335	5	3.0208	3.0208	NUM
iajs-2800	335	6	0.34632	0.34632	NUM
iajs-2800	335	7	2.9799	2.9799	NUM
iajs-2800	335	8	0.34628	0.34628	NUM
iajs-2800	335	9	2.8983	2.8983	NUM
iajs-2800	335	10	0.36035	0.36035	NUM
iajs-2800	335	11	50	50	NUM
iajs-2800	335	12	est	est	NOUN
iajs-2800	335	13	.	.	PUNCT
iajs-2800	336	1	values	value	NOUN
iajs-2800	336	2	rmse	rmse	VERB
iajs-2800	336	3	3.003	3.003	NUM
iajs-2800	336	4	0.24378	0.24378	NUM
iajs-2800	336	5	3.0133	3.0133	NUM
iajs-2800	336	6	0.24658	0.24658	NUM
iajs-2800	336	7	2.9931	2.9931	NUM
iajs-2800	336	8	0.24632	0.24632	NUM
iajs-2800	336	9	2.9526	2.9526	NUM
iajs-2800	336	10	0.25074	0.25074	NUM
iajs-2800	336	11	100	100	NUM
iajs-2800	336	12	est	est	X
iajs-2800	336	13	.	.	PUNCT
iajs-2800	337	1	values	value	NOUN
iajs-2800	337	2	rmse	rmse	VERB
iajs-2800	337	3	3.0008	3.0008	NUM
iajs-2800	337	4	0.17482	0.17482	NUM
iajs-2800	337	5	3.0058	3.0058	NUM
iajs-2800	337	6	0.1758	0.1758	NUM
iajs-2800	337	7	2.9958	2.9958	NUM
iajs-2800	337	8	0.17575	0.17575	NUM
iajs-2800	337	9	2.9757	2.9757	NUM
iajs-2800	337	10	0.17738	0.17738	NUM
iajs-2800	337	11	9θ	9θ	NUM
iajs-2800	337	12			NUM
iajs-2800	337	13	25	25	NUM
iajs-2800	337	14	est	est	X
iajs-2800	337	15	.	.	PUNCT
iajs-2800	338	1	values	value	NOUN
iajs-2800	338	2	rmse	rmse	VERB
iajs-2800	339	1	9.0033	9.0033	NUM
iajs-2800	339	2	0.58613	0.58613	NUM
iajs-2800	339	3	9.1475	9.1475	NUM
iajs-2800	339	4	0.61608	0.61608	NUM
iajs-2800	339	5	9.1067	9.1067	NUM
iajs-2800	339	6	0.6076	0.6076	NUM
iajs-2800	339	7	9.025	9.025	NUM
iajs-2800	339	8	0.59869	0.59869	NUM
iajs-2800	339	9	50	50	NUM
iajs-2800	339	10	est	est	NOUN
iajs-2800	339	11	.	.	PUNCT
iajs-2800	340	1	values	value	NOUN
iajs-2800	340	2	rmse	rmse	VERB
iajs-2800	341	1	9.0036	9.0036	NUM
iajs-2800	341	2	0.4215	0.4215	NUM
iajs-2800	341	3	9.0746	9.0746	NUM
iajs-2800	341	4	0.43225	0.43225	NUM
iajs-2800	341	5	9.0544	9.0544	NUM
iajs-2800	341	6	0.42922	0.42922	NUM
iajs-2800	341	7	9.014	9.014	NUM
iajs-2800	341	8	0.42599	0.42599	NUM
iajs-2800	341	9	100	100	NUM
iajs-2800	341	10	est	est	X
iajs-2800	341	11	.	.	PUNCT
iajs-2800	342	1	values	value	NOUN
iajs-2800	342	2	rmse	rmse	VERB
iajs-2800	342	3	8.9985	8.9985	NUM
iajs-2800	342	4	0.30358	0.30358	NUM
iajs-2800	342	5	9.0338	9.0338	NUM
iajs-2800	342	6	0.30696	0.30696	NUM
iajs-2800	342	7	9.0237	9.0237	NUM
iajs-2800	342	8	0.30602	0.30602	NUM
iajs-2800	342	9	9.0036	9.0036	NUM
iajs-2800	342	10	0.30512	0.30512	NUM
iajs-2800	342	11	note	note	NOUN
iajs-2800	342	12	:	:	PUNCT
iajs-2800	342	13	the	the	DET
iajs-2800	342	14	shadow	shadow	NOUN
iajs-2800	342	15	cells	cell	NOUN
iajs-2800	342	16	represent	represent	VERB
iajs-2800	342	17	the	the	DET
iajs-2800	342	18	smallest	small	ADJ
iajs-2800	342	19	value	value	NOUN
iajs-2800	342	20	of	of	ADP
iajs-2800	342	21	rmse	rmse	NOUN
iajs-2800	342	22	.	.	PUNCT
iajs-2800	343	1	4	4	X
iajs-2800	343	2	.	.	X
iajs-2800	343	3	discussion	discussion	NOUN
iajs-2800	343	4	for	for	ADP
iajs-2800	343	5	the	the	DET
iajs-2800	343	6	results	result	NOUN
iajs-2800	343	7	listed	list	VERB
iajs-2800	343	8	in	in	ADP
iajs-2800	343	9	table.1and	table.1and	PROPN
iajs-2800	343	10	table.2	table.2	ADJ
iajs-2800	343	11	,	,	PUNCT
iajs-2800	343	12	we	we	PRON
iajs-2800	343	13	see	see	VERB
iajs-2800	343	14	that	that	SCONJ
iajs-2800	343	15	the	the	DET
iajs-2800	343	16	best	good	ADJ
iajs-2800	343	17	bayes	bayes	NOUN
iajs-2800	343	18	estimates	estimate	VERB
iajs-2800	343	19	under	under	ADP
iajs-2800	343	20	the	the	DET
iajs-2800	343	21	squared	square	VERB
iajs-2800	343	22	error	error	NOUN
iajs-2800	343	23	loss	loss	NOUN
iajs-2800	343	24	function	function	NOUN
iajs-2800	343	25	(	(	PUNCT
iajs-2800	343	26	self	self	NOUN
iajs-2800	343	27	)	)	PUNCT
iajs-2800	343	28	according	accord	VERB
iajs-2800	343	29	to	to	ADP
iajs-2800	343	30	the	the	DET
iajs-2800	343	31	smallest	small	ADJ
iajs-2800	343	32	value	value	NOUN
iajs-2800	343	33	of	of	ADP
iajs-2800	343	34	rmse	rmse	NOUN
iajs-2800	343	35	as	as	SCONJ
iajs-2800	343	36	compared	compare	VERB
iajs-2800	343	37	with	with	ADP
iajs-2800	343	38	other	other	ADJ
iajs-2800	343	39	estimates	estimate	NOUN
iajs-2800	343	40	based	base	VERB
iajs-2800	343	41	on	on	ADP
iajs-2800	343	42	the	the	DET
iajs-2800	343	43	other	other	ADJ
iajs-2800	343	44	values	value	NOUN
iajs-2800	343	45	of	of	ADP
iajs-2800	343	46	the	the	DET
iajs-2800	343	47	parameters	parameter	NOUN
iajs-2800	343	48	for	for	ADP
iajs-2800	343	49	the	the	DET
iajs-2800	343	50	same	same	ADJ
iajs-2800	343	51	priors	prior	NOUN
iajs-2800	343	52	as	as	SCONJ
iajs-2800	343	53	listed	list	VERB
iajs-2800	343	54	below	below	ADP
iajs-2800	343	55			DET
iajs-2800	343	56	erlangen	erlangen	PROPN
iajs-2800	343	57	prior	prior	ADV
iajs-2800	343	58	with	with	ADP
iajs-2800	343	59	3δ	3δ	PROPN
iajs-2800	343	60			NOUN
iajs-2800	343	61	,	,	PUNCT
iajs-2800	343	62	inverse	inverse	NOUN
iajs-2800	343	63	levy	levy	NOUN
iajs-2800	343	64	prior	prior	ADV
iajs-2800	343	65	with	with	ADP
iajs-2800	343	66	3	3	NUM
iajs-2800	343	67	v	v	NOUN
iajs-2800	343	68			NOUN
iajs-2800	343	69	and	and	CCONJ
iajs-2800	343	70	noninformative	noninformative	PROPN
iajs-2800	343	71	prior	prior	ADV
iajs-2800	343	72	with	with	ADP
iajs-2800	343	73	2c	2c	NUM
iajs-2800	343	74			NOUN
iajs-2800	343	75	,	,	PUNCT
iajs-2800	343	76	for	for	ADP
iajs-2800	343	77	all	all	DET
iajs-2800	343	78	sample	sample	NOUN
iajs-2800	343	79	sizes	size	NOUN
iajs-2800	343	80	(	(	PUNCT
iajs-2800	343	81	n	n	CCONJ
iajs-2800	343	82	)	)	PUNCT
iajs-2800	343	83	when	when	SCONJ
iajs-2800	343	84	the	the	DET
iajs-2800	343	85	true	true	ADJ
iajs-2800	343	86	value	value	NOUN
iajs-2800	343	87	is	be	AUX
iajs-2800	343	88	1θ	1θ	PROPN
iajs-2800	343	89			NUM
iajs-2800	343	90	.	.	PUNCT
iajs-2800	344	1			PROPN
iajs-2800	344	2	erlang	erlang	PROPN
iajs-2800	344	3	prior	prior	ADV
iajs-2800	344	4	with	with	ADP
iajs-2800	344	5	2δ	2δ	NUM
iajs-2800	344	6			NUM
iajs-2800	344	7	,	,	PUNCT
iajs-2800	344	8	inverse	inverse	NOUN
iajs-2800	344	9	levy	levy	NOUN
iajs-2800	344	10	prior	prior	ADV
iajs-2800	344	11	with	with	ADP
iajs-2800	344	12	1v	1v	NUM
iajs-2800	344	13			NUM
iajs-2800	344	14	and	and	CCONJ
iajs-2800	344	15	noninformative	noninformative	PROPN
iajs-2800	344	16	prior	prior	ADV
iajs-2800	344	17	with	with	ADP
iajs-2800	344	18	2c	2c	NUM
iajs-2800	344	19			NOUN
iajs-2800	344	20	,	,	PUNCT
iajs-2800	344	21	for	for	ADP
iajs-2800	344	22	all	all	DET
iajs-2800	344	23	n	n	NOUN
iajs-2800	345	1	when	when	SCONJ
iajs-2800	345	2	4,3θ	4,3θ	NOUN
iajs-2800	345	3			VERB
iajs-2800	345	4	.	.	PUNCT
iajs-2800	346	1	it	it	PRON
iajs-2800	346	2	is	be	AUX
iajs-2800	346	3	observed	observe	VERB
iajs-2800	346	4	that	that	SCONJ
iajs-2800	346	5	the	the	DET
iajs-2800	346	6	performance	performance	NOUN
iajs-2800	346	7	of	of	ADP
iajs-2800	346	8	bayes	bayes	NOUN
iajs-2800	346	9	estimators	estimator	NOUN
iajs-2800	346	10	under	under	ADP
iajs-2800	346	11	self	self	NOUN
iajs-2800	346	12	are	be	AUX
iajs-2800	346	13	the	the	DET
iajs-2800	346	14	best	good	ADJ
iajs-2800	346	15	according	accord	VERB
iajs-2800	346	16	to	to	ADP
iajs-2800	346	17	the	the	DET
iajs-2800	346	18	smallest	small	ADJ
iajs-2800	346	19	value	value	NOUN
iajs-2800	346	20	of	of	ADP
iajs-2800	346	21	rmse	rmse	NOUN
iajs-2800	346	22	as	as	SCONJ
iajs-2800	346	23	compared	compare	VERB
iajs-2800	346	24	with	with	ADP
iajs-2800	346	25	other	other	ADJ
iajs-2800	346	26	estimators	estimator	NOUN
iajs-2800	346	27	in	in	ADP
iajs-2800	346	28	mle	mle	PROPN
iajs-2800	346	29	for	for	ADP
iajs-2800	346	30			PRON
iajs-2800	346	31	erlang	erlang	PROPN
iajs-2800	346	32	prior	prior	ADV
iajs-2800	346	33	with	with	ADP
iajs-2800	346	34	3δ	3δ	PROPN
iajs-2800	346	35			NUM
iajs-2800	346	36	and	and	CCONJ
iajs-2800	346	37	inverse	inverse	NOUN
iajs-2800	346	38	levy	levy	NOUN
iajs-2800	346	39	prior	prior	ADV
iajs-2800	346	40	with	with	ADP
iajs-2800	346	41	3v	3v	NUM
iajs-2800	346	42			NUM
iajs-2800	346	43	,	,	PUNCT
iajs-2800	346	44	for	for	ADP
iajs-2800	346	45	all	all	DET
iajs-2800	346	46	sample	sample	NOUN
iajs-2800	346	47	sizes	size	NOUN
iajs-2800	346	48	(	(	PUNCT
iajs-2800	346	49	n	n	CCONJ
iajs-2800	346	50	)	)	PUNCT
iajs-2800	346	51	when	when	SCONJ
iajs-2800	346	52	1θ	1θ	PROPN
iajs-2800	346	53			VERB
iajs-2800	346	54	.	.	PUNCT
iajs-2800	347	1			NOUN
iajs-2800	347	2	inverse	inverse	NOUN
iajs-2800	347	3	levy	levy	NOUN
iajs-2800	347	4	prior	prior	ADV
iajs-2800	347	5	with	with	ADP
iajs-2800	347	6	1v	1v	NUM
iajs-2800	347	7			NUM
iajs-2800	347	8	,	,	PUNCT
iajs-2800	347	9	for	for	ADP
iajs-2800	347	10	all	all	DET
iajs-2800	347	11	n	n	NOUN
iajs-2800	347	12	when	when	SCONJ
iajs-2800	347	13	3θ	3θ	PROPN
iajs-2800	347	14			VERB
iajs-2800	347	15	.	.	PUNCT
iajs-2800	348	1	we	we	PRON
iajs-2800	348	2	see	see	VERB
iajs-2800	348	3	that	that	SCONJ
iajs-2800	348	4	the	the	DET
iajs-2800	348	5	best	good	ADJ
iajs-2800	348	6	bayes	bayes	NOUN
iajs-2800	348	7	estimates	estimate	VERB
iajs-2800	348	8	under	under	ADP
iajs-2800	348	9	the	the	DET
iajs-2800	348	10	proposed	propose	VERB
iajs-2800	348	11	exponential	exponential	ADJ
iajs-2800	348	12	loss	loss	NOUN
iajs-2800	348	13	function	function	NOUN
iajs-2800	348	14	according	accord	VERB
iajs-2800	348	15	to	to	ADP
iajs-2800	348	16	the	the	DET
iajs-2800	348	17	smallest	small	ADJ
iajs-2800	348	18	value	value	NOUN
iajs-2800	348	19	of	of	ADP
iajs-2800	348	20	rmse	rmse	NOUN
iajs-2800	348	21	as	as	SCONJ
iajs-2800	348	22	compared	compare	VERB
iajs-2800	348	23	with	with	ADP
iajs-2800	348	24	other	other	ADJ
iajs-2800	348	25	estimates	estimate	NOUN
iajs-2800	348	26	based	base	VERB
iajs-2800	348	27	on	on	ADP
iajs-2800	348	28	the	the	DET
iajs-2800	348	29	other	other	ADJ
iajs-2800	348	30	values	value	NOUN
iajs-2800	348	31	of	of	ADP
iajs-2800	348	32	the	the	DET
iajs-2800	348	33	parameters	parameter	NOUN
iajs-2800	348	34	for	for	ADP
iajs-2800	348	35	the	the	DET
iajs-2800	348	36	same	same	ADJ
iajs-2800	348	37	priors	prior	NOUN
iajs-2800	348	38	as	as	SCONJ
iajs-2800	348	39	listed	list	VERB
iajs-2800	348	40	below	below	ADP
iajs-2800	348	41	ibn	ibn	PROPN
iajs-2800	348	42	al	al	PROPN
iajs-2800	348	43	-	-	PUNCT
iajs-2800	348	44	haitham	haitham	PROPN
iajs-2800	348	45	jour	jour	X
iajs-2800	348	46	.	.	PROPN
iajs-2800	348	47	for	for	ADP
iajs-2800	348	48	pure	pure	ADJ
iajs-2800	348	49	&	&	CCONJ
iajs-2800	348	50	appl	appl	PROPN
iajs-2800	348	51	.	.	PUNCT
iajs-2800	349	1	sci	sci	PROPN
iajs-2800	349	2	.	.	PROPN
iajs-2800	350	1	53	53	NUM
iajs-2800	350	2	(	(	PUNCT
iajs-2800	350	3	1)2022	1)2022	PROPN
iajs-2800	350	4	71	71	NUM
iajs-2800	350	5			NOUN
iajs-2800	350	6	erlang	erlang	PROPN
iajs-2800	350	7	prior	prior	ADV
iajs-2800	350	8	with	with	ADP
iajs-2800	350	9	3δ	3δ	PROPN
iajs-2800	350	10			NOUN
iajs-2800	350	11	,	,	PUNCT
iajs-2800	350	12	inverse	inverse	NOUN
iajs-2800	350	13	levy	levy	NOUN
iajs-2800	350	14	prior	prior	ADV
iajs-2800	350	15	with	with	ADP
iajs-2800	350	16	3v	3v	NUM
iajs-2800	350	17			NUM
iajs-2800	350	18	and	and	CCONJ
iajs-2800	350	19	noninformative	noninformative	PROPN
iajs-2800	350	20	prior	prior	ADV
iajs-2800	350	21	with	with	ADP
iajs-2800	350	22	2c	2c	NUM
iajs-2800	350	23			NOUN
iajs-2800	350	24	,	,	PUNCT
iajs-2800	350	25	for	for	ADP
iajs-2800	350	26	all	all	DET
iajs-2800	350	27	n	n	NOUN
iajs-2800	350	28	when	when	SCONJ
iajs-2800	350	29	1θ	1θ	PROPN
iajs-2800	350	30			VERB
iajs-2800	350	31	.	.	PUNCT
iajs-2800	351	1			PROPN
iajs-2800	351	2	erlang	erlang	PROPN
iajs-2800	351	3	prior	prior	ADV
iajs-2800	351	4	with	with	ADP
iajs-2800	351	5	2δ	2δ	NUM
iajs-2800	351	6			NUM
iajs-2800	351	7	,	,	PUNCT
iajs-2800	351	8	for	for	ADP
iajs-2800	351	9	all	all	DET
iajs-2800	351	10	n	n	NOUN
iajs-2800	352	1	when	when	SCONJ
iajs-2800	352	2	9,3θ	9,3θ	ADV
iajs-2800	352	3			VERB
iajs-2800	352	4	.	.	PUNCT
iajs-2800	353	1			NOUN
iajs-2800	353	2	inverse	inverse	NOUN
iajs-2800	353	3	levy	levy	NOUN
iajs-2800	353	4	prior	prior	ADV
iajs-2800	353	5	with	with	ADP
iajs-2800	353	6	1v	1v	NUM
iajs-2800	353	7			NUM
iajs-2800	353	8	,	,	PUNCT
iajs-2800	353	9	for	for	ADP
iajs-2800	353	10	n=25	n=25	ADV
iajs-2800	354	1	when	when	SCONJ
iajs-2800	354	2	3θ	3θ	PROPN
iajs-2800	354	3			VERB
iajs-2800	354	4	.and	.and	NOUN
iajs-2800	354	5	for	for	ADP
iajs-2800	354	6	all	all	DET
iajs-2800	354	7	n	n	NOUN
iajs-2800	354	8	when	when	SCONJ
iajs-2800	354	9	9θ	9θ	PRON
iajs-2800	354	10			VERB
iajs-2800	354	11	.	.	PUNCT
iajs-2800	355	1			PROPN
iajs-2800	355	2	noninformative	noninformative	PROPN
iajs-2800	355	3	prior	prior	ADV
iajs-2800	355	4	with	with	ADP
iajs-2800	355	5	5	5	NUM
iajs-2800	355	6	3,c	3,c	NUM
iajs-2800	355	7			NOUN
iajs-2800	355	8	,	,	PUNCT
iajs-2800	355	9	for	for	ADP
iajs-2800	355	10	all	all	DET
iajs-2800	355	11	n	n	NOUN
iajs-2800	355	12	when	when	SCONJ
iajs-2800	355	13	3,5θ	3,5θ	NUM
iajs-2800	355	14			NUM
iajs-2800	355	15	respectively	respectively	ADV
iajs-2800	355	16	.	.	PUNCT
iajs-2800	356	1	it	it	PRON
iajs-2800	356	2	is	be	AUX
iajs-2800	356	3	observed	observe	VERB
iajs-2800	356	4	that	that	SCONJ
iajs-2800	356	5	the	the	DET
iajs-2800	356	6	performance	performance	NOUN
iajs-2800	356	7	of	of	ADP
iajs-2800	356	8	bayes	bayes	NOUN
iajs-2800	356	9	estimators	estimator	NOUN
iajs-2800	356	10	under	under	ADP
iajs-2800	356	11	proposed	propose	VERB
iajs-2800	356	12	exponential	exponential	NOUN
iajs-2800	356	13	are	be	AUX
iajs-2800	356	14	the	the	DET
iajs-2800	356	15	best	good	ADJ
iajs-2800	356	16	according	accord	VERB
iajs-2800	356	17	to	to	ADP
iajs-2800	356	18	the	the	DET
iajs-2800	356	19	smallest	small	ADJ
iajs-2800	356	20	value	value	NOUN
iajs-2800	356	21	of	of	ADP
iajs-2800	356	22	rmse	rmse	NOUN
iajs-2800	356	23	as	as	SCONJ
iajs-2800	356	24	compared	compare	VERB
iajs-2800	356	25	with	with	ADP
iajs-2800	356	26	other	other	ADJ
iajs-2800	356	27	estimators	estimator	NOUN
iajs-2800	356	28	in	in	ADP
iajs-2800	356	29	mle	mle	PROPN
iajs-2800	356	30	for	for	ADP
iajs-2800	356	31			PRON
iajs-2800	356	32	erlang	erlang	PROPN
iajs-2800	356	33	prior	prior	ADV
iajs-2800	356	34	with	with	ADP
iajs-2800	356	35	3δ	3δ	PROPN
iajs-2800	356	36			NOUN
iajs-2800	356	37	,	,	PUNCT
iajs-2800	356	38	inverse	inverse	NOUN
iajs-2800	356	39	levy	levy	NOUN
iajs-2800	356	40	prior	prior	ADV
iajs-2800	356	41	with	with	ADP
iajs-2800	356	42	3v	3v	NUM
iajs-2800	356	43			NUM
iajs-2800	356	44	for	for	ADP
iajs-2800	356	45	all	all	DET
iajs-2800	356	46	n	n	NOUN
iajs-2800	356	47	when	when	SCONJ
iajs-2800	356	48	1θ	1θ	PROPN
iajs-2800	356	49			VERB
iajs-2800	356	50	.	.	PUNCT
iajs-2800	357	1			PROPN
iajs-2800	357	2	erlang	erlang	PROPN
iajs-2800	357	3	prior	prior	ADV
iajs-2800	357	4	with	with	ADP
iajs-2800	357	5	2δ	2δ	NUM
iajs-2800	357	6			NUM
iajs-2800	357	7	,	,	PUNCT
iajs-2800	357	8	for	for	ADP
iajs-2800	357	9	all	all	DET
iajs-2800	357	10	n	n	NOUN
iajs-2800	357	11	when	when	SCONJ
iajs-2800	357	12	3θ	3θ	PROPN
iajs-2800	357	13			VERB
iajs-2800	357	14	.	.	PUNCT
iajs-2800	358	1			NOUN
iajs-2800	358	2	inverse	inverse	NOUN
iajs-2800	358	3	levy	levy	NOUN
iajs-2800	358	4	prior	prior	ADV
iajs-2800	358	5	with	with	ADP
iajs-2800	358	6	1v	1v	NUM
iajs-2800	358	7			NUM
iajs-2800	358	8	for	for	ADP
iajs-2800	358	9	n=25	n=25	PROPN
iajs-2800	358	10	and	and	CCONJ
iajs-2800	358	11	with	with	ADP
iajs-2800	358	12	3v	3v	NUM
iajs-2800	358	13			NUM
iajs-2800	358	14	for	for	ADP
iajs-2800	358	15	n=50	n=50	ADJ
iajs-2800	358	16	,	,	PUNCT
iajs-2800	358	17	100	100	NUM
iajs-2800	358	18	when	when	SCONJ
iajs-2800	358	19	3θ	3θ	NOUN
iajs-2800	358	20			NUM
iajs-2800	358	21	.	.	PUNCT
iajs-2800	359	1	5	5	X
iajs-2800	359	2	.	.	X
iajs-2800	359	3	conclusion	conclusion	NOUN
iajs-2800	359	4	in	in	ADP
iajs-2800	359	5	this	this	DET
iajs-2800	359	6	paper	paper	NOUN
iajs-2800	359	7	we	we	PRON
iajs-2800	359	8	have	have	AUX
iajs-2800	359	9	presented	present	VERB
iajs-2800	359	10	the	the	DET
iajs-2800	359	11	bayesian	bayesian	NOUN
iajs-2800	359	12	and	and	CCONJ
iajs-2800	359	13	maximum	maximum	ADJ
iajs-2800	359	14	likelihood	likelihood	NOUN
iajs-2800	359	15	estimates	estimate	NOUN
iajs-2800	359	16	of	of	ADP
iajs-2800	359	17	the	the	DET
iajs-2800	359	18	parameter	parameter	NOUN
iajs-2800	359	19	of	of	ADP
iajs-2800	359	20	the	the	DET
iajs-2800	359	21	poisson	poisson	NOUN
iajs-2800	359	22	distribution	distribution	NOUN
iajs-2800	359	23	.	.	PUNCT
iajs-2800	360	1	the	the	DET
iajs-2800	360	2	estimation	estimation	NOUN
iajs-2800	360	3	is	be	AUX
iajs-2800	360	4	conducted	conduct	VERB
iajs-2800	360	5	on	on	ADP
iajs-2800	360	6	rmse	rmse	NOUN
iajs-2800	360	7	.	.	PUNCT
iajs-2800	361	1	bayes	bayes	PROPN
iajs-2800	361	2	estimators	estimator	NOUN
iajs-2800	361	3	,	,	PUNCT
iajs-2800	361	4	under	under	ADP
iajs-2800	361	5	squared	square	VERB
iajs-2800	361	6	error	error	NOUN
iajs-2800	361	7	loss	loss	NOUN
iajs-2800	361	8	function	function	NOUN
iajs-2800	361	9	and	and	CCONJ
iajs-2800	361	10	the	the	DET
iajs-2800	361	11	proposed	propose	VERB
iajs-2800	361	12	exponential	exponential	ADJ
iajs-2800	361	13	loss	loss	NOUN
iajs-2800	361	14	function	function	NOUN
iajs-2800	361	15	.	.	PUNCT
iajs-2800	362	1	the	the	DET
iajs-2800	362	2	mle	mle	PROPN
iajs-2800	362	3	’s	’s	PART
iajs-2800	362	4	are	be	AUX
iajs-2800	362	5	also	also	ADV
iajs-2800	362	6	obtained	obtain	VERB
iajs-2800	362	7	.	.	PUNCT
iajs-2800	363	1	our	our	PRON
iajs-2800	363	2	conclusions	conclusion	NOUN
iajs-2800	363	3	about	about	ADP
iajs-2800	363	4	the	the	DET
iajs-2800	363	5	results	result	NOUN
iajs-2800	363	6	are	be	AUX
iajs-2800	363	7	stated	state	VERB
iajs-2800	363	8	in	in	ADP
iajs-2800	363	9	the	the	DET
iajs-2800	363	10	following	follow	VERB
iajs-2800	363	11	points	point	NOUN
iajs-2800	363	12	:	:	PUNCT
iajs-2800	363	13	the	the	DET
iajs-2800	363	14	bayes	bayes	NOUN
iajs-2800	363	15	estimates	estimate	VERB
iajs-2800	363	16	under	under	ADP
iajs-2800	363	17	the	the	DET
iajs-2800	363	18	proposed	propose	VERB
iajs-2800	363	19	exponential	exponential	ADJ
iajs-2800	363	20	loss	loss	NOUN
iajs-2800	363	21	function	function	NOUN
iajs-2800	363	22	usually	usually	ADV
iajs-2800	363	23	have	have	VERB
iajs-2800	363	24	the	the	DET
iajs-2800	363	25	most	most	ADV
iajs-2800	363	26	minor	minor	ADJ
iajs-2800	363	27	estimated	estimate	VERB
iajs-2800	363	28	rmse	rmse	NOUN
iajs-2800	363	29	’s	’	VERB
iajs-2800	363	30	as	as	SCONJ
iajs-2800	363	31	compared	compare	VERB
iajs-2800	363	32	to	to	ADP
iajs-2800	363	33	the	the	DET
iajs-2800	363	34	rmse	rmse	NOUN
iajs-2800	363	35	’s	’s	PART
iajs-2800	363	36	estimates	estimate	NOUN
iajs-2800	363	37	under	under	ADP
iajs-2800	363	38	the	the	DET
iajs-2800	363	39	squared	square	VERB
iajs-2800	363	40	error	error	NOUN
iajs-2800	363	41	loss	loss	NOUN
iajs-2800	363	42	function	function	NOUN
iajs-2800	363	43	based	base	VERB
iajs-2800	363	44	on	on	ADP
iajs-2800	363	45	the	the	DET
iajs-2800	363	46	same	same	ADJ
iajs-2800	363	47	prior	prior	NOUN
iajs-2800	363	48	,	,	PUNCT
iajs-2800	363	49	with	with	ADP
iajs-2800	363	50	the	the	DET
iajs-2800	363	51	same	same	ADJ
iajs-2800	363	52	values	value	NOUN
iajs-2800	363	53	to	to	ADP
iajs-2800	363	54	their	their	PRON
iajs-2800	363	55	parameters	parameter	NOUN
iajs-2800	363	56	for	for	ADP
iajs-2800	363	57	all	all	DET
iajs-2800	363	58	sample	sample	NOUN
iajs-2800	363	59	sizes	size	NOUN
iajs-2800	363	60	.	.	PUNCT
iajs-2800	364	1	from	from	ADP
iajs-2800	364	2	table	table	NOUN
iajs-2800	364	3	1	1	NUM
iajs-2800	364	4	and	and	CCONJ
iajs-2800	364	5	table	table	NOUN
iajs-2800	364	6	2	2	NUM
iajs-2800	364	7	,	,	PUNCT
iajs-2800	364	8	we	we	PRON
iajs-2800	364	9	can	can	AUX
iajs-2800	364	10	see	see	VERB
iajs-2800	364	11	that	that	SCONJ
iajs-2800	364	12	1	1	X
iajs-2800	364	13	.	.	X
iajs-2800	364	14	erlang	erlang	PROPN
iajs-2800	364	15	prior	prior	ADV
iajs-2800	364	16	with	with	ADP
iajs-2800	364	17	3	3	NUM
iajs-2800	364	18	,	,	PUNCT
iajs-2800	364	19	2δ	2δ	NUM
iajs-2800	364	20			NUM
iajs-2800	364	21	when	when	SCONJ
iajs-2800	365	1	9,3θ	9,3θ	ADV
iajs-2800	365	2			NUM
iajs-2800	365	3	and	and	CCONJ
iajs-2800	365	4	with	with	ADP
iajs-2800	365	5	5δ	5δ	NUM
iajs-2800	365	6			NOUN
iajs-2800	365	7	when	when	SCONJ
iajs-2800	365	8	9	9	NUM
iajs-2800	365	9	,	,	PUNCT
iajs-2800	365	10	3	3	NUM
iajs-2800	365	11	,	,	PUNCT
iajs-2800	365	12	1θ	1θ	NUM
iajs-2800	365	13			ADJ
iajs-2800	365	14	for	for	ADP
iajs-2800	365	15	all	all	DET
iajs-2800	365	16	sample	sample	NOUN
iajs-2800	365	17	sizes	size	NOUN
iajs-2800	365	18	.	.	PUNCT
iajs-2800	366	1	2	2	X
iajs-2800	366	2	.	.	X
iajs-2800	366	3	inverse	inverse	NOUN
iajs-2800	366	4	levy	levy	NOUN
iajs-2800	366	5	prior	prior	ADV
iajs-2800	366	6	with	with	ADP
iajs-2800	366	7	v=1	v=1	ADP
iajs-2800	366	8	when	when	SCONJ
iajs-2800	366	9	9	9	NUM
iajs-2800	366	10	θ	θ	NOUN
iajs-2800	366	11			NOUN
iajs-2800	366	12	and	and	CCONJ
iajs-2800	366	13	with	with	ADP
iajs-2800	366	14	v=3	v=3	NOUN
iajs-2800	366	15	when	when	SCONJ
iajs-2800	366	16	9,3θ	9,3θ	ADV
iajs-2800	366	17			NUM
iajs-2800	366	18	and	and	CCONJ
iajs-2800	366	19	with	with	ADP
iajs-2800	366	20	v=5	v=5	PROPN
iajs-2800	366	21	when	when	SCONJ
iajs-2800	366	22	9	9	NUM
iajs-2800	366	23	,	,	PUNCT
iajs-2800	366	24	3	3	NUM
iajs-2800	366	25	,	,	PUNCT
iajs-2800	366	26	1θ	1θ	NUM
iajs-2800	366	27			NOUN
iajs-2800	367	1	.	.	PUNCT
iajs-2800	368	1	3	3	X
iajs-2800	368	2	.	.	X
iajs-2800	368	3	non	non	ADJ
iajs-2800	368	4	-	-	ADJ
iajs-2800	368	5	informative	informative	ADJ
iajs-2800	368	6	prior	prior	ADV
iajs-2800	368	7	with	with	ADP
iajs-2800	368	8	3c	3c	NUM
iajs-2800	368	9			NOUN
iajs-2800	368	10	when	when	SCONJ
iajs-2800	368	11	3	3	NUM
iajs-2800	368	12	,	,	PUNCT
iajs-2800	368	13	1θ	1θ	NUM
iajs-2800	368	14			NOUN
iajs-2800	368	15	and	and	CCONJ
iajs-2800	368	16	with	with	ADP
iajs-2800	368	17	5c	5c	NUM
iajs-2800	368	18			NUM
iajs-2800	368	19	when	when	SCONJ
iajs-2800	368	20	9	9	NUM
iajs-2800	368	21	,	,	PUNCT
iajs-2800	368	22	3	3	NUM
iajs-2800	368	23	,	,	PUNCT
iajs-2800	368	24	1θ	1θ	NUM
iajs-2800	368	25			NOUN
iajs-2800	368	26	.	.	PUNCT
iajs-2800	369	1	the	the	DET
iajs-2800	369	2	bayes	bayes	PROPN
iajs-2800	369	3	estimates	estimate	VERB
iajs-2800	369	4	under	under	ADP
iajs-2800	369	5	the	the	DET
iajs-2800	369	6	proposed	propose	VERB
iajs-2800	369	7	exponential	exponential	ADJ
iajs-2800	369	8	loss	loss	NOUN
iajs-2800	369	9	function	function	NOUN
iajs-2800	369	10	have	have	VERB
iajs-2800	369	11	the	the	DET
iajs-2800	369	12	smallest	small	ADJ
iajs-2800	369	13	estimated	estimate	VERB
iajs-2800	369	14	rmse	rmse	NOUN
iajs-2800	369	15	’s	’	VERB
iajs-2800	369	16	as	as	SCONJ
iajs-2800	369	17	compared	compare	VERB
iajs-2800	369	18	with	with	ADP
iajs-2800	369	19	the	the	DET
iajs-2800	369	20	rmse	rmse	NOUN
iajs-2800	369	21	’s	’s	ADV
iajs-2800	369	22	of	of	ADP
iajs-2800	369	23	estimates	estimate	NOUN
iajs-2800	369	24	of	of	ADP
iajs-2800	369	25	the	the	DET
iajs-2800	369	26	maximum	maximum	ADJ
iajs-2800	369	27	likelihood	likelihood	NOUN
iajs-2800	369	28	estimates(mle	estimates(mle	NOUN
iajs-2800	369	29	)	)	PUNCT
iajs-2800	369	30	,	,	PUNCT
iajs-2800	369	31	for	for	ADP
iajs-2800	369	32	the	the	DET
iajs-2800	369	33	same	same	ADJ
iajs-2800	369	34	value	value	NOUN
iajs-2800	369	35	for	for	ADP
iajs-2800	369	36	θ	θ	PROPN
iajs-2800	369	37	and	and	CCONJ
iajs-2800	369	38	sample	sample	NOUN
iajs-2800	369	39	sizes	size	NOUN
iajs-2800	369	40	.	.	PUNCT
iajs-2800	370	1	from	from	ADP
iajs-2800	370	2	table	table	NOUN
iajs-2800	370	3	1	1	NUM
iajs-2800	370	4	and	and	CCONJ
iajs-2800	370	5	table	table	NOUN
iajs-2800	370	6	2	2	NUM
iajs-2800	370	7	,	,	PUNCT
iajs-2800	370	8	we	we	PRON
iajs-2800	370	9	can	can	AUX
iajs-2800	370	10	see	see	VERB
iajs-2800	370	11	that	that	SCONJ
iajs-2800	370	12	1	1	X
iajs-2800	370	13	.	.	X
iajs-2800	370	14	erlang	erlang	PROPN
iajs-2800	370	15	prior	prior	ADV
iajs-2800	370	16	with	with	ADP
iajs-2800	370	17	)	)	PUNCT
iajs-2800	370	18	2δ	2δ	NUM
iajs-2800	370	19	(	(	PUNCT
iajs-2800	370	20			NUM
iajs-2800	370	21	when	when	SCONJ
iajs-2800	370	22	3θ	3θ	NUM
iajs-2800	370	23			VERB
iajs-2800	370	24	and	and	CCONJ
iajs-2800	370	25	with	with	ADP
iajs-2800	370	26	5	5	NUM
iajs-2800	370	27	3,δ	3,δ	NUM
iajs-2800	370	28			NOUN
iajs-2800	370	29	when	when	SCONJ
iajs-2800	370	30	1θ	1θ	PROPN
iajs-2800	370	31			NOUN
iajs-2800	370	32	.	.	PUNCT
iajs-2800	371	1	2	2	X
iajs-2800	371	2	.	.	X
iajs-2800	371	3	inverse	inverse	NOUN
iajs-2800	371	4	levy	levy	NOUN
iajs-2800	371	5	prior	prior	ADV
iajs-2800	371	6	with	with	ADP
iajs-2800	371	7	v=3,5	v=3,5	NOUN
iajs-2800	371	8	when	when	SCONJ
iajs-2800	371	9	the	the	DET
iajs-2800	371	10	true	true	ADJ
iajs-2800	371	11	value	value	NOUN
iajs-2800	371	12	1θ	1θ	PROPN
iajs-2800	371	13			NUM
iajs-2800	371	14	.	.	PUNCT
iajs-2800	372	1	references	reference	NOUN
iajs-2800	372	2	1	1	NUM
iajs-2800	372	3	.	.	PUNCT
iajs-2800	373	1	larsson	larsson	PROPN
iajs-2800	373	2	r.;how	r.;how	PROPN
iajs-2800	373	3	informative	informative	ADJ
iajs-2800	373	4	is	be	AUX
iajs-2800	373	5	a	a	DET
iajs-2800	373	6	non	non	ADJ
iajs-2800	373	7	-	-	ADJ
iajs-2800	373	8	informative	informative	ADJ
iajs-2800	373	9	prior	prior	ADV
iajs-2800	373	10	?	?	PUNCT
iajs-2800	373	11	.	.	PUNCT
iajs-2800	374	1	working	work	VERB
iajs-2800	374	2	paper	paper	PROPN
iajs-2800	374	3	department	department	PROPN
iajs-2800	374	4	of	of	ADP
iajs-2800	374	5	statistics	statistics	PROPN
iajs-2800	374	6	uppsala	uppsala	PROPN
iajs-2800	374	7	university	university	PROPN
iajs-2800	374	8	.	.	PUNCT
iajs-2800	375	1	2011	2011	NUM
iajs-2800	375	2	,	,	PUNCT
iajs-2800	375	3	2:1	2:1	NUM
iajs-2800	375	4	-	-	SYM
iajs-2800	375	5	8	8	NUM
iajs-2800	375	6	.	.	NOUN
iajs-2800	376	1	2	2	NUM
iajs-2800	376	2	.	.	X
iajs-2800	376	3	sultan	sultan	PROPN
iajs-2800	376	4	r.	r.	PROPN
iajs-2800	376	5	;	;	PUNCT
iajs-2800	377	1	ahmad	ahmad	PROPN
iajs-2800	377	2	s.	s.	PROPN
iajs-2800	377	3	p.	p.	PROPN
iajs-2800	377	4	;	;	PUNCT
iajs-2800	377	5	posterior	posterior	ADJ
iajs-2800	377	6	estimates	estimate	NOUN
iajs-2800	377	7	of	of	ADP
iajs-2800	377	8	poisson	poisson	NOUN
iajs-2800	377	9	distribution	distribution	NOUN
iajs-2800	377	10	using	use	VERB
iajs-2800	377	11	r	r	NOUN
iajs-2800	377	12	software	software	NOUN
iajs-2800	377	13	.	.	PUNCT
iajs-2800	378	1	journal	journal	NOUN
iajs-2800	378	2	of	of	ADP
iajs-2800	378	3	modern	modern	ADJ
iajs-2800	378	4	applied	apply	VERB
iajs-2800	378	5	statistical	statistical	ADJ
iajs-2800	378	6	methods	method	NOUN
iajs-2800	378	7	.	.	PUNCT
iajs-2800	379	1	2012	2012	NUM
iajs-2800	379	2	,	,	PUNCT
iajs-2800	379	3	11	11	NUM
iajs-2800	379	4	,	,	PUNCT
iajs-2800	379	5	2	2	NUM
iajs-2800	379	6	:	:	SYM
iajs-2800	379	7	530	530	NUM
iajs-2800	379	8	-	-	SYM
iajs-2800	379	9	535	535	NUM
iajs-2800	379	10	.	.	PUNCT
iajs-2800	380	1	3	3	X
iajs-2800	380	2	.	.	X
iajs-2800	380	3	sahoo	sahoo	PROPN
iajs-2800	380	4	s.	s.	PROPN
iajs-2800	380	5	a	a	PROPN
iajs-2800	380	6	;	;	PUNCT
iajs-2800	380	7	study	study	NOUN
iajs-2800	380	8	on	on	ADP
iajs-2800	380	9	bayesian	bayesian	NOUN
iajs-2800	380	10	estimation	estimation	NOUN
iajs-2800	380	11	of	of	ADP
iajs-2800	380	12	parameters	parameter	NOUN
iajs-2800	380	13	of	of	ADP
iajs-2800	380	14	some	some	DET
iajs-2800	380	15	well	well	ADV
iajs-2800	380	16	known	know	VERB
iajs-2800	380	17	distribution	distribution	NOUN
iajs-2800	380	18	functions	function	NOUN
iajs-2800	380	19	.	.	PUNCT
iajs-2800	381	1	thesis	thesis	NOUN
iajs-2800	381	2	submitted	submit	VERB
iajs-2800	381	3	in	in	ADP
iajs-2800	381	4	partial	partial	ADJ
iajs-2800	381	5	fulfillment	fulfillment	NOUN
iajs-2800	381	6	of	of	ADP
iajs-2800	381	7	the	the	DET
iajs-2800	381	8	requirements	requirement	NOUN
iajs-2800	381	9	for	for	ADP
iajs-2800	381	10	the	the	DET
iajs-2800	381	11	degree	degree	NOUN
iajs-2800	381	12	of	of	ADP
iajs-2800	381	13	master	master	NOUN
iajs-2800	381	14	of	of	ADP
iajs-2800	381	15	science	science	NOUN
iajs-2800	381	16	,	,	PUNCT
iajs-2800	381	17	2014	2014	NUM
iajs-2800	381	18	.	.	PUNCT
iajs-2800	382	1	4	4	X
iajs-2800	382	2	.	.	PUNCT
iajs-2800	382	3	araveeporn	araveeporn	ADJ
iajs-2800	382	4	a.	a.	NOUN
iajs-2800	382	5	;	;	PUNCT
iajs-2800	382	6	parameter	parameter	NOUN
iajs-2800	382	7	estimation	estimation	NOUN
iajs-2800	382	8	of	of	ADP
iajs-2800	382	9	poisson	poisson	NOUN
iajs-2800	382	10	distribution	distribution	NOUN
iajs-2800	382	11	by	by	ADP
iajs-2800	382	12	using	use	VERB
iajs-2800	382	13	maximum	maximum	ADJ
iajs-2800	382	14	likelihood	likelihood	NOUN
iajs-2800	382	15	,	,	PUNCT
iajs-2800	382	16	markov	markov	NOUN
iajs-2800	382	17	chain	chain	NOUN
iajs-2800	382	18	monte	monte	PROPN
iajs-2800	382	19	carlo	carlo	PROPN
iajs-2800	382	20	,	,	PUNCT
iajs-2800	382	21	and	and	CCONJ
iajs-2800	382	22	bayes	bayes	PROPN
iajs-2800	382	23	method	method	PROPN
iajs-2800	382	24	.	.	PUNCT
iajs-2800	383	1	thammasat	thammasat	PROPN
iajs-2800	383	2	international	international	PROPN
iajs-2800	383	3	journal	journal	PROPN
iajs-2800	383	4	of	of	ADP
iajs-2800	383	5	science	science	NOUN
iajs-2800	383	6	and	and	CCONJ
iajs-2800	383	7	technology	technology	NOUN
iajs-2800	383	8	.	.	PUNCT
iajs-2800	384	1	2014	2014	NUM
iajs-2800	384	2	,	,	PUNCT
iajs-2800	384	3	19	19	NUM
iajs-2800	384	4	,	,	PUNCT
iajs-2800	384	5	3:1	3:1	NUM
iajs-2800	384	6	-	-	SYM
iajs-2800	384	7	14	14	NUM
iajs-2800	384	8	.	.	PUNCT
iajs-2800	385	1	5	5	X
iajs-2800	385	2	.	.	X
iajs-2800	385	3	nadarajah	nadarajah	PROPN
iajs-2800	385	4	s.	s.	PROPN
iajs-2800	385	5	;	;	PUNCT
iajs-2800	385	6	alizadeh	alizadeh	NOUN
iajs-2800	385	7	m.	m.	NOUN
iajs-2800	385	8	;	;	PUNCT
iajs-2800	385	9	bagheri	bagheri	PROPN
iajs-2800	385	10	s.f	s.f	PROPN
iajs-2800	385	11	.	.	PROPN
iajs-2800	385	12	;	;	PUNCT
iajs-2800	385	13	bayesian	bayesian	NOUN
iajs-2800	385	14	and	and	CCONJ
iajs-2800	385	15	nonbayesian	nonbayesian	ADJ
iajs-2800	385	16	interval	interval	NOUN
iajs-2800	385	17	estimators	estimator	NOUN
iajs-2800	385	18	for	for	ADP
iajs-2800	385	19	the	the	DET
iajs-2800	385	20	poisson	poisson	NOUN
iajs-2800	385	21	mean	mean	NOUN
iajs-2800	385	22	.	.	PUNCT
iajs-2800	386	1	revastat	revastat	ADJ
iajs-2800	386	2	–	–	PUNCT
iajs-2800	386	3	statistical	statistical	ADJ
iajs-2800	386	4	journal	journal	NOUN
iajs-2800	386	5	.	.	PUNCT
iajs-2800	387	1	2015	2015	NUM
iajs-2800	387	2	,	,	PUNCT
iajs-2800	387	3	13	13	NUM
iajs-2800	387	4	,	,	PUNCT
iajs-2800	387	5	3:245–262	3:245–262	NUM
iajs-2800	387	6	.	.	PUNCT
iajs-2800	388	1	ibn	ibn	PROPN
iajs-2800	388	2	al	al	PROPN
iajs-2800	388	3	-	-	PUNCT
iajs-2800	388	4	haitham	haitham	PROPN
iajs-2800	388	5	jour	jour	X
iajs-2800	388	6	.	.	PROPN
iajs-2800	388	7	for	for	ADP
iajs-2800	388	8	pure	pure	ADJ
iajs-2800	388	9	&	&	CCONJ
iajs-2800	388	10	appl	appl	PROPN
iajs-2800	388	11	.	.	PUNCT
iajs-2800	389	1	sci	sci	PROPN
iajs-2800	389	2	.	.	PROPN
iajs-2800	390	1	53	53	NUM
iajs-2800	390	2	(	(	PUNCT
iajs-2800	390	3	1)2022	1)2022	PROPN
iajs-2800	390	4	72	72	NUM
iajs-2800	390	5	6	6	NUM
iajs-2800	390	6	.	.	PUNCT
iajs-2800	391	1	zhang	zhang	PROPN
iajs-2800	391	2	y.	y.	PROPN
iajs-2800	391	3	;	;	PUNCT
iajs-2800	391	4	ze	ze	PROPN
iajs-2800	391	5	-	-	PUNCT
iajs-2800	391	6	yu	yu	PROPN
iajs-2800	391	7	w.	w.	PROPN
iajs-2800	391	8	;	;	PUNCT
iajs-2800	391	9	zheng	zheng	PROPN
iajs-2800	391	10	-	-	PUNCT
iajs-2800	391	11	min	min	PROPN
iajs-2800	391	12	d.;wen	d.;wen	NOUN
iajs-2800	391	13	m.	m.	NOUN
iajs-2800	391	14	;	;	PUNCT
iajs-2800	391	15	the	the	DET
iajs-2800	391	16	empirical	empirical	ADJ
iajs-2800	391	17	bayes	bayes	NOUN
iajs-2800	391	18	estimators	estimator	NOUN
iajs-2800	391	19	of	of	ADP
iajs-2800	391	20	the	the	DET
iajs-2800	391	21	parameter	parameter	NOUN
iajs-2800	391	22	of	of	ADP
iajs-2800	391	23	the	the	DET
iajs-2800	391	24	poisson	poisson	NOUN
iajs-2800	391	25	distribution	distribution	NOUN
iajs-2800	391	26	with	with	ADP
iajs-2800	391	27	a	a	DET
iajs-2800	391	28	conjugate	conjugate	ADJ
iajs-2800	391	29	gamma	gamma	NOUN
iajs-2800	391	30	prior	prior	ADV
iajs-2800	391	31	under	under	ADP
iajs-2800	391	32	stein	stein	PROPN
iajs-2800	391	33	's	's	PART
iajs-2800	391	34	loss	loss	NOUN
iajs-2800	391	35	function	function	NOUN
iajs-2800	391	36	.	.	PUNCT
iajs-2800	392	1	journal	journal	NOUN
iajs-2800	392	2	of	of	ADP
iajs-2800	392	3	statistical	statistical	ADJ
iajs-2800	392	4	computation	computation	NOUN
iajs-2800	392	5	and	and	CCONJ
iajs-2800	392	6	simulation.2019	simulation.2019	PROPN
iajs-2800	392	7	,	,	PUNCT
iajs-2800	392	8	89	89	NUM
iajs-2800	392	9	,	,	PUNCT
iajs-2800	392	10	16	16	NUM
iajs-2800	392	11	:	:	SYM
iajs-2800	392	12	3061	3061	NUM
iajs-2800	392	13	-	-	SYM
iajs-2800	392	14	3074	3074	NUM
iajs-2800	392	15	.	.	PUNCT
iajs-2800	393	1	7	7	X
iajs-2800	393	2	.	.	PUNCT
iajs-2800	393	3	mohammed	mohammed	PROPN
iajs-2800	393	4	h.	h.	PROPN
iajs-2800	393	5	s.	s.	PROPN
iajs-2800	393	6	;	;	PUNCT
iajs-2800	393	7	empirical	empirical	ADJ
iajs-2800	393	8	e	e	NOUN
iajs-2800	393	9	-	-	ADJ
iajs-2800	393	10	bayesian	bayesian	ADJ
iajs-2800	393	11	estimation	estimation	NOUN
iajs-2800	393	12	for	for	ADP
iajs-2800	393	13	the	the	DET
iajs-2800	393	14	parameter	parameter	NOUN
iajs-2800	393	15	of	of	ADP
iajs-2800	393	16	poisson	poisson	NOUN
iajs-2800	393	17	distribution	distribution	NOUN
iajs-2800	393	18	.	.	PUNCT
iajs-2800	394	1	aims	aim	VERB
iajs-2800	394	2	mathematics	mathematic	NOUN
iajs-2800	394	3	.	.	PUNCT
iajs-2800	395	1	2021	2021	NUM
iajs-2800	395	2	,	,	PUNCT
iajs-2800	395	3	6	6	NUM
iajs-2800	395	4	,	,	PUNCT
iajs-2800	395	5	8	8	NUM
iajs-2800	395	6	:	:	SYM
iajs-2800	395	7	8205–8220	8205–8220	NUM
iajs-2800	395	8	.	.	NOUN
iajs-2800	395	9	8	8	NUM
iajs-2800	395	10	.	.	X
iajs-2800	396	1	supharakonsakun	supharakonsakun	PROPN
iajs-2800	396	2	y.	y.	PROPN
iajs-2800	396	3	;	;	PUNCT
iajs-2800	396	4	bayesian	bayesian	NOUN
iajs-2800	396	5	approaches	approach	VERB
iajs-2800	396	6	for	for	ADP
iajs-2800	396	7	poisson	poisson	NOUN
iajs-2800	396	8	distribution	distribution	NOUN
iajs-2800	396	9	parameter	parameter	NOUN
iajs-2800	396	10	estimation	estimation	NOUN
iajs-2800	396	11	.	.	PUNCT
iajs-2800	397	1	emerging	emerge	VERB
iajs-2800	397	2	science	science	NOUN
iajs-2800	397	3	journal	journal	NOUN
iajs-2800	397	4	.	.	PUNCT
iajs-2800	398	1	2021	2021	NUM
iajs-2800	398	2	,	,	PUNCT
iajs-2800	398	3	5	5	NUM
iajs-2800	398	4	,	,	PUNCT
iajs-2800	398	5	5	5	NUM
iajs-2800	398	6	,	,	PUNCT
iajs-2800	398	7	issn	issn	NOUN
iajs-2800	398	8	:	:	PUNCT
iajs-2800	398	9	2610	2610	NUM
iajs-2800	398	10	-	-	SYM
iajs-2800	398	11	9182	9182	NUM
iajs-2800	398	12	.	.	PUNCT
iajs-2800	399	1	9	9	NUM
iajs-2800	399	2	.	.	X
iajs-2800	399	3	bickel	bickel	PROPN
iajs-2800	399	4	p.j	p.j	PROPN
iajs-2800	399	5	.	.	PUNCT
iajs-2800	399	6	;	;	PUNCT
iajs-2800	399	7	doksum	doksum	PROPN
iajs-2800	399	8	k.	k.	PROPN
iajs-2800	399	9	a.	a.	PROPN
iajs-2800	399	10	;	;	PUNCT
iajs-2800	399	11	mathematical	mathematical	ADJ
iajs-2800	399	12	statistics	statistic	NOUN
iajs-2800	399	13	:	:	PUNCT
iajs-2800	399	14	basic	basic	ADJ
iajs-2800	399	15	ideas	idea	NOUN
iajs-2800	399	16	and	and	CCONJ
iajs-2800	399	17	selected	select	VERB
iajs-2800	399	18	topics	topic	NOUN
iajs-2800	399	19	.	.	PUNCT
iajs-2800	400	1	holdenday	holdenday	PROPN
iajs-2800	400	2	,	,	PUNCT
iajs-2800	400	3	inc	inc	PROPN
iajs-2800	400	4	.	.	PROPN
iajs-2800	400	5	,	,	PUNCT
iajs-2800	400	6	san	san	PROPN
iajs-2800	400	7	francisco	francisco	PROPN
iajs-2800	400	8	.	.	PUNCT
iajs-2800	401	1	1977	1977	NUM
iajs-2800	401	2	.	.	PUNCT
iajs-2800	402	1	10	10	NUM
iajs-2800	402	2	.	.	PUNCT
iajs-2800	403	1	aijaz	aijaz	PROPN
iajs-2800	403	2	a.	a.	PROPN
iajs-2800	403	3	;	;	PUNCT
iajs-2800	403	4	qurat	qurat	PROPN
iajs-2800	403	5	ul	ul	PROPN
iajs-2800	403	6	a.	a.	PROPN
iajs-2800	403	7	s.	s.	PROPN
iajs-2800	403	8	;	;	PUNCT
iajs-2800	403	9	ahmad	ahmad	PROPN
iajs-2800	403	10	a.	a.	PROPN
iajs-2800	403	11	;	;	PUNCT
iajs-2800	403	12	tripathi	tripathi	PROPN
iajs-2800	403	13	r.	r.	PROPN
iajs-2800	403	14	;	;	PUNCT
iajs-2800	403	15	an	an	DET
iajs-2800	403	16	extension	extension	NOUN
iajs-2800	403	17	of	of	ADP
iajs-2800	403	18	erlang	erlang	NOUN
iajs-2800	403	19	distribution	distribution	NOUN
iajs-2800	403	20	with	with	ADP
iajs-2800	403	21	properties	property	NOUN
iajs-2800	403	22	having	have	VERB
iajs-2800	403	23	applications	application	NOUN
iajs-2800	403	24	in	in	ADP
iajs-2800	403	25	engineering	engineering	NOUN
iajs-2800	403	26	and	and	CCONJ
iajs-2800	403	27	medical	medical	ADJ
iajs-2800	403	28	-	-	PUNCT
iajs-2800	403	29	science	science	NOUN
iajs-2800	403	30	.	.	PUNCT
iajs-2800	404	1	int	int	NOUN
iajs-2800	404	2	.	.	PUNCT
iajs-2800	405	1	j.	j.	PROPN
iajs-2800	405	2	open	open	PROPN
iajs-2800	405	3	problems	problem	NOUN
iajs-2800	405	4	compt	compt	VERB
iajs-2800	405	5	.	.	PUNCT
iajs-2800	405	6	math	math	NOUN
iajs-2800	405	7	.	.	PUNCT
iajs-2800	406	1	2021	2021	NUM
iajs-2800	406	2	,	,	PUNCT
iajs-2800	406	3	14	14	NUM
iajs-2800	406	4	,	,	PUNCT
iajs-2800	406	5	1	1	NUM
iajs-2800	406	6	,	,	PUNCT
iajs-2800	406	7	print	print	NOUN
iajs-2800	406	8	issn	issn	PROPN
iajs-2800	406	9	:	:	PUNCT
iajs-2800	406	10	1998	1998	NUM
iajs-2800	406	11	-	-	SYM
iajs-2800	406	12	6262	6262	NUM
iajs-2800	406	13	.	.	PUNCT
iajs-2800	407	1	11	11	NUM
iajs-2800	407	2	.	.	X
iajs-2800	408	1	carolynne	carolynne	PROPN
iajs-2800	408	2	a.k	a.k	PROPN
iajs-2800	408	3	.	.	PROPN
iajs-2800	408	4	;	;	PUNCT
iajs-2800	408	5	gamma	gamma	NOUN
iajs-2800	408	6	and	and	CCONJ
iajs-2800	408	7	related	related	ADJ
iajs-2800	408	8	distributions	distribution	NOUN
iajs-2800	408	9	.	.	PUNCT
iajs-2800	409	1	a	a	DET
iajs-2800	409	2	thesis	thesis	NOUN
iajs-2800	409	3	submitted	submit	VERB
iajs-2800	409	4	to	to	ADP
iajs-2800	409	5	the	the	DET
iajs-2800	409	6	school	school	NOUN
iajs-2800	409	7	of	of	ADP
iajs-2800	409	8	mathematics	mathematic	NOUN
iajs-2800	409	9	,	,	PUNCT
iajs-2800	409	10	university	university	PROPN
iajs-2800	409	11	of	of	ADP
iajs-2800	409	12	nairobi	nairobi	PROPN
iajs-2800	409	13	in	in	ADP
iajs-2800	409	14	partial	partial	ADJ
iajs-2800	409	15	fulfillment	fulfillment	NOUN
iajs-2800	409	16	of	of	ADP
iajs-2800	409	17	the	the	DET
iajs-2800	409	18	requirements	requirement	NOUN
iajs-2800	409	19	for	for	ADP
iajs-2800	409	20	the	the	DET
iajs-2800	409	21	degree	degree	NOUN
iajs-2800	409	22	of	of	ADP
iajs-2800	409	23	master	master	NOUN
iajs-2800	409	24	of	of	ADP
iajs-2800	409	25	science	science	NOUN
iajs-2800	409	26	in	in	ADP
iajs-2800	409	27	statistics	statistic	NOUN
iajs-2800	409	28	.	.	PUNCT
iajs-2800	410	1	2013	2013	NUM
iajs-2800	410	2	.	.	PUNCT
iajs-2800	411	1	12	12	NUM
iajs-2800	411	2	.	.	PUNCT
iajs-2800	412	1	al	al	PROPN
iajs-2800	412	2	-	-	PUNCT
iajs-2800	412	3	noor	noor	PROPN
iajs-2800	412	4	n.h	n.h	PROPN
iajs-2800	412	5	.	.	PUNCT
iajs-2800	412	6	;	;	PUNCT
iajs-2800	412	7	alwan.s	alwan.s	X
iajs-2800	412	8	.	.	PUNCT
iajs-2800	413	1	s.	s.	PROPN
iajs-2800	413	2	;	;	PUNCT
iajs-2800	413	3	non	non	NOUN
iajs-2800	413	4	-	-	NOUN
iajs-2800	413	5	bayes	baye	NOUN
iajs-2800	413	6	,	,	PUNCT
iajs-2800	413	7	bayes	bayes	NOUN
iajs-2800	413	8	and	and	CCONJ
iajs-2800	413	9	empirical	empirical	ADJ
iajs-2800	413	10	bayes	bayes	NOUN
iajs-2800	413	11	estimators	estimator	NOUN
iajs-2800	413	12	for	for	ADP
iajs-2800	413	13	the	the	DET
iajs-2800	413	14	shape	shape	NOUN
iajs-2800	413	15	parameter	parameter	NOUN
iajs-2800	413	16	of	of	ADP
iajs-2800	413	17	lomax	lomax	PROPN
iajs-2800	413	18	distribution	distribution	NOUN
iajs-2800	413	19	.	.	PUNCT
iajs-2800	414	1	mathematical	mathematical	ADJ
iajs-2800	414	2	theory	theory	NOUN
iajs-2800	414	3	and	and	CCONJ
iajs-2800	414	4	modeling	modeling	NOUN
iajs-2800	414	5	.	.	PUNCT
iajs-2800	415	1	2015	2015	NUM
iajs-2800	415	2	,	,	PUNCT
iajs-2800	415	3	5	5	NUM
iajs-2800	415	4	,	,	PUNCT
iajs-2800	415	5	2	2	NUM
iajs-2800	415	6	:	:	PUNCT
iajs-2800	415	7	issn	issn	PROPN
iajs-2800	415	8	2224	2224	NUM
iajs-2800	415	9	-	-	SYM
iajs-2800	415	10	5804	5804	NUM
iajs-2800	415	11	(	(	PUNCT
iajs-2800	415	12	paper	paper	NOUN
iajs-2800	415	13	)	)	PUNCT
iajs-2800	415	14	.	.	PUNCT