id	sid	tid	token	lemma	pos
iajs-2563	1	1	ibn	ibn	PROPN
iajs-2563	1	2	al	al	PROPN
iajs-2563	1	3	-	-	PUNCT
iajs-2563	1	4	haitham	haitham	PROPN
iajs-2563	1	5	jour	jour	X
iajs-2563	1	6	.	.	PROPN
iajs-2563	1	7	for	for	ADP
iajs-2563	1	8	pure	pure	ADJ
iajs-2563	1	9	&	&	CCONJ
iajs-2563	1	10	appl	appl	PROPN
iajs-2563	1	11	.	.	PUNCT
iajs-2563	2	1	sci	sci	PROPN
iajs-2563	2	2	.	.	PROPN
iajs-2563	3	1	34	34	NUM
iajs-2563	3	2	(	(	PUNCT
iajs-2563	3	3	1	1	NUM
iajs-2563	3	4	)	)	PUNCT
iajs-2563	3	5	2021	2021	NUM
iajs-2563	3	6	125	125	NUM
iajs-2563	3	7	using	use	VERB
iajs-2563	3	8	entropy	entropy	NOUN
iajs-2563	3	9	and	and	CCONJ
iajs-2563	3	10	linear	linear	PROPN
iajs-2563	3	11	exponential	exponential	NOUN
iajs-2563	3	12	loos	loo	NOUN
iajs-2563	3	13	function	function	VERB
iajs-2563	3	14	estimators	estimator	NOUN
iajs-2563	3	15	the	the	DET
iajs-2563	3	16	parameter	parameter	NOUN
iajs-2563	3	17	and	and	CCONJ
iajs-2563	3	18	reliability	reliability	NOUN
iajs-2563	3	19	function	function	NOUN
iajs-2563	3	20	of	of	ADP
iajs-2563	3	21	inverse	inverse	NOUN
iajs-2563	3	22	rayleigh	rayleigh	PROPN
iajs-2563	3	23	distribution	distribution	NOUN
iajs-2563	3	24	masooma	masooma	PROPN
iajs-2563	3	25	ali	ali	PROPN
iajs-2563	3	26	abod	abod	PROPN
iajs-2563	3	27	hazim	hazim	PROPN
iajs-2563	3	28	mansoor	mansoor	PROPN
iajs-2563	3	29	gorgees	gorgees	PROPN
iajs-2563	3	30	department	department	PROPN
iajs-2563	3	31	of	of	ADP
iajs-2563	3	32	mathematics	mathematics	PROPN
iajs-2563	3	33	,	,	PUNCT
iajs-2563	3	34	college	college	NOUN
iajs-2563	3	35	of	of	ADP
iajs-2563	3	36	education	education	NOUN
iajs-2563	3	37	for	for	ADP
iajs-2563	3	38	pure	pure	ADJ
iajs-2563	3	39	science	science	NOUN
iajs-2563	3	40	ibn	ibn	PROPN
iajs-2563	3	41	al	al	PROPN
iajs-2563	3	42	-	-	PUNCT
iajs-2563	3	43	haitham	haitham	PROPN
iajs-2563	3	44	,	,	PUNCT
iajs-2563	3	45	university	university	NOUN
iajs-2563	3	46	of	of	ADP
iajs-2563	3	47	baghdad	baghdad	PROPN
iajs-2563	3	48	,	,	PUNCT
iajs-2563	3	49	baghdad	baghdad	PROPN
iajs-2563	3	50	,	,	PUNCT
iajs-2563	3	51	iraq	iraq	PROPN
iajs-2563	3	52	.	.	PUNCT
iajs-2563	4	1	masoomaaliabod@gmail.com	masoomaaliabod@gmail.com	X
iajs-2563	4	2	hazim5656@yahoo.com	hazim5656@yahoo.com	X
iajs-2563	5	1	abstract	abstract	ADJ
iajs-2563	5	2	this	this	DET
iajs-2563	5	3	paper	paper	NOUN
iajs-2563	5	4	is	be	AUX
iajs-2563	5	5	devoted	devote	VERB
iajs-2563	5	6	to	to	PART
iajs-2563	5	7	compare	compare	VERB
iajs-2563	5	8	the	the	DET
iajs-2563	5	9	performance	performance	NOUN
iajs-2563	5	10	of	of	ADP
iajs-2563	5	11	non	non	ADJ
iajs-2563	5	12	-	-	ADJ
iajs-2563	5	13	bayesian	bayesian	ADJ
iajs-2563	5	14	estimators	estimator	NOUN
iajs-2563	5	15	represented	represent	VERB
iajs-2563	5	16	by	by	ADP
iajs-2563	5	17	the	the	DET
iajs-2563	5	18	maximum	maximum	ADJ
iajs-2563	5	19	likelihood	likelihood	NOUN
iajs-2563	5	20	estimator	estimator	NOUN
iajs-2563	5	21	of	of	ADP
iajs-2563	5	22	the	the	DET
iajs-2563	5	23	scale	scale	NOUN
iajs-2563	5	24	parameter	parameter	NOUN
iajs-2563	5	25	and	and	CCONJ
iajs-2563	5	26	reliability	reliability	NOUN
iajs-2563	5	27	function	function	NOUN
iajs-2563	5	28	of	of	ADP
iajs-2563	5	29	inverse	inverse	NOUN
iajs-2563	5	30	rayleigh	rayleigh	NOUN
iajs-2563	5	31	distribution	distribution	NOUN
iajs-2563	5	32	with	with	ADP
iajs-2563	5	33	bayesian	bayesian	NOUN
iajs-2563	5	34	estimators	estimator	NOUN
iajs-2563	5	35	obtained	obtain	VERB
iajs-2563	5	36	under	under	ADP
iajs-2563	5	37	two	two	NUM
iajs-2563	5	38	types	type	NOUN
iajs-2563	5	39	of	of	ADP
iajs-2563	5	40	loss	loss	NOUN
iajs-2563	5	41	function	function	NOUN
iajs-2563	5	42	specifically	specifically	ADV
iajs-2563	5	43	;	;	PUNCT
iajs-2563	5	44	the	the	DET
iajs-2563	5	45	linear	linear	ADJ
iajs-2563	5	46	,	,	PUNCT
iajs-2563	5	47	exponential	exponential	ADJ
iajs-2563	5	48	(	(	PUNCT
iajs-2563	5	49	linex	linex	ADJ
iajs-2563	5	50	)	)	PUNCT
iajs-2563	5	51	loss	loss	NOUN
iajs-2563	5	52	function	function	NOUN
iajs-2563	5	53	and	and	CCONJ
iajs-2563	5	54	entropy	entropy	VERB
iajs-2563	5	55	loss	loss	NOUN
iajs-2563	5	56	function	function	NOUN
iajs-2563	5	57	,	,	PUNCT
iajs-2563	5	58	taking	take	VERB
iajs-2563	5	59	into	into	ADP
iajs-2563	5	60	consideration	consideration	NOUN
iajs-2563	5	61	the	the	DET
iajs-2563	5	62	informative	informative	ADJ
iajs-2563	5	63	and	and	CCONJ
iajs-2563	5	64	non	non	ADJ
iajs-2563	5	65	-	-	ADJ
iajs-2563	5	66	informative	informative	ADJ
iajs-2563	5	67	priors	prior	NOUN
iajs-2563	5	68	.	.	PUNCT
iajs-2563	6	1	the	the	DET
iajs-2563	6	2	performance	performance	NOUN
iajs-2563	6	3	of	of	ADP
iajs-2563	6	4	such	such	ADJ
iajs-2563	6	5	estimators	estimator	NOUN
iajs-2563	6	6	assessed	assess	VERB
iajs-2563	6	7	on	on	ADP
iajs-2563	6	8	the	the	DET
iajs-2563	6	9	basis	basis	NOUN
iajs-2563	6	10	of	of	ADP
iajs-2563	6	11	mean	mean	ADJ
iajs-2563	6	12	square	square	ADJ
iajs-2563	6	13	error	error	NOUN
iajs-2563	6	14	(	(	PUNCT
iajs-2563	6	15	mse	mse	NOUN
iajs-2563	6	16	)	)	PUNCT
iajs-2563	6	17	criterion	criterion	NOUN
iajs-2563	6	18	.	.	PUNCT
iajs-2563	7	1	the	the	DET
iajs-2563	7	2	monte	monte	PROPN
iajs-2563	7	3	carlo	carlo	PROPN
iajs-2563	7	4	simulation	simulation	NOUN
iajs-2563	7	5	experiments	experiment	NOUN
iajs-2563	7	6	are	be	AUX
iajs-2563	7	7	conducted	conduct	VERB
iajs-2563	7	8	in	in	ADP
iajs-2563	7	9	order	order	NOUN
iajs-2563	7	10	to	to	PART
iajs-2563	7	11	obtain	obtain	VERB
iajs-2563	7	12	the	the	DET
iajs-2563	7	13	required	require	VERB
iajs-2563	7	14	results	result	NOUN
iajs-2563	7	15	.	.	PUNCT
iajs-2563	8	1	keyword	keyword	NOUN
iajs-2563	8	2	:	:	PUNCT
iajs-2563	8	3	inverse	inverse	NOUN
iajs-2563	8	4	rayleigh	rayleigh	NOUN
iajs-2563	8	5	distribution	distribution	NOUN
iajs-2563	8	6	,	,	PUNCT
iajs-2563	8	7	entropy	entropy	VERB
iajs-2563	8	8	loss	loss	NOUN
iajs-2563	8	9	function	function	NOUN
iajs-2563	8	10	,	,	PUNCT
iajs-2563	8	11	linex	linex	ADV
iajs-2563	8	12	loss	loss	NOUN
iajs-2563	8	13	function	function	NOUN
iajs-2563	8	14	,	,	PUNCT
iajs-2563	8	15	prior	prior	ADJ
iajs-2563	8	16	information	information	NOUN
iajs-2563	8	17	.	.	PUNCT
iajs-2563	9	1	1	1	X
iajs-2563	9	2	.	.	X
iajs-2563	9	3	introduction	introduction	NOUN
iajs-2563	9	4	inverse	inverse	NOUN
iajs-2563	9	5	rayleigh	rayleigh	NOUN
iajs-2563	9	6	distribution	distribution	NOUN
iajs-2563	9	7	(	(	PUNCT
iajs-2563	9	8	ird	ird	PROPN
iajs-2563	9	9	)	)	PUNCT
iajs-2563	9	10	is	be	AUX
iajs-2563	9	11	one	one	NUM
iajs-2563	9	12	of	of	ADP
iajs-2563	9	13	the	the	DET
iajs-2563	9	14	comprehensive	comprehensive	ADJ
iajs-2563	9	15	and	and	CCONJ
iajs-2563	9	16	relevant	relevant	ADJ
iajs-2563	9	17	lifetime	lifetime	NOUN
iajs-2563	9	18	model	model	NOUN
iajs-2563	9	19	,	,	PUNCT
iajs-2563	9	20	and	and	CCONJ
iajs-2563	9	21	its	its	PRON
iajs-2563	9	22	applications	application	NOUN
iajs-2563	9	23	are	be	AUX
iajs-2563	9	24	in	in	ADP
iajs-2563	9	25	reliability	reliability	NOUN
iajs-2563	9	26	and	and	CCONJ
iajs-2563	9	27	survival	survival	NOUN
iajs-2563	9	28	data	datum	NOUN
iajs-2563	9	29	sets	set	VERB
iajs-2563	9	30	.a	.a	ADJ
iajs-2563	9	31	numerous	numerous	ADJ
iajs-2563	9	32	work	work	NOUN
iajs-2563	9	33	has	have	AUX
iajs-2563	9	34	been	be	AUX
iajs-2563	9	35	done	do	VERB
iajs-2563	9	36	in	in	ADP
iajs-2563	9	37	the	the	DET
iajs-2563	9	38	literature	literature	NOUN
iajs-2563	9	39	concerning	concern	VERB
iajs-2563	9	40	ird	ird	PROPN
iajs-2563	9	41	.	.	PUNCT
iajs-2563	10	1	the	the	DET
iajs-2563	10	2	distribution	distribution	NOUN
iajs-2563	10	3	was	be	AUX
iajs-2563	10	4	supported	support	VERB
iajs-2563	10	5	by	by	ADP
iajs-2563	10	6	voda	voda	PROPN
iajs-2563	10	7	in	in	ADP
iajs-2563	10	8	1972,who	1972,who	NUM
iajs-2563	10	9	considered	consider	VERB
iajs-2563	10	10	its	its	PRON
iajs-2563	10	11	properties	property	NOUN
iajs-2563	10	12	and	and	CCONJ
iajs-2563	10	13	consider	consider	VERB
iajs-2563	10	14	mle	mle	PROPN
iajs-2563	10	15	estimator	estimator	NOUN
iajs-2563	10	16	for	for	SCONJ
iajs-2563	10	17	estimate	estimate	VERB
iajs-2563	10	18	its	its	PRON
iajs-2563	10	19	scale	scale	NOUN
iajs-2563	10	20	parameter	parameter	NOUN
iajs-2563	10	21	[	[	X
iajs-2563	10	22	1	1	NUM
iajs-2563	10	23	]	]	PUNCT
iajs-2563	10	24	.	.	PUNCT
iajs-2563	11	1	next	next	ADV
iajs-2563	11	2	,	,	PUNCT
iajs-2563	11	3	gharraph	gharraph	NOUN
iajs-2563	11	4	in	in	ADP
iajs-2563	11	5	1993	1993	NUM
iajs-2563	11	6	developed	develop	VERB
iajs-2563	11	7	closed	closed	ADJ
iajs-2563	11	8	form	form	NOUN
iajs-2563	11	9	expressions	expression	NOUN
iajs-2563	11	10	for	for	ADP
iajs-2563	11	11	the	the	DET
iajs-2563	11	12	mean	mean	ADJ
iajs-2563	11	13	,	,	PUNCT
iajs-2563	11	14	mode	mode	NOUN
iajs-2563	11	15	,	,	PUNCT
iajs-2563	11	16	median	median	NOUN
iajs-2563	11	17	,	,	PUNCT
iajs-2563	11	18	harmonic	harmonic	ADJ
iajs-2563	11	19	mean	mean	NOUN
iajs-2563	11	20	and	and	CCONJ
iajs-2563	11	21	geometric	geometric	ADJ
iajs-2563	11	22	mean	mean	NOUN
iajs-2563	11	23	of	of	ADP
iajs-2563	11	24	ird	ird	PROPN
iajs-2563	12	1	[	[	X
iajs-2563	12	2	2	2	NUM
iajs-2563	12	3	]	]	PUNCT
iajs-2563	12	4	.	.	PUNCT
iajs-2563	13	1	furthermore	furthermore	ADV
iajs-2563	13	2	,	,	PUNCT
iajs-2563	13	3	soliman	soliman	NOUN
iajs-2563	13	4	,	,	PUNCT
iajs-2563	13	5	amin	amin	PROPN
iajs-2563	13	6	,	,	PUNCT
iajs-2563	13	7	and	and	CCONJ
iajs-2563	13	8	abd	abd	PROPN
iajs-2563	13	9	-	-	PUNCT
iajs-2563	13	10	ei	ei	PROPN
iajs-2563	13	11	aziz	aziz	PROPN
iajs-2563	13	12	in	in	ADP
iajs-2563	13	13	2010	2010	NUM
iajs-2563	13	14	estimated	estimate	VERB
iajs-2563	13	15	the	the	DET
iajs-2563	13	16	parameter	parameter	NOUN
iajs-2563	13	17	using	use	VERB
iajs-2563	13	18	different	different	ADJ
iajs-2563	13	19	traditional	traditional	ADJ
iajs-2563	13	20	and	and	CCONJ
iajs-2563	13	21	bayesian	bayesian	NOUN
iajs-2563	13	22	estimation	estimation	NOUN
iajs-2563	13	23	's	's	PART
iajs-2563	13	24	methods	method	NOUN
iajs-2563	13	25	[	[	X
iajs-2563	13	26	3	3	NUM
iajs-2563	13	27	]	]	PUNCT
iajs-2563	13	28	.	.	PUNCT
iajs-2563	14	1	the	the	DET
iajs-2563	14	2	probability	probability	NOUN
iajs-2563	14	3	density	density	NOUN
iajs-2563	14	4	function	function	NOUN
iajs-2563	14	5	of	of	ADP
iajs-2563	14	6	inverse	inverse	NOUN
iajs-2563	14	7	rayleigh	rayleigh	NOUN
iajs-2563	14	8	distribution	distribution	NOUN
iajs-2563	14	9	is	be	AUX
iajs-2563	14	10	defined	define	VERB
iajs-2563	14	11	as	as	SCONJ
iajs-2563	14	12	follows	follow	VERB
iajs-2563	14	13	[	[	X
iajs-2563	14	14	4	4	NUM
iajs-2563	14	15	]	]	PUNCT
iajs-2563	14	16	:	:	PUNCT
iajs-2563	14	17	ibn	ibn	PROPN
iajs-2563	14	18	al	al	PROPN
iajs-2563	14	19	haitham	haitham	PROPN
iajs-2563	14	20	journal	journal	PROPN
iajs-2563	14	21	for	for	ADP
iajs-2563	14	22	pure	pure	ADJ
iajs-2563	14	23	and	and	CCONJ
iajs-2563	14	24	applied	apply	VERB
iajs-2563	14	25	science	science	NOUN
iajs-2563	14	26	journal	journal	PROPN
iajs-2563	14	27	homepage	homepage	NOUN
iajs-2563	14	28	:	:	PUNCT
iajs-2563	14	29	http://jih.uobaghdad.edu.iq/index.php/j/index	http://jih.uobaghdad.edu.iq/index.php/j/index	NOUN
iajs-2563	14	30	doi	doi	NOUN
iajs-2563	14	31	:	:	PUNCT
iajs-2563	14	32	10.30526/34.1.2563	10.30526/34.1.2563	PROPN
iajs-2563	14	33	article	article	NOUN
iajs-2563	14	34	history	history	NOUN
iajs-2563	14	35	:	:	PUNCT
iajs-2563	14	36	received	receive	VERB
iajs-2563	14	37	12,october,2019	12,october,2019	NUM
iajs-2563	14	38	,	,	PUNCT
iajs-2563	14	39	accepted8,january,2020	accepted8,january,2020	PROPN
iajs-2563	14	40	,	,	PUNCT
iajs-2563	14	41	published	publish	VERB
iajs-2563	14	42	in	in	ADP
iajs-2563	14	43	january	january	PROPN
iajs-2563	14	44	2021	2021	NUM
iajs-2563	15	1	file:///c:/users/المجلة/downloads/masoomaaliabod@gmail.com	file:///c:/users/المجلة/downloads/masoomaaliabod@gmail.com	PROPN
iajs-2563	15	2	file:///c:/users/المجلة/downloads/hazim5656@yahoo.com	file:///c:/users/المجلة/downloads/hazim5656@yahoo.com	PROPN
iajs-2563	15	3	126	126	NUM
iajs-2563	16	1	ibn	ibn	PROPN
iajs-2563	16	2	al	al	PROPN
iajs-2563	16	3	-	-	PUNCT
iajs-2563	16	4	haitham	haitham	PROPN
iajs-2563	16	5	jour	jour	X
iajs-2563	16	6	.	.	PROPN
iajs-2563	16	7	for	for	ADP
iajs-2563	16	8	pure	pure	ADJ
iajs-2563	16	9	&	&	CCONJ
iajs-2563	16	10	appl	appl	PROPN
iajs-2563	16	11	.	.	PUNCT
iajs-2563	17	1	sci	sci	PROPN
iajs-2563	17	2	.	.	PROPN
iajs-2563	18	1	34	34	NUM
iajs-2563	18	2	(	(	PUNCT
iajs-2563	18	3	1	1	NUM
iajs-2563	18	4	)	)	PUNCT
iajs-2563	18	5	2021	2021	NUM
iajs-2563	18	6	𝑓(𝑡	𝑓(𝑡	PROPN
iajs-2563	18	7	,	,	PUNCT
iajs-2563	18	8	𝜃	𝜃	NOUN
iajs-2563	18	9	)	)	PUNCT
iajs-2563	18	10	=	=	SYM
iajs-2563	18	11	2𝜃	2𝜃	NUM
iajs-2563	18	12	𝑡3	𝑡3	NOUN
iajs-2563	18	13	exp	exp	NOUN
iajs-2563	18	14	(	(	PUNCT
iajs-2563	18	15	−	−	PROPN
iajs-2563	18	16	𝜃	𝜃	SYM
iajs-2563	18	17	𝑡2	𝑡2	PROPN
iajs-2563	18	18	)	)	PUNCT
iajs-2563	18	19	,	,	PUNCT
iajs-2563	18	20	𝑡	𝑡	X
iajs-2563	18	21	>	>	X
iajs-2563	18	22	0	0	NUM
iajs-2563	18	23	,	,	PUNCT
iajs-2563	18	24	𝜃	𝜃	X
iajs-2563	18	25	>	>	X
iajs-2563	18	26	0	0	PUNCT
iajs-2563	19	1	(	(	PUNCT
iajs-2563	19	2	1	1	NUM
iajs-2563	19	3	)	)	PUNCT
iajs-2563	19	4	where	where	SCONJ
iajs-2563	19	5	(	(	PUNCT
iajs-2563	19	6	t	t	NOUN
iajs-2563	19	7	)	)	PUNCT
iajs-2563	19	8	is	be	AUX
iajs-2563	19	9	a	a	DET
iajs-2563	19	10	random	random	ADJ
iajs-2563	19	11	variable	variable	NOUN
iajs-2563	19	12	that	that	PRON
iajs-2563	19	13	follows	follow	VERB
iajs-2563	19	14	ird	ird	PROPN
iajs-2563	19	15	and	and	CCONJ
iajs-2563	19	16	𝜃	𝜃	NOUN
iajs-2563	19	17	is	be	AUX
iajs-2563	19	18	the	the	DET
iajs-2563	19	19	scale	scale	NOUN
iajs-2563	19	20	parameter	parameter	NOUN
iajs-2563	19	21	.	.	PUNCT
iajs-2563	20	1	the	the	DET
iajs-2563	20	2	cumulative	cumulative	ADJ
iajs-2563	20	3	distribution	distribution	NOUN
iajs-2563	20	4	function	function	NOUN
iajs-2563	20	5	is	be	AUX
iajs-2563	20	6	given	give	VERB
iajs-2563	20	7	by	by	ADP
iajs-2563	20	8	[	[	X
iajs-2563	20	9	4	4	NUM
iajs-2563	20	10	]	]	PUNCT
iajs-2563	20	11	:	:	PUNCT
iajs-2563	20	12	𝐹(𝑡	𝐹(𝑡	NUM
iajs-2563	20	13	,	,	PUNCT
iajs-2563	20	14	𝜃	𝜃	NOUN
iajs-2563	20	15	)	)	PUNCT
iajs-2563	20	16	=	=	SYM
iajs-2563	20	17	exp	exp	NOUN
iajs-2563	20	18	(	(	PUNCT
iajs-2563	20	19	−	−	PROPN
iajs-2563	20	20	𝜃	𝜃	SYM
iajs-2563	20	21	𝑡2	𝑡2	PROPN
iajs-2563	20	22	)	)	PUNCT
iajs-2563	20	23	,	,	PUNCT
iajs-2563	20	24	𝑡	𝑡	X
iajs-2563	20	25	>	>	X
iajs-2563	20	26	0	0	NUM
iajs-2563	20	27	,	,	PUNCT
iajs-2563	20	28	𝜃	𝜃	X
iajs-2563	20	29	>	>	X
iajs-2563	20	30	0	0	PUNCT
iajs-2563	21	1	(	(	PUNCT
iajs-2563	21	2	2	2	X
iajs-2563	21	3	)	)	PUNCT
iajs-2563	21	4	the	the	DET
iajs-2563	21	5	reliability	reliability	NOUN
iajs-2563	21	6	function	function	NOUN
iajs-2563	21	7	of	of	ADP
iajs-2563	21	8	ird	ird	PROPN
iajs-2563	21	9	is	be	AUX
iajs-2563	21	10	therefore	therefore	ADV
iajs-2563	21	11	defined	define	VERB
iajs-2563	21	12	as	as	ADP
iajs-2563	21	13	[	[	X
iajs-2563	21	14	4	4	NUM
iajs-2563	21	15	]	]	PUNCT
iajs-2563	21	16	:	:	PUNCT
iajs-2563	21	17	𝑅(𝑡	𝑅(𝑡	NUM
iajs-2563	21	18	,	,	PUNCT
iajs-2563	21	19	𝜃	𝜃	NOUN
iajs-2563	21	20	)	)	PUNCT
iajs-2563	21	21	=	=	SYM
iajs-2563	22	1	1	1	NUM
iajs-2563	22	2	−	−	NOUN
iajs-2563	22	3	𝐹(𝑡	𝐹(𝑡	NUM
iajs-2563	22	4	,	,	PUNCT
iajs-2563	22	5	𝜃	𝜃	NOUN
iajs-2563	22	6	)	)	PUNCT
iajs-2563	22	7	=	=	SYM
iajs-2563	22	8	1	1	NUM
iajs-2563	22	9	−	−	NOUN
iajs-2563	22	10	exp	exp	NOUN
iajs-2563	22	11	(	(	PUNCT
iajs-2563	22	12	−	−	PROPN
iajs-2563	22	13	𝜃	𝜃	SYM
iajs-2563	22	14	𝑡2	𝑡2	PROPN
iajs-2563	22	15	)	)	PUNCT
iajs-2563	22	16	,	,	PUNCT
iajs-2563	22	17	𝑡	𝑡	X
iajs-2563	22	18	>	>	X
iajs-2563	22	19	0	0	NUM
iajs-2563	22	20	,	,	PUNCT
iajs-2563	22	21	𝜃	𝜃	X
iajs-2563	22	22	>	>	X
iajs-2563	22	23	0	0	PUNCT
iajs-2563	23	1	(	(	PUNCT
iajs-2563	23	2	3	3	X
iajs-2563	23	3	)	)	PUNCT
iajs-2563	23	4	it	it	PRON
iajs-2563	23	5	is	be	AUX
iajs-2563	23	6	worth	worth	ADJ
iajs-2563	23	7	mentioning	mention	VERB
iajs-2563	23	8	here	here	ADV
iajs-2563	23	9	that	that	SCONJ
iajs-2563	23	10	the	the	DET
iajs-2563	23	11	variance	variance	NOUN
iajs-2563	23	12	and	and	CCONJ
iajs-2563	23	13	higher	high	ADJ
iajs-2563	23	14	order	order	NOUN
iajs-2563	23	15	moments	moment	NOUN
iajs-2563	23	16	not	not	PART
iajs-2563	23	17	exists	exist	VERB
iajs-2563	23	18	in	in	ADP
iajs-2563	23	19	this	this	DET
iajs-2563	23	20	distribution	distribution	NOUN
iajs-2563	23	21	.	.	PUNCT
iajs-2563	24	1	in	in	ADP
iajs-2563	24	2	this	this	DET
iajs-2563	24	3	section	section	NOUN
iajs-2563	24	4	,	,	PUNCT
iajs-2563	24	5	maximum	maximum	ADJ
iajs-2563	24	6	likelihood	likelihood	NOUN
iajs-2563	24	7	estimators	estimator	NOUN
iajs-2563	24	8	,	,	PUNCT
iajs-2563	24	9	posterior	posterior	ADJ
iajs-2563	24	10	density	density	NOUN
iajs-2563	24	11	of	of	ADP
iajs-2563	24	12	the	the	DET
iajs-2563	24	13	inverse	inverse	NOUN
iajs-2563	24	14	rayleigh	rayleigh	PROPN
iajs-2563	24	15	parameter	parameter	NOUN
iajs-2563	24	16	based	base	VERB
iajs-2563	24	17	on	on	ADP
iajs-2563	24	18	(	(	PUNCT
iajs-2563	24	19	jeffrey	jeffrey	PROPN
iajs-2563	24	20	's	's	PART
iajs-2563	24	21	prior	prior	ADJ
iajs-2563	24	22	information	information	NOUN
iajs-2563	24	23	,	,	PUNCT
iajs-2563	24	24	exponential	exponential	ADJ
iajs-2563	24	25	prior	prior	ADJ
iajs-2563	24	26	distribution	distribution	NOUN
iajs-2563	24	27	)	)	PUNCT
iajs-2563	24	28	and	and	CCONJ
iajs-2563	24	29	types	type	NOUN
iajs-2563	24	30	of	of	ADP
iajs-2563	24	31	loss	loss	NOUN
iajs-2563	24	32	functions	function	NOUN
iajs-2563	24	33	(	(	PUNCT
iajs-2563	24	34	entropy	entropy	VERB
iajs-2563	24	35	loss	loss	NOUN
iajs-2563	24	36	function	function	NOUN
iajs-2563	24	37	,	,	PUNCT
iajs-2563	24	38	linear	linear	ADJ
iajs-2563	24	39	exponential	exponential	ADJ
iajs-2563	24	40	loss	loss	NOUN
iajs-2563	24	41	function	function	NOUN
iajs-2563	24	42	)	)	PUNCT
iajs-2563	24	43	will	will	AUX
iajs-2563	24	44	be	be	AUX
iajs-2563	24	45	considered	consider	VERB
iajs-2563	24	46	.	.	PUNCT
iajs-2563	25	1	2	2	X
iajs-2563	25	2	.	.	X
iajs-2563	25	3	maximum	maximum	ADJ
iajs-2563	25	4	likelihood	likelihood	NOUN
iajs-2563	25	5	estimators	estimator	NOUN
iajs-2563	25	6	let	let	VERB
iajs-2563	25	7	𝑡1,𝑡2,	𝑡1,𝑡2,	ADJ
iajs-2563	25	8	…	…	PUNCT
iajs-2563	25	9	…	…	PUNCT
iajs-2563	25	10	…	…	PUNCT
iajs-2563	25	11	,𝑡𝑛	,𝑡𝑛	PUNCT
iajs-2563	25	12	be	be	AUX
iajs-2563	25	13	random	random	ADJ
iajs-2563	25	14	samples	sample	NOUN
iajs-2563	25	15	drawn	draw	VERB
iajs-2563	25	16	from	from	ADP
iajs-2563	25	17	the	the	DET
iajs-2563	25	18	density	density	NOUN
iajs-2563	25	19	given	give	VERB
iajs-2563	25	20	in	in	ADP
iajs-2563	25	21	equation	equation	NOUN
iajs-2563	25	22	(	(	PUNCT
iajs-2563	25	23	1	1	NUM
iajs-2563	25	24	)	)	PUNCT
iajs-2563	25	25	,	,	PUNCT
iajs-2563	25	26	then	then	ADV
iajs-2563	25	27	the	the	DET
iajs-2563	25	28	likelihood	likelihood	NOUN
iajs-2563	25	29	function	function	NOUN
iajs-2563	25	30	is	be	AUX
iajs-2563	25	31	defined	define	VERB
iajs-2563	25	32	as	as	ADP
iajs-2563	25	33	𝐿(𝑡|𝜃	𝐿(𝑡|𝜃	NOUN
iajs-2563	25	34	)	)	PUNCT
iajs-2563	25	35	=	=	SYM
iajs-2563	25	36	∏	∏	X
iajs-2563	25	37	𝑓(𝑛	𝑓(𝑛	X
iajs-2563	25	38	𝑖=1	𝑖=1	PROPN
iajs-2563	25	39	𝑡𝑖	𝑡𝑖	NOUN
iajs-2563	25	40	,	,	PUNCT
iajs-2563	25	41	𝜃	𝜃	NOUN
iajs-2563	25	42	)	)	PUNCT
iajs-2563	25	43	=	=	PUNCT
iajs-2563	26	1	2𝑛𝜃𝑛	2𝑛𝜃𝑛	NUM
iajs-2563	26	2	∏	∏	NUM
iajs-2563	26	3	1	1	NUM
iajs-2563	26	4	𝑡𝑖	𝑡𝑖	NOUN
iajs-2563	26	5	3	3	NUM
iajs-2563	26	6	𝑛	𝑛	PRON
iajs-2563	26	7	𝑖=1	𝑖=1	PUNCT
iajs-2563	26	8	𝑒	𝑒	PROPN
iajs-2563	27	1	[	[	X
iajs-2563	27	2	−𝜃	−𝜃	NOUN
iajs-2563	27	3	∑	∑	PROPN
iajs-2563	27	4	1	1	NUM
iajs-2563	27	5	𝑡𝑖	𝑡𝑖	NOUN
iajs-2563	27	6	,	,	PUNCT
iajs-2563	27	7	2	2	NUM
iajs-2563	27	8	]	]	SYM
iajs-2563	27	9	𝑛	𝑛	PROPN
iajs-2563	27	10	𝑖	𝑖	SYM
iajs-2563	27	11	(	(	PUNCT
iajs-2563	27	12	4	4	X
iajs-2563	27	13	)	)	PUNCT
iajs-2563	27	14	taking	take	VERB
iajs-2563	27	15	the	the	DET
iajs-2563	27	16	natural	natural	ADJ
iajs-2563	27	17	logarithm	logarithm	NOUN
iajs-2563	27	18	for	for	ADP
iajs-2563	27	19	the	the	DET
iajs-2563	27	20	likelihood	likelihood	NOUN
iajs-2563	27	21	function	function	NOUN
iajs-2563	27	22	,	,	PUNCT
iajs-2563	27	23	we	we	PRON
iajs-2563	27	24	get	get	VERB
iajs-2563	27	25	ln	ln	ADJ
iajs-2563	27	26	𝐿	𝐿	PROPN
iajs-2563	27	27	(	(	PUNCT
iajs-2563	27	28	𝑡|𝜃	𝑡|𝜃	PUNCT
iajs-2563	27	29	)	)	PUNCT
iajs-2563	27	30	=	=	SYM
iajs-2563	27	31	𝑛𝑙𝑛2	𝑛𝑙𝑛2	NOUN
iajs-2563	27	32	+	+	CCONJ
iajs-2563	27	33	𝑛𝑙𝑛𝜃	𝑛𝑙𝑛𝜃	ADJ
iajs-2563	27	34	+	+	CCONJ
iajs-2563	27	35	∑	∑	PROPN
iajs-2563	27	36	𝑙𝑛	𝑙𝑛	NOUN
iajs-2563	27	37	1	1	NUM
iajs-2563	27	38	𝑡𝑖	𝑡𝑖	NOUN
iajs-2563	27	39	3	3	NUM
iajs-2563	27	40	𝑛	𝑛	PRON
iajs-2563	27	41	𝑖=1	𝑖=1	PROPN
iajs-2563	28	1	−	−	PROPN
iajs-2563	28	2	𝜃	𝜃	NOUN
iajs-2563	28	3	∑	∑	PROPN
iajs-2563	28	4	1	1	NUM
iajs-2563	28	5	𝑡𝑖	𝑡𝑖	PART
iajs-2563	28	6	2	2	NUM
iajs-2563	28	7	𝑛	𝑛	PRON
iajs-2563	28	8	𝑖=1	𝑖=1	PUNCT
iajs-2563	28	9	by	by	ADP
iajs-2563	28	10	differentiating	differentiate	VERB
iajs-2563	28	11	the	the	DET
iajs-2563	28	12	log	log	NOUN
iajs-2563	28	13	likelihood	likelihood	NOUN
iajs-2563	28	14	function	function	NOUN
iajs-2563	28	15	with	with	ADP
iajs-2563	28	16	respect	respect	NOUN
iajs-2563	28	17	to	to	ADP
iajs-2563	28	18	𝜃	𝜃	NOUN
iajs-2563	28	19	and	and	CCONJ
iajs-2563	28	20	then	then	ADV
iajs-2563	28	21	equating	equate	VERB
iajs-2563	28	22	the	the	DET
iajs-2563	28	23	resultant	resultant	NOUN
iajs-2563	28	24	derivative	derivative	NOUN
iajs-2563	28	25	to	to	ADP
iajs-2563	28	26	zero	zero	NUM
iajs-2563	28	27	,	,	PUNCT
iajs-2563	28	28	we	we	PRON
iajs-2563	28	29	get	get	VERB
iajs-2563	28	30	𝜕𝑙𝑛𝐿(𝑡|𝜃	𝜕𝑙𝑛𝐿(𝑡|𝜃	NOUN
iajs-2563	28	31	)	)	PUNCT
iajs-2563	28	32	𝜕𝜃	𝜕𝜃	NOUN
iajs-2563	29	1	=	=	SYM
iajs-2563	29	2	𝑛	𝑛	PRON
iajs-2563	29	3	𝜃	𝜃	NOUN
iajs-2563	29	4	−	−	NOUN
iajs-2563	29	5	∑	∑	SYM
iajs-2563	29	6	1	1	NUM
iajs-2563	29	7	𝑡𝑖	𝑡𝑖	PART
iajs-2563	29	8	2	2	NUM
iajs-2563	29	9	𝑛	𝑛	PRON
iajs-2563	29	10	𝑖=1	𝑖=1	PUNCT
iajs-2563	29	11	=	=	SYM
iajs-2563	29	12	0	0	PUNCT
iajs-2563	30	1	hence	hence	ADV
iajs-2563	30	2	,	,	PUNCT
iajs-2563	30	3	the	the	DET
iajs-2563	30	4	mle	mle	PROPN
iajs-2563	30	5	for	for	ADP
iajs-2563	30	6	𝜃	𝜃	PRON
iajs-2563	30	7	denoted	denote	VERB
iajs-2563	30	8	by	by	ADP
iajs-2563	30	9	𝜃𝑀𝐿𝐸	𝜃𝑀𝐿𝐸	NOUN
iajs-2563	30	10	is	be	AUX
iajs-2563	30	11	𝜃𝑀𝐿𝐸	𝜃𝑀𝐿𝐸	NOUN
iajs-2563	30	12	=	=	SYM
iajs-2563	31	1	𝑛	𝑛	PRON
iajs-2563	31	2	∑	∑	SYM
iajs-2563	31	3	1	1	NUM
iajs-2563	31	4	𝑡𝑖	𝑡𝑖	PART
iajs-2563	31	5	2	2	NUM
iajs-2563	31	6	𝑛	𝑛	PRON
iajs-2563	31	7	𝑖=1	𝑖=1	PUNCT
iajs-2563	31	8	=	=	SYM
iajs-2563	31	9	𝑛	𝑛	PRON
iajs-2563	31	10	𝑇	𝑇	PROPN
iajs-2563	31	11	(	(	PUNCT
iajs-2563	31	12	5	5	NUM
iajs-2563	31	13	)	)	PUNCT
iajs-2563	31	14	where	where	SCONJ
iajs-2563	31	15	𝑇	𝑇	PROPN
iajs-2563	31	16	=	=	SYM
iajs-2563	31	17	∑	∑	PROPN
iajs-2563	31	18	1	1	NUM
iajs-2563	31	19	𝑡𝑖	𝑡𝑖	PART
iajs-2563	31	20	2	2	NUM
iajs-2563	31	21	𝑛	𝑛	PRON
iajs-2563	31	22	𝑖=1	𝑖=1	PROPN
iajs-2563	31	23	3	3	X
iajs-2563	31	24	.	.	X
iajs-2563	31	25	posterior	posterior	ADJ
iajs-2563	31	26	density	density	NOUN
iajs-2563	31	27	of	of	ADP
iajs-2563	31	28	inverse	inverse	NOUN
iajs-2563	31	29	rayleigh	rayleigh	PROPN
iajs-2563	31	30	parameter	parameter	NOUN
iajs-2563	31	31	based	base	VERB
iajs-2563	31	32	on	on	ADP
iajs-2563	31	33	jeffrey	jeffrey	PROPN
iajs-2563	31	34	's	's	PART
iajs-2563	31	35	prior	prior	ADJ
iajs-2563	31	36	information	information	NOUN
iajs-2563	31	37	assume	assume	VERB
iajs-2563	31	38	that	that	SCONJ
iajs-2563	31	39	θ	θ	PROPN
iajs-2563	31	40	has	have	VERB
iajs-2563	31	41	a	a	DET
iajs-2563	31	42	non	non	ADJ
iajs-2563	31	43	-	-	ADJ
iajs-2563	31	44	informative	informative	ADJ
iajs-2563	31	45	prior	prior	ADV
iajs-2563	31	46	.	.	PUNCT
iajs-2563	32	1	applying	apply	VERB
iajs-2563	32	2	jeffrey	jeffrey	PROPN
iajs-2563	32	3	's	's	PART
iajs-2563	32	4	rule	rule	NOUN
iajs-2563	32	5	[	[	X
iajs-2563	32	6	5	5	NUM
iajs-2563	32	7	]	]	PUNCT
iajs-2563	32	8	,	,	PUNCT
iajs-2563	32	9	we	we	PRON
iajs-2563	32	10	get	get	VERB
iajs-2563	32	11	𝑔(𝜃	𝑔(𝜃	NUM
iajs-2563	32	12	)	)	PUNCT
iajs-2563	32	13	∝	∝	PROPN
iajs-2563	32	14	√𝐼(𝜃	√𝐼(𝜃	PROPN
iajs-2563	32	15	)	)	PUNCT
iajs-2563	32	16	or	or	CCONJ
iajs-2563	32	17	𝑔(𝜃	𝑔(𝜃	NUM
iajs-2563	32	18	)	)	PUNCT
iajs-2563	32	19	=	=	SYM
iajs-2563	33	1	𝑐√𝐼(𝜃	𝑐√𝐼(𝜃	X
iajs-2563	33	2	)	)	PUNCT
iajs-2563	33	3	127	127	NUM
iajs-2563	33	4	ibn	ibn	PROPN
iajs-2563	33	5	al	al	PROPN
iajs-2563	33	6	-	-	PUNCT
iajs-2563	33	7	haitham	haitham	PROPN
iajs-2563	33	8	jour	jour	X
iajs-2563	33	9	.	.	PROPN
iajs-2563	34	1	for	for	ADP
iajs-2563	34	2	pure	pure	ADJ
iajs-2563	34	3	&	&	CCONJ
iajs-2563	34	4	appl	appl	PROPN
iajs-2563	34	5	.	.	PUNCT
iajs-2563	35	1	sci	sci	PROPN
iajs-2563	35	2	.	.	PROPN
iajs-2563	36	1	34	34	NUM
iajs-2563	36	2	(	(	PUNCT
iajs-2563	36	3	1	1	NUM
iajs-2563	36	4	)	)	PUNCT
iajs-2563	36	5	2021	2021	NUM
iajs-2563	36	6	where	where	SCONJ
iajs-2563	36	7	𝑔(𝜃	𝑔(𝜃	NOUN
iajs-2563	36	8	)	)	PUNCT
iajs-2563	36	9	represents	represent	VERB
iajs-2563	36	10	jeffrey	jeffrey	PROPN
iajs-2563	36	11	's	's	PART
iajs-2563	36	12	prior	prior	ADJ
iajs-2563	36	13	information	information	NOUN
iajs-2563	36	14	,	,	PUNCT
iajs-2563	36	15	c	c	PROPN
iajs-2563	36	16	is	be	AUX
iajs-2563	36	17	the	the	DET
iajs-2563	36	18	constant	constant	ADJ
iajs-2563	36	19	of	of	ADP
iajs-2563	36	20	proportionality	proportionality	NOUN
iajs-2563	36	21	and	and	CCONJ
iajs-2563	36	22	𝐼(𝜃	𝐼(𝜃	CCONJ
iajs-2563	36	23	)	)	PUNCT
iajs-2563	36	24	represents	represent	VERB
iajs-2563	36	25	fisher	fisher	PROPN
iajs-2563	36	26	information	information	NOUN
iajs-2563	36	27	,	,	PUNCT
iajs-2563	36	28	defined	define	VERB
iajs-2563	36	29	as	as	SCONJ
iajs-2563	36	30	follows	follow	VERB
iajs-2563	36	31	:	:	PUNCT
iajs-2563	36	32	𝐼(𝜃	𝐼(𝜃	NUM
iajs-2563	36	33	)	)	PUNCT
iajs-2563	37	1	=	=	PUNCT
iajs-2563	37	2	−𝑛𝐸	−𝑛𝐸	PROPN
iajs-2563	37	3	[	[	PUNCT
iajs-2563	37	4	𝜕2	𝜕2	NOUN
iajs-2563	37	5	ln	ln	NOUN
iajs-2563	37	6	𝑓(𝑡,𝜃	𝑓(𝑡,𝜃	NOUN
iajs-2563	37	7	)	)	PUNCT
iajs-2563	37	8	𝜕𝜃2	𝜕𝜃2	X
iajs-2563	37	9	]	]	PUNCT
iajs-2563	37	10	(	(	PUNCT
iajs-2563	37	11	6	6	NUM
iajs-2563	37	12	)	)	PUNCT
iajs-2563	37	13	therefore	therefore	ADV
iajs-2563	37	14	,	,	PUNCT
iajs-2563	37	15	𝑔1(𝜃	𝑔1(𝜃	NOUN
iajs-2563	37	16	)	)	PUNCT
iajs-2563	37	17	=	=	SYM
iajs-2563	38	1	𝑐√−𝑛𝐸	𝑐√−𝑛𝐸	PUNCT
iajs-2563	38	2	(	(	PUNCT
iajs-2563	38	3	𝜕2	𝜕2	NUM
iajs-2563	38	4	ln	ln	NOUN
iajs-2563	38	5	𝑓(𝑡,𝜃	𝑓(𝑡,𝜃	NOUN
iajs-2563	38	6	)	)	PUNCT
iajs-2563	38	7	𝜕𝜃2	𝜕𝜃2	PUNCT
iajs-2563	38	8	)	)	PUNCT
iajs-2563	38	9	(	(	PUNCT
iajs-2563	38	10	7	7	NUM
iajs-2563	38	11	)	)	PUNCT
iajs-2563	38	12	by	by	ADP
iajs-2563	38	13	taking	take	VERB
iajs-2563	38	14	the	the	DET
iajs-2563	38	15	logarithm	logarithm	NOUN
iajs-2563	38	16	of	of	ADP
iajs-2563	38	17	equation	equation	NOUN
iajs-2563	38	18	(	(	PUNCT
iajs-2563	38	19	1	1	NUM
iajs-2563	38	20	)	)	PUNCT
iajs-2563	38	21	,	,	PUNCT
iajs-2563	38	22	we	we	PRON
iajs-2563	38	23	get	get	VERB
iajs-2563	38	24	𝑙n	𝑙n	ADJ
iajs-2563	38	25	𝑓(𝑡𝑖	𝑓(𝑡𝑖	PRON
iajs-2563	38	26	,	,	PUNCT
iajs-2563	38	27	𝜃	𝜃	X
iajs-2563	38	28	)	)	PUNCT
iajs-2563	38	29	=	=	SYM
iajs-2563	38	30	𝑙𝑛(2	𝑙𝑛(2	NOUN
iajs-2563	38	31	)	)	PUNCT
iajs-2563	38	32	+	+	CCONJ
iajs-2563	38	33	𝑙n(𝜃	𝑙n(𝜃	X
iajs-2563	38	34	)	)	PUNCT
iajs-2563	39	1	+	+	CCONJ
iajs-2563	39	2	ln	ln	ADJ
iajs-2563	39	3	(	(	PUNCT
iajs-2563	39	4	1	1	NUM
iajs-2563	39	5	𝑡3	𝑡3	PROPN
iajs-2563	39	6	)	)	PUNCT
iajs-2563	40	1	−	−	PROPN
iajs-2563	40	2	𝜃	𝜃	NUM
iajs-2563	40	3	𝑡2	𝑡2	PROPN
iajs-2563	40	4	𝜕	𝜕	PROPN
iajs-2563	40	5	𝑙n	𝑙n	PROPN
iajs-2563	40	6	𝑓(𝑡𝑖,𝜃	𝑓(𝑡𝑖,𝜃	PROPN
iajs-2563	40	7	)	)	PUNCT
iajs-2563	40	8	𝜕𝜃	𝜕𝜃	NOUN
iajs-2563	41	1	=	=	SYM
iajs-2563	42	1	1	1	NUM
iajs-2563	42	2	𝜃	𝜃	NOUN
iajs-2563	42	3	−	−	NOUN
iajs-2563	42	4	1	1	NUM
iajs-2563	42	5	𝑡𝑖	𝑡𝑖	NOUN
iajs-2563	42	6	2	2	NUM
iajs-2563	42	7	thus	thus	ADV
iajs-2563	42	8	,	,	PUNCT
iajs-2563	42	9	the	the	DET
iajs-2563	42	10	second	second	ADJ
iajs-2563	42	11	derivative	derivative	NOUN
iajs-2563	42	12	is	be	AUX
iajs-2563	42	13	𝜕2	𝜕2	NOUN
iajs-2563	42	14	ln	ln	ADJ
iajs-2563	42	15	𝑓(𝑡𝑖	𝑓(𝑡𝑖	NUM
iajs-2563	42	16	,	,	PUNCT
iajs-2563	42	17	𝜃	𝜃	X
iajs-2563	42	18	)	)	PUNCT
iajs-2563	42	19	𝜕	𝜕	NOUN
iajs-2563	42	20	𝜃2	𝜃2	NOUN
iajs-2563	42	21	=	=	SYM
iajs-2563	42	22	−	−	PROPN
iajs-2563	42	23	1	1	NUM
iajs-2563	42	24	𝜃2	𝜃2	NOUN
iajs-2563	42	25	hence	hence	ADV
iajs-2563	42	26	,	,	PUNCT
iajs-2563	42	27	we	we	PRON
iajs-2563	42	28	get	get	VERB
iajs-2563	42	29	:	:	PUNCT
iajs-2563	42	30	𝐸	𝐸	PROPN
iajs-2563	42	31	(	(	PUNCT
iajs-2563	42	32	𝜕2	𝜕2	NUM
iajs-2563	42	33	ln	ln	ADV
iajs-2563	42	34	𝑓	𝑓	PROPN
iajs-2563	42	35	(	(	PUNCT
iajs-2563	42	36	𝑡𝑖	𝑡𝑖	NOUN
iajs-2563	42	37	,	,	PUNCT
iajs-2563	42	38	𝜃	𝜃	X
iajs-2563	42	39	)	)	PUNCT
iajs-2563	42	40	𝜕	𝜕	NOUN
iajs-2563	42	41	𝜃2	𝜃2	NOUN
iajs-2563	42	42	)	)	PUNCT
iajs-2563	42	43	=	=	SYM
iajs-2563	42	44	−	−	PROPN
iajs-2563	42	45	1	1	NUM
iajs-2563	42	46	𝜃2	𝜃2	NOUN
iajs-2563	42	47	after	after	ADP
iajs-2563	42	48	substitution	substitution	NOUN
iajs-2563	42	49	into	into	ADP
iajs-2563	42	50	(	(	PUNCT
iajs-2563	42	51	7	7	NUM
iajs-2563	42	52	)	)	PUNCT
iajs-2563	42	53	,	,	PUNCT
iajs-2563	42	54	we	we	PRON
iajs-2563	42	55	get	get	VERB
iajs-2563	42	56	𝑔1(𝜃	𝑔1(𝜃	NOUN
iajs-2563	42	57	)	)	PUNCT
iajs-2563	42	58	=	=	SYM
iajs-2563	42	59	𝑐	𝑐	PUNCT
iajs-2563	42	60	𝜃	𝜃	NOUN
iajs-2563	42	61	√𝑛	√𝑛	NOUN
iajs-2563	42	62	,	,	PUNCT
iajs-2563	42	63	𝜃	𝜃	X
iajs-2563	42	64	>	>	X
iajs-2563	42	65	0	0	PUNCT
iajs-2563	43	1	(	(	PUNCT
iajs-2563	43	2	8)	8)	NUM
iajs-2563	43	3	the	the	DET
iajs-2563	43	4	posterior	posterior	ADJ
iajs-2563	43	5	density	density	NOUN
iajs-2563	43	6	function	function	NOUN
iajs-2563	43	7	is	be	AUX
iajs-2563	43	8	defined	define	VERB
iajs-2563	43	9	as	as	ADP
iajs-2563	43	10	:	:	PUNCT
iajs-2563	43	11	ℎ(𝜃|𝑡	ℎ(𝜃|𝑡	NUM
iajs-2563	43	12	)	)	PUNCT
iajs-2563	43	13	=	=	SYM
iajs-2563	43	14	𝑔(𝜃)𝐿(𝑡|𝜃	𝑔(𝜃)𝐿(𝑡|𝜃	PROPN
iajs-2563	43	15	)	)	PUNCT
iajs-2563	43	16	∫	∫	PROPN
iajs-2563	43	17	𝑔(𝜃)𝐿(𝑡|𝜃	𝑔(𝜃)𝐿(𝑡|𝜃	NOUN
iajs-2563	43	18	)	)	PUNCT
iajs-2563	43	19	∞	∞	NUM
iajs-2563	43	20	0	0	NUM
iajs-2563	44	1	(	(	PUNCT
iajs-2563	44	2	9	9	NUM
iajs-2563	44	3	)	)	PUNCT
iajs-2563	44	4	hence	hence	ADV
iajs-2563	44	5	,	,	PUNCT
iajs-2563	44	6	the	the	DET
iajs-2563	44	7	posterior	posterior	ADJ
iajs-2563	44	8	density	density	NOUN
iajs-2563	44	9	function	function	NOUN
iajs-2563	44	10	for	for	ADP
iajs-2563	44	11	θ	θ	PROPN
iajs-2563	44	12	based	base	VERB
iajs-2563	44	13	on	on	ADP
iajs-2563	44	14	jeffreys	jeffreys	PROPN
iajs-2563	44	15	prior	prior	ADV
iajs-2563	44	16	will	will	AUX
iajs-2563	44	17	be	be	AUX
iajs-2563	44	18	h1(θ|𝑡	h1(θ|𝑡	ADV
iajs-2563	44	19	)	)	PUNCT
iajs-2563	44	20	=	=	SYM
iajs-2563	44	21	𝑐	𝑐	PUNCT
iajs-2563	44	22	𝜃	𝜃	NUM
iajs-2563	44	23	√𝑛	√𝑛	ADP
iajs-2563	44	24	2𝑛𝜃𝑛	2𝑛𝜃𝑛	NUM
iajs-2563	44	25	∏	∏	NUM
iajs-2563	44	26	1	1	NUM
iajs-2563	44	27	𝑡𝑖	𝑡𝑖	PART
iajs-2563	44	28	3	3	NUM
iajs-2563	44	29	𝑛	𝑛	PRON
iajs-2563	44	30	𝑖=1	𝑖=1	PROPN
iajs-2563	44	31	exp	exp	NOUN
iajs-2563	44	32	(	(	PUNCT
iajs-2563	44	33	−𝜃	−𝜃	NOUN
iajs-2563	44	34	∑	∑	PROPN
iajs-2563	44	35	1	1	NUM
iajs-2563	44	36	𝑡𝑖	𝑡𝑖	PART
iajs-2563	44	37	2	2	NUM
iajs-2563	44	38	𝑛	𝑛	PRON
iajs-2563	44	39	𝑖=1	𝑖=1	PROPN
iajs-2563	45	1	)	)	PUNCT
iajs-2563	45	2	∫	∫	PROPN
iajs-2563	45	3	𝑐	𝑐	PROPN
iajs-2563	45	4	𝜃	𝜃	PROPN
iajs-2563	45	5	√𝑛	√𝑛	ADP
iajs-2563	45	6	2𝑛𝜃𝑛	2𝑛𝜃𝑛	NUM
iajs-2563	45	7	∏	∏	NUM
iajs-2563	45	8	1	1	NUM
iajs-2563	45	9	𝑡𝑖	𝑡𝑖	PART
iajs-2563	45	10	3	3	NUM
iajs-2563	45	11	𝑛	𝑛	PRON
iajs-2563	45	12	𝑖=1	𝑖=1	PROPN
iajs-2563	45	13	exp	exp	NOUN
iajs-2563	45	14	(	(	PUNCT
iajs-2563	45	15	−𝜃	−𝜃	NOUN
iajs-2563	45	16	∑	∑	PROPN
iajs-2563	45	17	1	1	NUM
iajs-2563	45	18	𝑡𝑖	𝑡𝑖	PART
iajs-2563	45	19	2	2	NUM
iajs-2563	45	20	𝑛	𝑛	PRON
iajs-2563	45	21	𝑖=1	𝑖=1	PROPN
iajs-2563	45	22	)	)	PUNCT
iajs-2563	46	1	𝑑𝜃	𝑑𝜃	ADP
iajs-2563	46	2	∞	∞	NUM
iajs-2563	46	3	0	0	NUM
iajs-2563	46	4	h1(θ|𝑡	h1(θ|𝑡	NOUN
iajs-2563	46	5	)	)	PUNCT
iajs-2563	46	6	=	=	SYM
iajs-2563	47	1	𝜃𝑛−1𝑒−𝜃𝑇	𝜃𝑛−1𝑒−𝜃𝑇	PROPN
iajs-2563	47	2	∫	∫	PROPN
iajs-2563	47	3	𝜃𝑛−1𝑒−𝜃𝑇𝑑𝜃	𝜃𝑛−1𝑒−𝜃𝑇𝑑𝜃	PROPN
iajs-2563	47	4	∞	∞	PROPN
iajs-2563	47	5	0	0	NUM
iajs-2563	47	6	,	,	PUNCT
iajs-2563	47	7	𝑇	𝑇	PROPN
iajs-2563	47	8	=	=	SYM
iajs-2563	47	9	∑	∑	PROPN
iajs-2563	47	10	1	1	NUM
iajs-2563	47	11	𝑡2	𝑡2	NOUN
iajs-2563	47	12	𝑛	𝑛	PRON
iajs-2563	47	13	𝑖=1	𝑖=1	PROPN
iajs-2563	47	14	,	,	PUNCT
iajs-2563	47	15	𝜃	𝜃	X
iajs-2563	47	16	>	>	X
iajs-2563	47	17	0	0	PUNCT
iajs-2563	48	1	hence	hence	ADV
iajs-2563	48	2	,	,	PUNCT
iajs-2563	48	3	the	the	DET
iajs-2563	48	4	posterior	posterior	ADJ
iajs-2563	48	5	density	density	NOUN
iajs-2563	48	6	function	function	NOUN
iajs-2563	48	7	of	of	ADP
iajs-2563	48	8	𝜃	𝜃	PROPN
iajs-2563	48	9	with	with	ADP
iajs-2563	48	10	jeffreys	jeffreys	PROPN
iajs-2563	48	11	prior	prior	ADV
iajs-2563	48	12	can	can	AUX
iajs-2563	48	13	be	be	AUX
iajs-2563	48	14	written	write	VERB
iajs-2563	48	15	as	as	ADP
iajs-2563	48	16	128	128	NUM
iajs-2563	48	17	ibn	ibn	PROPN
iajs-2563	48	18	al	al	PROPN
iajs-2563	48	19	-	-	PUNCT
iajs-2563	48	20	haitham	haitham	PROPN
iajs-2563	48	21	jour	jour	X
iajs-2563	48	22	.	.	PROPN
iajs-2563	48	23	for	for	ADP
iajs-2563	48	24	pure	pure	ADJ
iajs-2563	48	25	&	&	CCONJ
iajs-2563	48	26	appl	appl	PROPN
iajs-2563	48	27	.	.	PUNCT
iajs-2563	49	1	sci	sci	PROPN
iajs-2563	49	2	.	.	PROPN
iajs-2563	50	1	34	34	NUM
iajs-2563	50	2	(	(	PUNCT
iajs-2563	50	3	1	1	NUM
iajs-2563	50	4	)	)	PUNCT
iajs-2563	50	5	2021	2021	NUM
iajs-2563	50	6	=	=	SYM
iajs-2563	50	7	𝑇𝑛𝜃𝑛−1𝑒−𝜃𝑇	𝑇𝑛𝜃𝑛−1𝑒−𝜃𝑇	NUM
iajs-2563	50	8	γ(n	γ(n	X
iajs-2563	50	9	)	)	PUNCT
iajs-2563	50	10	(	(	PUNCT
iajs-2563	50	11	10	10	NUM
iajs-2563	50	12	)	)	PUNCT
iajs-2563	50	13	the	the	DET
iajs-2563	50	14	posterior	posterior	ADJ
iajs-2563	50	15	density	density	NOUN
iajs-2563	50	16	function	function	NOUN
iajs-2563	50	17	is	be	AUX
iajs-2563	50	18	recognized	recognize	VERB
iajs-2563	50	19	as	as	ADP
iajs-2563	50	20	the	the	DET
iajs-2563	50	21	density	density	NOUN
iajs-2563	50	22	of	of	ADP
iajs-2563	50	23	the	the	DET
iajs-2563	50	24	gamma	gamma	NOUN
iajs-2563	50	25	distribution	distribution	NOUN
iajs-2563	50	26	,	,	PUNCT
iajs-2563	50	27	i.e.	i.e.	X
iajs-2563	50	28	(	(	PUNCT
iajs-2563	50	29	θ|t)~𝐺𝑎𝑚𝑚𝑎	θ|t)~𝐺𝑎𝑚𝑚𝑎	PROPN
iajs-2563	50	30	(	(	PUNCT
iajs-2563	50	31	𝑛	𝑛	PROPN
iajs-2563	50	32	,	,	PUNCT
iajs-2563	50	33	1	1	NUM
iajs-2563	50	34	𝑇	𝑇	PROPN
iajs-2563	50	35	)	)	PUNCT
iajs-2563	50	36	,	,	PUNCT
iajs-2563	50	37	with	with	ADP
iajs-2563	50	38	𝐸(𝜃	𝐸(𝜃	PRON
iajs-2563	50	39	)	)	PUNCT
iajs-2563	50	40	=	=	SYM
iajs-2563	50	41	𝑛	𝑛	PRON
iajs-2563	50	42	𝑇	𝑇	PROPN
iajs-2563	50	43	,	,	PUNCT
iajs-2563	50	44	𝑉𝑎𝑟(𝜃	𝑉𝑎𝑟(𝜃	NUM
iajs-2563	50	45	)	)	PUNCT
iajs-2563	50	46	=	=	SYM
iajs-2563	50	47	𝑛	𝑛	PRON
iajs-2563	50	48	𝑇2	𝑇2	NOUN
iajs-2563	50	49	(	(	PUNCT
iajs-2563	50	50	11	11	NUM
iajs-2563	50	51	)	)	SYM
iajs-2563	50	52	4	4	NUM
iajs-2563	50	53	.	.	PUNCT
iajs-2563	50	54	posterior	posterior	ADJ
iajs-2563	50	55	density	density	NOUN
iajs-2563	50	56	of	of	ADP
iajs-2563	50	57	inverse	inverse	NOUN
iajs-2563	50	58	rayleigh	rayleigh	PROPN
iajs-2563	50	59	parameter	parameter	NOUN
iajs-2563	50	60	based	base	VERB
iajs-2563	50	61	on	on	ADP
iajs-2563	50	62	exponential	exponential	ADJ
iajs-2563	50	63	prior	prior	ADJ
iajs-2563	50	64	distribution	distribution	NOUN
iajs-2563	50	65	assuming	assume	VERB
iajs-2563	50	66	that	that	SCONJ
iajs-2563	50	67	the	the	DET
iajs-2563	50	68	inverse	inverse	NOUN
iajs-2563	50	69	rayleigh	rayleigh	PROPN
iajs-2563	50	70	parameter	parameter	PROPN
iajs-2563	50	71	𝜃	𝜃	PROPN
iajs-2563	50	72	follows	follow	VERB
iajs-2563	50	73	exponential	exponential	ADJ
iajs-2563	50	74	prior	prior	ADJ
iajs-2563	50	75	distribution	distribution	NOUN
iajs-2563	50	76	with	with	ADP
iajs-2563	50	77	parameter	parameter	NOUN
iajs-2563	50	78	𝜆	𝜆	X
iajs-2563	51	1	[	[	X
iajs-2563	51	2	6	6	NUM
iajs-2563	51	3	]	]	PUNCT
iajs-2563	51	4	,	,	PUNCT
iajs-2563	51	5	that	that	PRON
iajs-2563	51	6	is	be	AUX
iajs-2563	51	7	𝑔2(𝜃	𝑔2(𝜃	PROPN
iajs-2563	51	8	)	)	PUNCT
iajs-2563	51	9	=	=	SYM
iajs-2563	51	10	𝜆𝑒−𝜆𝜃	𝜆𝑒−𝜆𝜃	NOUN
iajs-2563	51	11	,	,	PUNCT
iajs-2563	51	12	λ	λ	X
iajs-2563	51	13	>	>	X
iajs-2563	51	14	0	0	NUM
iajs-2563	51	15	,	,	PUNCT
iajs-2563	51	16	𝜃	𝜃	X
iajs-2563	51	17	>	>	X
iajs-2563	51	18	0	0	PUNCT
iajs-2563	52	1	(	(	PUNCT
iajs-2563	52	2	12	12	NUM
iajs-2563	52	3	)	)	PUNCT
iajs-2563	52	4	where	where	SCONJ
iajs-2563	52	5	𝑔2(𝜃	𝑔2(𝜃	NOUN
iajs-2563	52	6	)	)	PUNCT
iajs-2563	52	7	denotes	denote	VERB
iajs-2563	52	8	the	the	DET
iajs-2563	52	9	exponential	exponential	ADJ
iajs-2563	52	10	prior	prior	ADJ
iajs-2563	52	11	distribution	distribution	NOUN
iajs-2563	52	12	of	of	ADP
iajs-2563	52	13	the	the	DET
iajs-2563	52	14	inverse	inverse	NOUN
iajs-2563	52	15	rayleigh	rayleigh	PROPN
iajs-2563	52	16	parameter	parameter	PROPN
iajs-2563	52	17	𝜃.	𝜃.	PROPN
iajs-2563	52	18	from	from	ADP
iajs-2563	52	19	bayesian	bayesian	NOUN
iajs-2563	52	20	theorem	theorem	VERB
iajs-2563	52	21	the	the	DET
iajs-2563	52	22	posterior	posterior	ADJ
iajs-2563	52	23	density	density	NOUN
iajs-2563	52	24	function	function	NOUN
iajs-2563	52	25	of	of	ADP
iajs-2563	52	26			PROPN
iajs-2563	52	27	denoted	denote	VERB
iajs-2563	52	28	by	by	ADP
iajs-2563	52	29	ℎ2(𝜃|𝑡	ℎ2(𝜃|𝑡	NOUN
iajs-2563	52	30	)	)	PUNCT
iajs-2563	52	31	can	can	AUX
iajs-2563	52	32	be	be	AUX
iajs-2563	52	33	obtained	obtain	VERB
iajs-2563	52	34	as	as	ADP
iajs-2563	52	35	ℎ2(𝜃|𝑡	ℎ2(𝜃|𝑡	NOUN
iajs-2563	52	36	)	)	PUNCT
iajs-2563	52	37	=	=	SYM
iajs-2563	52	38	𝜃𝑛𝑒−𝜃(𝑇+𝜆	𝜃𝑛𝑒−𝜃(𝑇+𝜆	NOUN
iajs-2563	52	39	)	)	PUNCT
iajs-2563	52	40	∫	∫	PROPN
iajs-2563	52	41	𝜃𝑛𝑒−𝜃(𝑇+𝜆	𝜃𝑛𝑒−𝜃(𝑇+𝜆	NOUN
iajs-2563	52	42	)	)	PUNCT
iajs-2563	53	1	∞	∞	PROPN
iajs-2563	53	2	0	0	NUM
iajs-2563	53	3	𝑑𝜃	𝑑𝜃	PROPN
iajs-2563	53	4	(	(	PUNCT
iajs-2563	53	5	13	13	NUM
iajs-2563	53	6	)	)	PUNCT
iajs-2563	53	7	where	where	SCONJ
iajs-2563	53	8	𝑇	𝑇	PROPN
iajs-2563	53	9	=	=	SYM
iajs-2563	53	10	∑	∑	PROPN
iajs-2563	53	11	1	1	NUM
iajs-2563	53	12	𝑡𝑖	𝑡𝑖	PART
iajs-2563	53	13	2	2	NUM
iajs-2563	53	14	𝑛	𝑛	PRON
iajs-2563	53	15	𝑖=1	𝑖=1	PUNCT
iajs-2563	53	16	ℎ2(𝜃|𝑡	ℎ2(𝜃|𝑡	NOUN
iajs-2563	53	17	)	)	PUNCT
iajs-2563	53	18	=	=	SYM
iajs-2563	53	19	(	(	PUNCT
iajs-2563	53	20	𝑇+𝜆)𝑛+1𝜃𝑛	𝑇+𝜆)𝑛+1𝜃𝑛	NUM
iajs-2563	53	21	𝑒−𝜃(𝑇+𝜆	𝑒−𝜃(𝑇+𝜆	NOUN
iajs-2563	53	22	)	)	PUNCT
iajs-2563	53	23	𝛤(𝑛+1	𝛤(𝑛+1	NUM
iajs-2563	53	24	)	)	PUNCT
iajs-2563	53	25	𝜃	𝜃	NOUN
iajs-2563	53	26	>	>	X
iajs-2563	53	27	0	0	PUNCT
iajs-2563	54	1	(	(	PUNCT
iajs-2563	54	2	14	14	NUM
iajs-2563	54	3	)	)	PUNCT
iajs-2563	54	4	it	it	PRON
iajs-2563	54	5	can	can	AUX
iajs-2563	54	6	easily	easily	ADV
iajs-2563	54	7	be	be	AUX
iajs-2563	54	8	noted	note	VERB
iajs-2563	54	9	that	that	SCONJ
iajs-2563	54	10	θ|x	θ|x	X
iajs-2563	54	11	~	~	SYM
iajs-2563	54	12	gamma	gamma	NOUN
iajs-2563	54	13	(	(	PUNCT
iajs-2563	54	14	𝑛	𝑛	PROPN
iajs-2563	54	15	+	+	NUM
iajs-2563	54	16	1	1	NUM
iajs-2563	54	17	,	,	PUNCT
iajs-2563	54	18	1	1	NUM
iajs-2563	54	19	𝑝	𝑝	NOUN
iajs-2563	54	20	)	)	PUNCT
iajs-2563	54	21	where	where	SCONJ
iajs-2563	54	22	𝑃	𝑃	NOUN
iajs-2563	54	23	=	=	SYM
iajs-2563	54	24	𝑇	𝑇	PROPN
iajs-2563	54	25	+	+	CCONJ
iajs-2563	54	26	𝜆	𝜆	NOUN
iajs-2563	54	27	with	with	ADP
iajs-2563	54	28	e(𝜃|𝑡	e(𝜃|𝑡	NOUN
iajs-2563	54	29	)	)	PUNCT
iajs-2563	54	30	=	=	SYM
iajs-2563	55	1	𝑛+1	𝑛+1	AUX
iajs-2563	55	2	𝑃	𝑃	PROPN
iajs-2563	55	3	,	,	PUNCT
iajs-2563	55	4	𝑉𝑎𝑟	𝑉𝑎𝑟	PROPN
iajs-2563	55	5	(	(	PUNCT
iajs-2563	55	6	𝜃|𝑡	𝜃|𝑡	NOUN
iajs-2563	55	7	)	)	PUNCT
iajs-2563	55	8	=	=	SYM
iajs-2563	56	1	𝑛+1	𝑛+1	NUM
iajs-2563	56	2	𝑃2	𝑃2	NOUN
iajs-2563	56	3	(	(	PUNCT
iajs-2563	56	4	15	15	NUM
iajs-2563	56	5	)	)	SYM
iajs-2563	56	6	5	5	NUM
iajs-2563	56	7	.	.	NOUN
iajs-2563	56	8	types	type	NOUN
iajs-2563	56	9	of	of	ADP
iajs-2563	56	10	loss	loss	NOUN
iajs-2563	56	11	functions	function	NOUN
iajs-2563	56	12	[	[	X
iajs-2563	56	13	7	7	NUM
iajs-2563	56	14	]	]	PUNCT
iajs-2563	56	15	from	from	ADP
iajs-2563	56	16	the	the	DET
iajs-2563	56	17	bayesian	bayesian	NOUN
iajs-2563	56	18	viewpoint	viewpoint	NOUN
iajs-2563	56	19	,	,	PUNCT
iajs-2563	56	20	the	the	DET
iajs-2563	56	21	essential	essential	ADJ
iajs-2563	56	22	step	step	NOUN
iajs-2563	56	23	in	in	ADP
iajs-2563	56	24	the	the	DET
iajs-2563	56	25	estimation	estimation	NOUN
iajs-2563	56	26	and	and	CCONJ
iajs-2563	56	27	prediction	prediction	NOUN
iajs-2563	56	28	problems	problem	NOUN
iajs-2563	56	29	was	be	AUX
iajs-2563	56	30	represented	represent	VERB
iajs-2563	56	31	by	by	ADP
iajs-2563	56	32	choosing	choose	VERB
iajs-2563	56	33	the	the	DET
iajs-2563	56	34	loss	loss	NOUN
iajs-2563	56	35	function	function	NOUN
iajs-2563	56	36	.	.	PUNCT
iajs-2563	57	1	in	in	ADP
iajs-2563	57	2	fact	fact	NOUN
iajs-2563	57	3	,	,	PUNCT
iajs-2563	57	4	there	there	PRON
iajs-2563	57	5	is	be	VERB
iajs-2563	57	6	no	no	DET
iajs-2563	57	7	specific	specific	ADJ
iajs-2563	57	8	analytical	analytical	ADJ
iajs-2563	57	9	procedure	procedure	NOUN
iajs-2563	57	10	to	to	PART
iajs-2563	57	11	determine	determine	VERB
iajs-2563	57	12	the	the	DET
iajs-2563	57	13	suitable	suitable	ADJ
iajs-2563	57	14	loss	loss	NOUN
iajs-2563	57	15	function	function	NOUN
iajs-2563	57	16	to	to	PART
iajs-2563	57	17	be	be	AUX
iajs-2563	57	18	employed	employ	VERB
iajs-2563	57	19	.	.	PUNCT
iajs-2563	58	1	in	in	ADP
iajs-2563	58	2	this	this	DET
iajs-2563	58	3	paper	paper	NOUN
iajs-2563	58	4	,	,	PUNCT
iajs-2563	58	5	we	we	PRON
iajs-2563	58	6	consider	consider	VERB
iajs-2563	58	7	two	two	NUM
iajs-2563	58	8	types	type	NOUN
iajs-2563	58	9	of	of	ADP
iajs-2563	58	10	loss	loss	NOUN
iajs-2563	58	11	function	function	NOUN
iajs-2563	58	12	,	,	PUNCT
iajs-2563	58	13	the	the	DET
iajs-2563	58	14	entropy	entropy	NOUN
iajs-2563	58	15	loss	loss	NOUN
iajs-2563	58	16	function	function	NOUN
iajs-2563	58	17	and	and	CCONJ
iajs-2563	58	18	linear	linear	ADJ
iajs-2563	58	19	exponential	exponential	ADJ
iajs-2563	58	20	loss	loss	NOUN
iajs-2563	58	21	function	function	NOUN
iajs-2563	58	22	(	(	PUNCT
iajs-2563	58	23	linex	linex	ADV
iajs-2563	58	24	)	)	PUNCT
iajs-2563	58	25	,	,	PUNCT
iajs-2563	58	26	as	as	SCONJ
iajs-2563	58	27	follows	follow	VERB
iajs-2563	58	28	:	:	PUNCT
iajs-2563	58	29	i	i	PRON
iajs-2563	58	30	)	)	PUNCT
iajs-2563	58	31	entropy	entropy	VERB
iajs-2563	58	32	squared	square	VERB
iajs-2563	58	33	loss	loss	NOUN
iajs-2563	58	34	function	function	NOUN
iajs-2563	58	35	which	which	PRON
iajs-2563	58	36	is	be	AUX
iajs-2563	58	37	defined	define	VERB
iajs-2563	58	38	as	as	ADP
iajs-2563	58	39	below	below	ADP
iajs-2563	58	40	𝐿(𝜃	𝐿(𝜃	PROPN
iajs-2563	58	41	,	,	PUNCT
iajs-2563	58	42	𝜃	𝜃	NOUN
iajs-2563	58	43	)	)	PUNCT
iajs-2563	58	44	=	=	SYM
iajs-2563	58	45	�	�	PROPN
iajs-2563	58	46	̂	̂	NUM
iajs-2563	58	47	�	�	PROPN
iajs-2563	58	48	𝜃	𝜃	PART
iajs-2563	58	49	−	−	PROPN
iajs-2563	58	50	𝑙𝑛	𝑙𝑛	PROPN
iajs-2563	58	51	�	�	PROPN
iajs-2563	58	52	̂	̂	PROPN
iajs-2563	58	53	�	�	PROPN
iajs-2563	58	54	𝜃	𝜃	NOUN
iajs-2563	58	55	−	−	NUM
iajs-2563	58	56	1	1	NUM
iajs-2563	58	57	(	(	PUNCT
iajs-2563	58	58	16	16	NUM
iajs-2563	58	59	)	)	PUNCT
iajs-2563	58	60	ii	ii	PROPN
iajs-2563	58	61	)	)	PUNCT
iajs-2563	58	62	linear	linear	PROPN
iajs-2563	58	63	exponential	exponential	ADJ
iajs-2563	58	64	loss	loss	NOUN
iajs-2563	58	65	function	function	NOUN
iajs-2563	58	66	(	(	PUNCT
iajs-2563	58	67	linex	linex	ADV
iajs-2563	58	68	)	)	PUNCT
iajs-2563	58	69	which	which	PRON
iajs-2563	58	70	is	be	AUX
iajs-2563	58	71	defined	define	VERB
iajs-2563	58	72	as	as	ADP
iajs-2563	58	73	below	below	ADP
iajs-2563	58	74	𝐿(𝜃	𝐿(𝜃	PROPN
iajs-2563	58	75	,	,	PUNCT
iajs-2563	58	76	𝜃	𝜃	NOUN
iajs-2563	58	77	)	)	PUNCT
iajs-2563	58	78	=	=	SYM
iajs-2563	58	79	𝑒(	𝑒(	PROPN
iajs-2563	58	80	�	�	PROPN
iajs-2563	58	81	̂	̂	NOUN
iajs-2563	58	82	�	�	NOUN
iajs-2563	58	83	−𝜃	−𝜃	NOUN
iajs-2563	58	84	)	)	PUNCT
iajs-2563	58	85	−	−	PROPN
iajs-2563	59	1	(	(	PUNCT
iajs-2563	59	2	𝜃	𝜃	X
iajs-2563	59	3	−	−	NOUN
iajs-2563	59	4	𝜃	𝜃	NOUN
iajs-2563	59	5	)	)	PUNCT
iajs-2563	59	6	−	−	PROPN
iajs-2563	59	7	1	1	NUM
iajs-2563	59	8	(	(	PUNCT
iajs-2563	59	9	17	17	NUM
iajs-2563	59	10	)	)	PUNCT
iajs-2563	59	11	129	129	NUM
iajs-2563	59	12	ibn	ibn	PROPN
iajs-2563	59	13	al	al	PROPN
iajs-2563	59	14	-	-	PUNCT
iajs-2563	59	15	haitham	haitham	PROPN
iajs-2563	59	16	jour	jour	X
iajs-2563	59	17	.	.	PROPN
iajs-2563	60	1	for	for	ADP
iajs-2563	60	2	pure	pure	ADJ
iajs-2563	60	3	&	&	CCONJ
iajs-2563	60	4	appl	appl	PROPN
iajs-2563	60	5	.	.	PUNCT
iajs-2563	61	1	sci	sci	PROPN
iajs-2563	61	2	.	.	PROPN
iajs-2563	62	1	34	34	NUM
iajs-2563	62	2	(	(	PUNCT
iajs-2563	62	3	1	1	NUM
iajs-2563	62	4	)	)	PUNCT
iajs-2563	62	5	2021	2021	NUM
iajs-2563	62	6	6	6	NUM
iajs-2563	62	7	.	.	PUNCT
iajs-2563	63	1	bayesian	bayesian	NOUN
iajs-2563	63	2	estimation	estimation	NOUN
iajs-2563	63	3	the	the	DET
iajs-2563	63	4	bayes	bayes	PROPN
iajs-2563	63	5	estimator	estimator	NOUN
iajs-2563	63	6	of	of	ADP
iajs-2563	63	7	the	the	DET
iajs-2563	63	8	parameter	parameter	NOUN
iajs-2563	63	9	𝜃	𝜃	NOUN
iajs-2563	63	10	is	be	AUX
iajs-2563	63	11	the	the	DET
iajs-2563	63	12	value	value	NOUN
iajs-2563	63	13	of	of	ADP
iajs-2563	63	14	𝜃	𝜃	PRON
iajs-2563	63	15	that	that	PRON
iajs-2563	63	16	minimize	minimize	VERB
iajs-2563	63	17	the	the	DET
iajs-2563	63	18	posterior	posterior	ADJ
iajs-2563	63	19	expectation	expectation	NOUN
iajs-2563	63	20	known	know	VERB
iajs-2563	63	21	as	as	ADP
iajs-2563	63	22	the	the	DET
iajs-2563	63	23	risk	risk	NOUN
iajs-2563	63	24	function	function	NOUN
iajs-2563	63	25	denoted	denote	VERB
iajs-2563	63	26	by	by	ADP
iajs-2563	63	27	𝑅(𝜃	𝑅(𝜃	PROPN
iajs-2563	63	28	,	,	PUNCT
iajs-2563	63	29	𝜃	𝜃	NOUN
iajs-2563	63	30	)	)	PUNCT
iajs-2563	63	31	,	,	PUNCT
iajs-2563	63	32	that	that	ADV
iajs-2563	63	33	is	be	AUX
iajs-2563	63	34	𝑅(𝜃	𝑅(𝜃	PROPN
iajs-2563	63	35	,	,	PUNCT
iajs-2563	63	36	𝜃	𝜃	NOUN
iajs-2563	63	37	)	)	PUNCT
iajs-2563	63	38	=	=	SYM
iajs-2563	63	39	𝐸[𝐿(𝜃	𝐸[𝐿(𝜃	PROPN
iajs-2563	63	40	,	,	PUNCT
iajs-2563	63	41	𝜃	𝜃	NOUN
iajs-2563	63	42	)	)	PUNCT
iajs-2563	63	43	]	]	PUNCT
iajs-2563	64	1	=	=	SYM
iajs-2563	64	2	∫	∫	PROPN
iajs-2563	64	3	𝐿(𝜃	𝐿(𝜃	PROPN
iajs-2563	64	4	,	,	PUNCT
iajs-2563	64	5	𝜃	𝜃	NOUN
iajs-2563	64	6	∞	∞	NUM
iajs-2563	64	7	0	0	NUM
iajs-2563	64	8	)	)	PUNCT
iajs-2563	64	9	ℎ(𝜃|𝑡)𝑑𝜃	ℎ(𝜃|𝑡)𝑑𝜃	NOUN
iajs-2563	64	10	(	(	PUNCT
iajs-2563	64	11	18	18	NUM
iajs-2563	64	12	)	)	PUNCT
iajs-2563	64	13	where	where	SCONJ
iajs-2563	64	14	ℎ(𝜃|𝑡	ℎ(𝜃|𝑡	NOUN
iajs-2563	64	15	)	)	PUNCT
iajs-2563	64	16	is	be	AUX
iajs-2563	64	17	the	the	DET
iajs-2563	64	18	posterior	posterior	ADJ
iajs-2563	64	19	density	density	NOUN
iajs-2563	64	20	of	of	ADP
iajs-2563	64	21	𝜃|𝑡	𝜃|𝑡	NOUN
iajs-2563	64	22	7	7	NUM
iajs-2563	64	23	.	.	X
iajs-2563	64	24	bayes	bayes	PROPN
iajs-2563	64	25	estimator	estimator	NOUN
iajs-2563	64	26	of	of	ADP
iajs-2563	64	27	parameter	parameter	PROPN
iajs-2563	64	28	𝜽	𝜽	ADP
iajs-2563	64	29	and	and	CCONJ
iajs-2563	64	30	reliability	reliability	NOUN
iajs-2563	64	31	function	function	NOUN
iajs-2563	64	32	of	of	ADP
iajs-2563	64	33	ird	ird	PROPN
iajs-2563	64	34	under	under	ADP
iajs-2563	64	35	entropy	entropy	PROPN
iajs-2563	64	36	loss	loss	NOUN
iajs-2563	64	37	function	function	NOUN
iajs-2563	64	38	[	[	X
iajs-2563	64	39	8	8	NUM
iajs-2563	64	40	,	,	PUNCT
iajs-2563	64	41	9	9	NUM
iajs-2563	64	42	]	]	PUNCT
iajs-2563	64	43	.	.	PUNCT
iajs-2563	65	1	if	if	SCONJ
iajs-2563	65	2	entropy	entropy	NOUN
iajs-2563	65	3	loss	loss	NOUN
iajs-2563	65	4	function	function	NOUN
iajs-2563	65	5	is	be	AUX
iajs-2563	65	6	chosen	choose	VERB
iajs-2563	65	7	,	,	PUNCT
iajs-2563	65	8	then	then	ADV
iajs-2563	65	9	according	accord	VERB
iajs-2563	65	10	to	to	ADP
iajs-2563	65	11	equation	equation	NOUN
iajs-2563	65	12	(	(	PUNCT
iajs-2563	65	13	18	18	NUM
iajs-2563	65	14	)	)	PUNCT
iajs-2563	65	15	,	,	PUNCT
iajs-2563	65	16	we	we	PRON
iajs-2563	65	17	have	have	VERB
iajs-2563	65	18	𝑅(𝜃	𝑅(𝜃	NUM
iajs-2563	65	19	,	,	PUNCT
iajs-2563	65	20	𝜃	𝜃	NOUN
iajs-2563	65	21	)	)	PUNCT
iajs-2563	65	22	=	=	SYM
iajs-2563	65	23	∫	∫	PROPN
iajs-2563	65	24	[	[	PUNCT
iajs-2563	65	25	�	�	PROPN
iajs-2563	65	26	̂	̂	SYM
iajs-2563	65	27	�	�	PROPN
iajs-2563	65	28	𝜃	𝜃	PART
iajs-2563	65	29	−	−	PROPN
iajs-2563	65	30	𝑙𝑛	𝑙𝑛	PROPN
iajs-2563	65	31	�	�	PROPN
iajs-2563	65	32	̂	̂	PROPN
iajs-2563	65	33	�	�	PROPN
iajs-2563	65	34	𝜃	𝜃	NOUN
iajs-2563	65	35	−	−	PROPN
iajs-2563	65	36	1	1	NUM
iajs-2563	65	37	]	]	PUNCT
iajs-2563	65	38	ℎ(𝜃|𝑡)𝑑𝜃	ℎ(𝜃|𝑡)𝑑𝜃	VERB
iajs-2563	65	39	∞	∞	NOUN
iajs-2563	65	40	0	0	NUM
iajs-2563	65	41	by	by	ADP
iajs-2563	65	42	differentiating	differentiate	VERB
iajs-2563	65	43	r(θ̂	r(θ̂	PROPN
iajs-2563	65	44	,	,	PUNCT
iajs-2563	65	45	θ	θ	PROPN
iajs-2563	65	46	)	)	PUNCT
iajs-2563	65	47	with	with	ADP
iajs-2563	65	48	respect	respect	NOUN
iajs-2563	65	49	to	to	ADP
iajs-2563	65	50	𝜃	𝜃	NOUN
iajs-2563	65	51	and	and	CCONJ
iajs-2563	65	52	setting	set	VERB
iajs-2563	65	53	the	the	DET
iajs-2563	65	54	resultant	resultant	NOUN
iajs-2563	65	55	,	,	PUNCT
iajs-2563	65	56	derivative	derivative	NOUN
iajs-2563	65	57	equal	equal	ADJ
iajs-2563	65	58	to	to	ADP
iajs-2563	65	59	zero	zero	NUM
iajs-2563	65	60	,	,	PUNCT
iajs-2563	65	61	then	then	ADV
iajs-2563	65	62	solving	solve	VERB
iajs-2563	65	63	for	for	ADP
iajs-2563	65	64	𝜃	𝜃	PROPN
iajs-2563	65	65	,	,	PUNCT
iajs-2563	65	66	we	we	PRON
iajs-2563	65	67	get	get	VERB
iajs-2563	65	68	𝜃𝐸𝑛	𝜃𝐸𝑛	NOUN
iajs-2563	65	69	=	=	SYM
iajs-2563	65	70	1	1	NUM
iajs-2563	65	71	∫	∫	PROPN
iajs-2563	65	72	1	1	NUM
iajs-2563	65	73	𝜃	𝜃	NUM
iajs-2563	65	74	ℎ(𝜃|𝑡)𝑑𝜃	ℎ(𝜃|𝑡)𝑑𝜃	VERB
iajs-2563	65	75	∞	∞	PRON
iajs-2563	65	76	0	0	NUM
iajs-2563	66	1	(	(	PUNCT
iajs-2563	66	2	19	19	NUM
iajs-2563	66	3	)	)	PUNCT
iajs-2563	66	4	on	on	ADP
iajs-2563	66	5	the	the	DET
iajs-2563	66	6	basis	basis	NOUN
iajs-2563	66	7	of	of	ADP
iajs-2563	66	8	non	non	ADJ
iajs-2563	66	9	-	-	ADJ
iajs-2563	66	10	informative	informative	ADJ
iajs-2563	66	11	prior	prior	ADV
iajs-2563	66	12	and	and	CCONJ
iajs-2563	66	13	according	accord	VERB
iajs-2563	66	14	to	to	ADP
iajs-2563	66	15	equation	equation	NOUN
iajs-2563	66	16	(	(	PUNCT
iajs-2563	66	17	10	10	NUM
iajs-2563	66	18	)	)	PUNCT
iajs-2563	66	19	,	,	PUNCT
iajs-2563	66	20	the	the	DET
iajs-2563	66	21	bayes	bayes	PROPN
iajs-2563	66	22	estimator	estimator	NOUN
iajs-2563	66	23	of	of	ADP
iajs-2563	66	24	inverse	inverse	PROPN
iajs-2563	66	25	rayleigh	rayleigh	PROPN
iajs-2563	66	26	parameter	parameter	PROPN
iajs-2563	66	27	𝜃	𝜃	PRON
iajs-2563	66	28	denoted	denote	VERB
iajs-2563	66	29	as	as	ADP
iajs-2563	66	30	𝜃𝐸𝑛(𝐽	𝜃𝐸𝑛(𝐽	NOUN
iajs-2563	66	31	)	)	PUNCT
iajs-2563	66	32	is	be	AUX
iajs-2563	66	33	given	give	VERB
iajs-2563	66	34	by	by	ADP
iajs-2563	66	35	𝜃𝐸𝑛(𝐽	𝜃𝐸𝑛(𝐽	NOUN
iajs-2563	66	36	)	)	PUNCT
iajs-2563	67	1	=	=	SYM
iajs-2563	67	2	𝑛−1	𝑛−1	PROPN
iajs-2563	67	3	𝑇	𝑇	PROPN
iajs-2563	67	4	(	(	PUNCT
iajs-2563	67	5	20	20	NUM
iajs-2563	67	6	)	)	PUNCT
iajs-2563	67	7	if	if	SCONJ
iajs-2563	67	8	the	the	DET
iajs-2563	67	9	inverse	inverse	NOUN
iajs-2563	67	10	rayleigh	rayleigh	PROPN
iajs-2563	67	11	parameter	parameter	PROPN
iajs-2563	67	12	follows	follow	VERB
iajs-2563	67	13	the	the	DET
iajs-2563	67	14	exponential	exponential	ADJ
iajs-2563	67	15	prior	prior	ADJ
iajs-2563	67	16	distribution	distribution	NOUN
iajs-2563	67	17	,	,	PUNCT
iajs-2563	67	18	then	then	ADV
iajs-2563	67	19	by	by	ADP
iajs-2563	67	20	equation	equation	NOUN
iajs-2563	67	21	(	(	PUNCT
iajs-2563	67	22	14	14	NUM
iajs-2563	67	23	)	)	PUNCT
iajs-2563	67	24	we	we	PRON
iajs-2563	67	25	conclude	conclude	VERB
iajs-2563	67	26	that	that	SCONJ
iajs-2563	67	27	𝜃𝐸𝑛(𝐸	𝜃𝐸𝑛(𝐸	AUX
iajs-2563	67	28	)	)	PUNCT
iajs-2563	67	29	=	=	SYM
iajs-2563	67	30	𝑛	𝑛	PROPN
iajs-2563	67	31	𝑝	𝑝	NOUN
iajs-2563	67	32	,	,	PUNCT
iajs-2563	67	33	where	where	SCONJ
iajs-2563	67	34	p	p	X
iajs-2563	67	35	=	=	NOUN
iajs-2563	67	36	t+λ	t+λ	NUM
iajs-2563	67	37	(	(	PUNCT
iajs-2563	67	38	21	21	NUM
iajs-2563	67	39	)	)	PUNCT
iajs-2563	67	40	the	the	DET
iajs-2563	67	41	estimator	estimator	NOUN
iajs-2563	67	42	of	of	ADP
iajs-2563	67	43	the	the	DET
iajs-2563	67	44	reliability	reliability	NOUN
iajs-2563	67	45	function	function	NOUN
iajs-2563	67	46	based	base	VERB
iajs-2563	67	47	on	on	ADP
iajs-2563	67	48	jeffrey	jeffrey	PROPN
iajs-2563	67	49	's	's	PART
iajs-2563	67	50	prior	prior	ADJ
iajs-2563	67	51	can	can	AUX
iajs-2563	67	52	be	be	AUX
iajs-2563	67	53	approximated	approximate	VERB
iajs-2563	67	54	as	as	ADP
iajs-2563	67	55	�	�	PROPN
iajs-2563	67	56	̂	̂	X
iajs-2563	67	57	�	�	NOUN
iajs-2563	67	58	(𝑡)𝐸𝑛(𝐽	(𝑡)𝐸𝑛(𝐽	NOUN
iajs-2563	67	59	)	)	PUNCT
iajs-2563	68	1	≅	≅	PROPN
iajs-2563	68	2	1	1	NUM
iajs-2563	68	3	−	−	NOUN
iajs-2563	68	4	𝑒	𝑒	PROPN
iajs-2563	68	5	−	−	PROPN
iajs-2563	68	6	�	�	PROPN
iajs-2563	68	7	̂	̂	NOUN
iajs-2563	68	8	�	�	NOUN
iajs-2563	68	9	𝐸𝑛(𝐽	𝐸𝑛(𝐽	NOUN
iajs-2563	68	10	)	)	PUNCT
iajs-2563	68	11	𝑡2	𝑡2	PROPN
iajs-2563	68	12	�	�	PROPN
iajs-2563	68	13	̂	̂	PROPN
iajs-2563	68	14	�	�	NOUN
iajs-2563	68	15	(𝑡)𝐸𝑛(𝐽	(𝑡)𝐸𝑛(𝐽	NOUN
iajs-2563	68	16	)	)	PUNCT
iajs-2563	69	1	≅	≅	PROPN
iajs-2563	69	2	1	1	NUM
iajs-2563	69	3	−	−	NOUN
iajs-2563	69	4	𝑒	𝑒	PROPN
iajs-2563	69	5	−	−	PROPN
iajs-2563	69	6	𝑛−1	𝑛−1	PROPN
iajs-2563	69	7	𝑇𝑡2	𝑇𝑡2	NOUN
iajs-2563	69	8	(	(	PUNCT
iajs-2563	69	9	22	22	NUM
iajs-2563	69	10	)	)	PUNCT
iajs-2563	69	11	the	the	DET
iajs-2563	69	12	estimator	estimator	NOUN
iajs-2563	69	13	of	of	ADP
iajs-2563	69	14	the	the	DET
iajs-2563	69	15	reliability	reliability	NOUN
iajs-2563	69	16	function	function	NOUN
iajs-2563	69	17	based	base	VERB
iajs-2563	69	18	on	on	ADP
iajs-2563	69	19	exponential	exponential	NOUN
iajs-2563	69	20	prior	prior	ADV
iajs-2563	69	21	can	can	AUX
iajs-2563	69	22	be	be	AUX
iajs-2563	69	23	approximated	approximate	VERB
iajs-2563	69	24	as	as	ADP
iajs-2563	69	25	�	�	PROPN
iajs-2563	69	26	̂	̂	X
iajs-2563	69	27	�	�	NOUN
iajs-2563	69	28	(𝑡)𝐸𝑛(𝐸	(𝑡)𝐸𝑛(𝐸	NOUN
iajs-2563	69	29	)	)	PUNCT
iajs-2563	70	1	≅	≅	PROPN
iajs-2563	70	2	1	1	NUM
iajs-2563	70	3	−	−	NOUN
iajs-2563	70	4	𝑒	𝑒	PROPN
iajs-2563	70	5	−	−	PROPN
iajs-2563	70	6	�	�	PROPN
iajs-2563	70	7	̂	̂	NOUN
iajs-2563	70	8	�	�	PROPN
iajs-2563	70	9	𝐸𝑛	𝐸𝑛	ADP
iajs-2563	70	10	𝑡2	𝑡2	PROPN
iajs-2563	70	11	�	�	PROPN
iajs-2563	70	12	̂	̂	PROPN
iajs-2563	70	13	�	�	PROPN
iajs-2563	70	14	(𝑡)𝐸𝑛(𝐸	(𝑡)𝐸𝑛(𝐸	NOUN
iajs-2563	70	15	)	)	PUNCT
iajs-2563	71	1	≅	≅	PROPN
iajs-2563	71	2	1	1	NUM
iajs-2563	71	3	−	−	NOUN
iajs-2563	71	4	𝑒	𝑒	PROPN
iajs-2563	71	5	−	−	PROPN
iajs-2563	71	6	𝑛	𝑛	DET
iajs-2563	71	7	𝑝𝑡2	𝑝𝑡2	NOUN
iajs-2563	71	8	(	(	PUNCT
iajs-2563	71	9	23	23	NUM
iajs-2563	71	10	)	)	PUNCT
iajs-2563	71	11	130	130	NUM
iajs-2563	71	12	ibn	ibn	PROPN
iajs-2563	71	13	al	al	PROPN
iajs-2563	71	14	-	-	PUNCT
iajs-2563	71	15	haitham	haitham	PROPN
iajs-2563	71	16	jour	jour	X
iajs-2563	71	17	.	.	PROPN
iajs-2563	72	1	for	for	ADP
iajs-2563	72	2	pure	pure	ADJ
iajs-2563	72	3	&	&	CCONJ
iajs-2563	72	4	appl	appl	PROPN
iajs-2563	72	5	.	.	PUNCT
iajs-2563	73	1	sci	sci	PROPN
iajs-2563	73	2	.	.	PROPN
iajs-2563	74	1	34	34	NUM
iajs-2563	74	2	(	(	PUNCT
iajs-2563	74	3	1	1	NUM
iajs-2563	74	4	)	)	PUNCT
iajs-2563	74	5	2021	2021	NUM
iajs-2563	74	6	8	8	NUM
iajs-2563	74	7	.	.	PUNCT
iajs-2563	75	1	bayes	bayes	PROPN
iajs-2563	75	2	estimator	estimator	NOUN
iajs-2563	75	3	of	of	ADP
iajs-2563	75	4	the	the	DET
iajs-2563	75	5	parameter	parameter	NOUN
iajs-2563	75	6	𝜽	𝜽	ADP
iajs-2563	75	7	and	and	CCONJ
iajs-2563	75	8	reliability	reliability	NOUN
iajs-2563	75	9	function	function	NOUN
iajs-2563	75	10	under	under	ADP
iajs-2563	75	11	linex	linex	ADV
iajs-2563	75	12	by	by	ADP
iajs-2563	75	13	substituting	substitute	VERB
iajs-2563	75	14	from	from	ADP
iajs-2563	75	15	𝐿(𝜃	𝐿(𝜃	PROPN
iajs-2563	75	16	,	,	PUNCT
iajs-2563	75	17	𝜃	𝜃	NOUN
iajs-2563	75	18	)	)	PUNCT
iajs-2563	75	19	given	give	VERB
iajs-2563	75	20	in	in	ADP
iajs-2563	75	21	equation	equation	NOUN
iajs-2563	75	22	(	(	PUNCT
iajs-2563	75	23	17	17	NUM
iajs-2563	75	24	)	)	PUNCT
iajs-2563	75	25	into	into	ADP
iajs-2563	75	26	equation	equation	NOUN
iajs-2563	75	27	(	(	PUNCT
iajs-2563	75	28	18	18	NUM
iajs-2563	75	29	)	)	PUNCT
iajs-2563	75	30	,	,	PUNCT
iajs-2563	75	31	we	we	PRON
iajs-2563	75	32	get	get	VERB
iajs-2563	75	33	𝑅(𝜃	𝑅(𝜃	PRON
iajs-2563	75	34	,	,	PUNCT
iajs-2563	75	35	𝜃	𝜃	NOUN
iajs-2563	75	36	)	)	PUNCT
iajs-2563	75	37	=	=	SYM
iajs-2563	76	1	∫	∫	PROPN
iajs-2563	77	1	[	[	X
iajs-2563	77	2	𝑒(	𝑒(	X
iajs-2563	77	3	�	�	PROPN
iajs-2563	77	4	̂	̂	NOUN
iajs-2563	77	5	�	�	NOUN
iajs-2563	77	6	−𝜃	−𝜃	NOUN
iajs-2563	77	7	)	)	PUNCT
iajs-2563	77	8	−	−	PROPN
iajs-2563	78	1	(	(	PUNCT
iajs-2563	78	2	𝜃	𝜃	NOUN
iajs-2563	78	3	−	−	NOUN
iajs-2563	78	4	𝜃	𝜃	NOUN
iajs-2563	78	5	)	)	PUNCT
iajs-2563	78	6	−	−	NOUN
iajs-2563	79	1	1]ℎ(𝜃|𝑡)𝑑𝜃	1]ℎ(𝜃|𝑡)𝑑𝜃	NOUN
iajs-2563	79	2	∞	∞	PROPN
iajs-2563	79	3	0	0	NUM
iajs-2563	80	1	by	by	ADP
iajs-2563	80	2	simplification	simplification	NOUN
iajs-2563	80	3	,	,	PUNCT
iajs-2563	80	4	we	we	PRON
iajs-2563	80	5	get	get	VERB
iajs-2563	80	6	𝑒	𝑒	PROPN
iajs-2563	80	7	�	�	PROPN
iajs-2563	80	8	̂	̂	VERB
iajs-2563	80	9	�	�	PROPN
iajs-2563	80	10	∫	∫	PROPN
iajs-2563	80	11	𝑒−𝜃∞	𝑒−𝜃∞	PROPN
iajs-2563	80	12	0	0	NUM
iajs-2563	80	13	ℎ(𝜃|𝑡)𝑑𝜃	ℎ(𝜃|𝑡)𝑑𝜃	NOUN
iajs-2563	80	14	=	=	NOUN
iajs-2563	80	15	1	1	NUM
iajs-2563	80	16	by	by	ADP
iajs-2563	80	17	differentiating	differentiate	VERB
iajs-2563	80	18	𝑅(𝜃	𝑅(𝜃	NUM
iajs-2563	80	19	,	,	PUNCT
iajs-2563	80	20	𝜃	𝜃	NOUN
iajs-2563	80	21	)	)	PUNCT
iajs-2563	80	22	with	with	ADP
iajs-2563	80	23	respect	respect	NOUN
iajs-2563	80	24	to	to	ADP
iajs-2563	80	25	𝜃	𝜃	PRON
iajs-2563	80	26	then	then	ADV
iajs-2563	80	27	equating	equate	VERB
iajs-2563	80	28	the	the	DET
iajs-2563	80	29	resultant	resultant	NOUN
iajs-2563	80	30	derivative	derivative	NOUN
iajs-2563	80	31	to	to	ADP
iajs-2563	80	32	zero	zero	NUM
iajs-2563	80	33	and	and	CCONJ
iajs-2563	80	34	solving	solve	VERB
iajs-2563	80	35	for	for	ADP
iajs-2563	80	36	𝜃,̂	𝜃,̂	NOUN
iajs-2563	80	37	we	we	PRON
iajs-2563	80	38	get	get	VERB
iajs-2563	80	39	the	the	DET
iajs-2563	80	40	bayes	bayes	PROPN
iajs-2563	80	41	estimator	estimator	NOUN
iajs-2563	80	42	of	of	ADP
iajs-2563	80	43	𝜃	𝜃	NUM
iajs-2563	80	44	under	under	ADP
iajs-2563	80	45	linear	linear	ADJ
iajs-2563	80	46	exponential	exponential	ADJ
iajs-2563	80	47	loss	loss	NOUN
iajs-2563	80	48	function	function	NOUN
iajs-2563	80	49	denoted	denote	VERB
iajs-2563	80	50	by	by	ADP
iajs-2563	80	51	𝜃𝐿	𝜃𝐿	NOUN
iajs-2563	80	52	as	as	SCONJ
iajs-2563	80	53	follows	follow	VERB
iajs-2563	80	54	𝜃𝐿𝐸	𝜃𝐿𝐸	NOUN
iajs-2563	80	55	=	=	PUNCT
iajs-2563	80	56	−𝑙𝑛	−𝑙𝑛	X
iajs-2563	80	57	∫	∫	PROPN
iajs-2563	80	58	𝑒−𝜃∞	𝑒−𝜃∞	PROPN
iajs-2563	80	59	0	0	NUM
iajs-2563	80	60	ℎ(𝜃|𝑡)𝑑𝜃	ℎ(𝜃|𝑡)𝑑𝜃	NOUN
iajs-2563	80	61	on	on	ADP
iajs-2563	80	62	the	the	DET
iajs-2563	80	63	basis	basis	NOUN
iajs-2563	80	64	of	of	ADP
iajs-2563	80	65	non	non	ADJ
iajs-2563	80	66	-	-	ADJ
iajs-2563	80	67	informative	informative	ADJ
iajs-2563	80	68	prior	prior	NOUN
iajs-2563	80	69	,	,	PUNCT
iajs-2563	80	70	the	the	DET
iajs-2563	80	71	bayes	bayes	PROPN
iajs-2563	80	72	estimator	estimator	NOUN
iajs-2563	80	73	of	of	ADP
iajs-2563	80	74	the	the	DET
iajs-2563	80	75	inverse	inverse	NOUN
iajs-2563	80	76	rayleigh	rayleigh	PROPN
iajs-2563	80	77	parameter	parameter	PROPN
iajs-2563	81	1	𝜃	𝜃	PRON
iajs-2563	81	2	denoted	denote	VERB
iajs-2563	81	3	as	as	ADP
iajs-2563	81	4	𝜃𝐿𝐸(𝐽	𝜃𝐿𝐸(𝐽	PROPN
iajs-2563	81	5	)	)	PUNCT
iajs-2563	82	1	is	be	AUX
iajs-2563	82	2	given	give	VERB
iajs-2563	82	3	by	by	ADP
iajs-2563	82	4	𝜃𝐿𝐸(𝐽	𝜃𝐿𝐸(𝐽	PROPN
iajs-2563	82	5	)	)	PUNCT
iajs-2563	82	6	=	=	SYM
iajs-2563	83	1	−	−	PROPN
iajs-2563	83	2	ln	ln	INTJ
iajs-2563	83	3	(	(	PUNCT
iajs-2563	83	4	𝑇	𝑇	PROPN
iajs-2563	83	5	1+𝑇	1+𝑇	PROPN
iajs-2563	83	6	)	)	PUNCT
iajs-2563	83	7	𝑛	𝑛	PROPN
iajs-2563	83	8	(	(	PUNCT
iajs-2563	83	9	24	24	NUM
iajs-2563	83	10	)	)	PUNCT
iajs-2563	83	11	if	if	SCONJ
iajs-2563	83	12	the	the	DET
iajs-2563	83	13	inverse	inverse	NOUN
iajs-2563	83	14	rayleigh	rayleigh	PROPN
iajs-2563	83	15	parameter	parameter	PROPN
iajs-2563	83	16	follows	follow	VERB
iajs-2563	83	17	the	the	DET
iajs-2563	83	18	exponential	exponential	ADJ
iajs-2563	83	19	prior	prior	ADJ
iajs-2563	83	20	distribution	distribution	NOUN
iajs-2563	83	21	𝜃𝐿𝐸(𝐸	𝜃𝐿𝐸(𝐸	PUNCT
iajs-2563	83	22	)	)	PUNCT
iajs-2563	83	23	=	=	SYM
iajs-2563	84	1	−	−	PROPN
iajs-2563	84	2	ln	ln	INTJ
iajs-2563	84	3	(	(	PUNCT
iajs-2563	84	4	𝑃	𝑃	PROPN
iajs-2563	84	5	1+𝑃	1+𝑃	NUM
iajs-2563	84	6	)	)	PUNCT
iajs-2563	84	7	𝑛+1	𝑛+1	PROPN
iajs-2563	84	8	,	,	PUNCT
iajs-2563	84	9	(	(	PUNCT
iajs-2563	84	10	25	25	NUM
iajs-2563	84	11	)	)	PUNCT
iajs-2563	84	12	the	the	DET
iajs-2563	84	13	estimator	estimator	NOUN
iajs-2563	84	14	of	of	ADP
iajs-2563	84	15	the	the	DET
iajs-2563	84	16	reliability	reliability	NOUN
iajs-2563	84	17	function	function	NOUN
iajs-2563	84	18	based	base	VERB
iajs-2563	84	19	on	on	ADP
iajs-2563	84	20	jeffrey	jeffrey	PROPN
iajs-2563	84	21	's	's	PART
iajs-2563	84	22	prior	prior	ADJ
iajs-2563	84	23	can	can	AUX
iajs-2563	84	24	be	be	AUX
iajs-2563	84	25	approximated	approximate	VERB
iajs-2563	84	26	as	as	ADP
iajs-2563	84	27	�	�	PROPN
iajs-2563	84	28	̂	̂	VERB
iajs-2563	84	29	�	�	NOUN
iajs-2563	84	30	(𝑡)𝐿𝐸(𝐽	(𝑡)𝐿𝐸(𝐽	VERB
iajs-2563	84	31	)	)	PUNCT
iajs-2563	84	32	≅	≅	PROPN
iajs-2563	85	1	1	1	NUM
iajs-2563	85	2	−	−	NOUN
iajs-2563	85	3	𝑒	𝑒	PROPN
iajs-2563	85	4	−	−	PROPN
iajs-2563	85	5	�	�	PROPN
iajs-2563	85	6	̂	̂	NOUN
iajs-2563	85	7	�	�	NOUN
iajs-2563	85	8	𝐿𝐸(𝐽	𝐿𝐸(𝐽	ADJ
iajs-2563	85	9	)	)	PUNCT
iajs-2563	85	10	𝑡2	𝑡2	NOUN
iajs-2563	85	11	which	which	PRON
iajs-2563	85	12	implies	imply	VERB
iajs-2563	85	13	that	that	SCONJ
iajs-2563	85	14	�	�	PROPN
iajs-2563	85	15	̂	̂	VERB
iajs-2563	85	16	�	�	NOUN
iajs-2563	85	17	(𝑡)𝐿𝐸(𝐽	(𝑡)𝐿𝐸(𝐽	VERB
iajs-2563	85	18	)	)	PUNCT
iajs-2563	86	1	≅	≅	PROPN
iajs-2563	86	2	1	1	NUM
iajs-2563	86	3	−	−	NOUN
iajs-2563	86	4	𝑒	𝑒	PROPN
iajs-2563	86	5	−	−	PROPN
iajs-2563	86	6	𝑙𝑛	𝑙𝑛	NOUN
iajs-2563	86	7	(	(	PUNCT
iajs-2563	86	8	𝑇	𝑇	PROPN
iajs-2563	86	9	1+𝑇	1+𝑇	PROPN
iajs-2563	86	10	)	)	PUNCT
iajs-2563	86	11	𝑛	𝑛	DET
iajs-2563	86	12	𝑡2	𝑡2	PROPN
iajs-2563	86	13	�	�	PROPN
iajs-2563	86	14	̂	̂	VERB
iajs-2563	86	15	�	�	NOUN
iajs-2563	86	16	(𝑡)𝐿𝐸(𝐽	(𝑡)𝐿𝐸(𝐽	VERB
iajs-2563	86	17	)	)	PUNCT
iajs-2563	87	1	≅	≅	PROPN
iajs-2563	87	2	1	1	NUM
iajs-2563	87	3	−	−	PROPN
iajs-2563	87	4	(	(	PUNCT
iajs-2563	87	5	𝑇	𝑇	PROPN
iajs-2563	87	6	1+𝑇	1+𝑇	PROPN
iajs-2563	87	7	)	)	PUNCT
iajs-2563	88	1	𝑛	𝑛	DET
iajs-2563	88	2	𝑡2	𝑡2	NOUN
iajs-2563	88	3	(	(	PUNCT
iajs-2563	88	4	26	26	NUM
iajs-2563	88	5	)	)	PUNCT
iajs-2563	88	6	the	the	DET
iajs-2563	88	7	estimator	estimator	NOUN
iajs-2563	88	8	of	of	ADP
iajs-2563	88	9	the	the	DET
iajs-2563	88	10	reliability	reliability	NOUN
iajs-2563	88	11	function	function	NOUN
iajs-2563	88	12	based	base	VERB
iajs-2563	88	13	on	on	ADP
iajs-2563	88	14	exponential	exponential	NOUN
iajs-2563	88	15	prior	prior	ADV
iajs-2563	88	16	can	can	AUX
iajs-2563	88	17	be	be	AUX
iajs-2563	88	18	approximated	approximate	VERB
iajs-2563	88	19	as	as	ADP
iajs-2563	88	20	�	�	PROPN
iajs-2563	88	21	̂	̂	X
iajs-2563	88	22	�	�	NOUN
iajs-2563	88	23	(𝑡)𝐿𝐸(𝐸	(𝑡)𝐿𝐸(𝐸	SYM
iajs-2563	88	24	)	)	PUNCT
iajs-2563	89	1	≅	≅	PROPN
iajs-2563	89	2	1	1	NUM
iajs-2563	89	3	−	−	NOUN
iajs-2563	89	4	𝑒	𝑒	PROPN
iajs-2563	89	5	−	−	PROPN
iajs-2563	89	6	�	�	PROPN
iajs-2563	89	7	̂	̂	NOUN
iajs-2563	89	8	�	�	NOUN
iajs-2563	89	9	𝐿𝐸(𝐸	𝐿𝐸(𝐸	NOUN
iajs-2563	89	10	)	)	PUNCT
iajs-2563	89	11	𝑡2	𝑡2	NOUN
iajs-2563	89	12	which	which	PRON
iajs-2563	89	13	implies	imply	VERB
iajs-2563	89	14	that	that	SCONJ
iajs-2563	89	15	�	�	PROPN
iajs-2563	89	16	̂	̂	SYM
iajs-2563	89	17	�	�	NOUN
iajs-2563	89	18	(𝑡)𝐿𝐸(𝐸	(𝑡)𝐿𝐸(𝐸	SYM
iajs-2563	89	19	)	)	PUNCT
iajs-2563	90	1	≅	≅	PROPN
iajs-2563	90	2	1	1	NUM
iajs-2563	90	3	−	−	NOUN
iajs-2563	91	1	𝑒	𝑒	PROPN
iajs-2563	91	2	−	−	PROPN
iajs-2563	91	3	𝑙𝑛	𝑙𝑛	NOUN
iajs-2563	91	4	(	(	PUNCT
iajs-2563	91	5	𝑃	𝑃	PROPN
iajs-2563	91	6	1+𝑃	1+𝑃	NUM
iajs-2563	91	7	)	)	PUNCT
iajs-2563	91	8	𝑛+1	𝑛+1	PROPN
iajs-2563	91	9	𝑡2	𝑡2	PROPN
iajs-2563	91	10	�	�	PROPN
iajs-2563	91	11	̂	̂	PROPN
iajs-2563	91	12	�	�	NOUN
iajs-2563	91	13	(𝑡)𝐿𝐸(𝐸	(𝑡)𝐿𝐸(𝐸	SYM
iajs-2563	91	14	)	)	PUNCT
iajs-2563	92	1	≅	≅	PROPN
iajs-2563	92	2	1	1	NUM
iajs-2563	92	3	−	−	PROPN
iajs-2563	92	4	(	(	PUNCT
iajs-2563	92	5	𝑃	𝑃	PROPN
iajs-2563	92	6	1+𝑃	1+𝑃	NUM
iajs-2563	92	7	)	)	PUNCT
iajs-2563	92	8	𝑛+1	𝑛+1	ADP
iajs-2563	92	9	𝑡2	𝑡2	NOUN
iajs-2563	92	10	(	(	PUNCT
iajs-2563	92	11	27	27	NUM
iajs-2563	92	12	)	)	PUNCT
iajs-2563	92	13	131	131	NUM
iajs-2563	92	14	ibn	ibn	PROPN
iajs-2563	92	15	al	al	PROPN
iajs-2563	92	16	-	-	PUNCT
iajs-2563	92	17	haitham	haitham	PROPN
iajs-2563	92	18	jour	jour	X
iajs-2563	92	19	.	.	PROPN
iajs-2563	93	1	for	for	ADP
iajs-2563	93	2	pure	pure	ADJ
iajs-2563	93	3	&	&	CCONJ
iajs-2563	93	4	appl	appl	PROPN
iajs-2563	93	5	.	.	PUNCT
iajs-2563	94	1	sci	sci	PROPN
iajs-2563	94	2	.	.	PROPN
iajs-2563	95	1	34	34	NUM
iajs-2563	95	2	(	(	PUNCT
iajs-2563	95	3	1	1	NUM
iajs-2563	95	4	)	)	PUNCT
iajs-2563	95	5	2021	2021	NUM
iajs-2563	95	6	10	10	NUM
iajs-2563	95	7	.	.	PUNCT
iajs-2563	96	1	simulation	simulation	NOUN
iajs-2563	96	2	study	study	NOUN
iajs-2563	96	3	in	in	ADP
iajs-2563	96	4	our	our	PRON
iajs-2563	96	5	simulation	simulation	NOUN
iajs-2563	96	6	study	study	NOUN
iajs-2563	96	7	,	,	PUNCT
iajs-2563	96	8	number	number	NOUN
iajs-2563	96	9	of	of	ADP
iajs-2563	96	10	repetitions	repetition	NOUN
iajs-2563	96	11	l=2000	l=2000	PROPN
iajs-2563	96	12	sample	sample	NOUN
iajs-2563	96	13	of	of	ADP
iajs-2563	96	14	size	size	NOUN
iajs-2563	96	15	n=10,50,100	n=10,50,100	PROPN
iajs-2563	96	16	and	and	CCONJ
iajs-2563	96	17	200	200	NUM
iajs-2563	96	18	are	be	AUX
iajs-2563	96	19	generated	generate	VERB
iajs-2563	96	20	in	in	ADP
iajs-2563	96	21	order	order	NOUN
iajs-2563	96	22	to	to	PART
iajs-2563	96	23	represent	represent	VERB
iajs-2563	96	24	,	,	PUNCT
iajs-2563	96	25	small	small	ADJ
iajs-2563	96	26	,	,	PUNCT
iajs-2563	96	27	moderate	moderate	ADJ
iajs-2563	96	28	,	,	PUNCT
iajs-2563	96	29	large	large	ADJ
iajs-2563	96	30	and	and	CCONJ
iajs-2563	96	31	very	very	ADV
iajs-2563	96	32	large	large	ADJ
iajs-2563	96	33	sample	sample	NOUN
iajs-2563	96	34	sizes	size	NOUN
iajs-2563	96	35	from	from	ADP
iajs-2563	96	36	inverse	inverse	ADJ
iajs-2563	96	37	rayleigh	rayleigh	NOUN
iajs-2563	96	38	distribution	distribution	NOUN
iajs-2563	96	39	with	with	ADP
iajs-2563	96	40	two	two	NUM
iajs-2563	96	41	values	value	NOUN
iajs-2563	96	42	of	of	ADP
iajs-2563	96	43	the	the	DET
iajs-2563	96	44	scale	scale	NOUN
iajs-2563	96	45	parameter	parameter	NOUN
iajs-2563	96	46	(	(	PUNCT
iajs-2563	96	47	𝛳	𝛳	NOUN
iajs-2563	96	48	=	=	SYM
iajs-2563	96	49	0.5	0.5	NUM
iajs-2563	96	50	,	,	PUNCT
iajs-2563	96	51	𝛳	𝛳	PROPN
iajs-2563	96	52	=	=	SYM
iajs-2563	96	53	1.5	1.5	NUM
iajs-2563	96	54	)	)	PUNCT
iajs-2563	96	55	,	,	PUNCT
iajs-2563	96	56	the	the	DET
iajs-2563	96	57	scale	scale	NOUN
iajs-2563	96	58	parameter	parameter	NOUN
iajs-2563	96	59	λ	λ	PROPN
iajs-2563	96	60	of	of	ADP
iajs-2563	96	61	exponential	exponential	NOUN
iajs-2563	96	62	prior	prior	ADV
iajs-2563	96	63	was	be	AUX
iajs-2563	96	64	chosen	choose	VERB
iajs-2563	96	65	to	to	PART
iajs-2563	96	66	be	be	AUX
iajs-2563	96	67	(	(	PUNCT
iajs-2563	96	68	λ=0.5	λ=0.5	NOUN
iajs-2563	96	69	,	,	PUNCT
iajs-2563	96	70	λ=1	λ=1	PRON
iajs-2563	96	71	)	)	PUNCT
iajs-2563	96	72	and	and	CCONJ
iajs-2563	96	73	mean	mean	VERB
iajs-2563	96	74	square	square	ADJ
iajs-2563	96	75	error	error	NOUN
iajs-2563	96	76	(	(	PUNCT
iajs-2563	96	77	mse	mse	NOUN
iajs-2563	96	78	)	)	PUNCT
iajs-2563	96	79	is	be	AUX
iajs-2563	96	80	employed	employ	VERB
iajs-2563	96	81	to	to	PART
iajs-2563	96	82	compare	compare	VERB
iajs-2563	96	83	the	the	DET
iajs-2563	96	84	performance	performance	NOUN
iajs-2563	96	85	of	of	ADP
iajs-2563	96	86	different	different	ADJ
iajs-2563	96	87	methods	method	NOUN
iajs-2563	96	88	for	for	ADP
iajs-2563	96	89	estimation	estimation	NOUN
iajs-2563	96	90	of	of	ADP
iajs-2563	96	91	the	the	DET
iajs-2563	96	92	scale	scale	NOUN
iajs-2563	96	93	parameter	parameter	NOUN
iajs-2563	96	94	and	and	CCONJ
iajs-2563	96	95	reliability	reliability	NOUN
iajs-2563	96	96	function	function	NOUN
iajs-2563	96	97	of	of	ADP
iajs-2563	96	98	ird	ird	PROPN
iajs-2563	96	99	where	where	SCONJ
iajs-2563	96	100	𝑀𝑆𝐸(𝜃	𝑀𝑆𝐸(𝜃	NOUN
iajs-2563	96	101	)	)	PUNCT
iajs-2563	96	102	=	=	SYM
iajs-2563	96	103	1	1	NUM
iajs-2563	96	104	𝐿	𝐿	PROPN
iajs-2563	96	105	∑	∑	PROPN
iajs-2563	96	106	(	(	PUNCT
iajs-2563	96	107	𝜃𝑖	𝜃𝑖	PRON
iajs-2563	96	108	−	−	X
iajs-2563	96	109	𝜃)2𝐿	𝜃)2𝐿	X
iajs-2563	96	110	𝑖=1	𝑖=1	PROPN
iajs-2563	96	111	(	(	PUNCT
iajs-2563	96	112	28	28	NUM
iajs-2563	96	113	)	)	PUNCT
iajs-2563	96	114	𝑀𝑆𝐸[	𝑀𝑆𝐸[	NOUN
iajs-2563	96	115	�	�	PROPN
iajs-2563	96	116	̂	̂	NOUN
iajs-2563	96	117	�	�	NOUN
iajs-2563	96	118	(𝑡	(𝑡	NOUN
iajs-2563	96	119	)	)	PUNCT
iajs-2563	96	120	]	]	PUNCT
iajs-2563	97	1	=	=	SYM
iajs-2563	97	2	1	1	NUM
iajs-2563	97	3	𝐿	𝐿	PROPN
iajs-2563	97	4	∑	∑	PROPN
iajs-2563	97	5	[	[	X
iajs-2563	97	6	�	�	NOUN
iajs-2563	97	7	̂	̂	SYM
iajs-2563	97	8	�	�	NOUN
iajs-2563	97	9	𝑖(𝑡	𝑖(𝑡	NUM
iajs-2563	97	10	)	)	PUNCT
iajs-2563	97	11	−	−	NOUN
iajs-2563	97	12	𝑅(𝑡)]2𝐿	𝑅(𝑡)]2𝐿	VERB
iajs-2563	97	13	𝑖=1	𝑖=1	PROPN
iajs-2563	97	14	(	(	PUNCT
iajs-2563	97	15	29	29	NUM
iajs-2563	97	16	)	)	PUNCT
iajs-2563	97	17	the	the	DET
iajs-2563	97	18	results	result	NOUN
iajs-2563	97	19	are	be	AUX
iajs-2563	97	20	presented	present	VERB
iajs-2563	97	21	in	in	ADP
iajs-2563	97	22	the	the	DET
iajs-2563	97	23	following	follow	VERB
iajs-2563	97	24	tables	table	NOUN
iajs-2563	97	25	(	(	PUNCT
iajs-2563	97	26	1	1	NUM
iajs-2563	97	27	-	-	SYM
iajs-2563	97	28	8)	8)	NUM
iajs-2563	97	29	.	.	PUNCT
iajs-2563	97	30	table	table	NOUN
iajs-2563	97	31	1	1	NUM
iajs-2563	97	32	.	.	X
iajs-2563	97	33	mse	mse	PROPN
iajs-2563	97	34	for	for	ADP
iajs-2563	97	35	parameter	parameter	NOUN
iajs-2563	97	36	𝜃	𝜃	NUM
iajs-2563	97	37	by	by	ADP
iajs-2563	97	38	using	use	VERB
iajs-2563	97	39	jeffrey	jeffrey	PROPN
iajs-2563	97	40	's	's	PART
iajs-2563	97	41	prior	prior	ADJ
iajs-2563	97	42	information	information	NOUN
iajs-2563	97	43	at	at	ADP
iajs-2563	97	44	𝜃	𝜃	NOUN
iajs-2563	97	45	=	=	SYM
iajs-2563	97	46	0.5	0.5	NUM
iajs-2563	97	47	n	n	NOUN
iajs-2563	97	48	estimator	estimator	NOUN
iajs-2563	97	49	10	10	NUM
iajs-2563	97	50	50	50	NUM
iajs-2563	97	51	100	100	NUM
iajs-2563	97	52	200	200	NUM
iajs-2563	97	53	mle	mle	NOUN
iajs-2563	97	54	0.0043	0.0043	NUM
iajs-2563	97	55	0.0001082	0.0001082	NUM
iajs-2563	97	56	0.000026176	0.000026176	NUM
iajs-2563	97	57	0.000006513	0.000006513	NUM
iajs-2563	97	58	ent	ent	NOUN
iajs-2563	97	59	0.0033	0.0033	NUM
iajs-2563	97	60	0.0001019	0.0001019	NUM
iajs-2563	97	61	0.000025396	0.000025396	NUM
iajs-2563	97	62	0.000006412	0.000006412	NUM
iajs-2563	97	63	lin	lin	PROPN
iajs-2563	97	64	0.0250	0.0250	NUM
iajs-2563	97	65	0.0050	0.0050	NUM
iajs-2563	97	66	0.0025	0.0025	NUM
iajs-2563	97	67	0.0013	0.0013	NUM
iajs-2563	97	68	best	good	ADJ
iajs-2563	97	69	ent	ent	PROPN
iajs-2563	97	70	ent	ent	PROPN
iajs-2563	97	71	ent	ent	PROPN
iajs-2563	97	72	ent	ent	PROPN
iajs-2563	97	73	table	table	NOUN
iajs-2563	97	74	2	2	NUM
iajs-2563	97	75	.	.	PUNCT
iajs-2563	97	76	mse	mse	NOUN
iajs-2563	97	77	values	value	NOUN
iajs-2563	97	78	of	of	ADP
iajs-2563	97	79	the	the	DET
iajs-2563	97	80	reliability	reliability	NOUN
iajs-2563	97	81	function	function	NOUN
iajs-2563	97	82	estimators	estimator	NOUN
iajs-2563	97	83	by	by	ADP
iajs-2563	97	84	using	use	VERB
iajs-2563	97	85	jeffrey	jeffrey	PROPN
iajs-2563	97	86	's	's	PART
iajs-2563	97	87	prior	prior	ADJ
iajs-2563	97	88	information	information	NOUN
iajs-2563	97	89	at	at	ADP
iajs-2563	97	90	𝜃	𝜃	NOUN
iajs-2563	97	91	=	=	SYM
iajs-2563	97	92	0.5	0.5	NUM
iajs-2563	97	93	n	n	NOUN
iajs-2563	97	94	estimator	estimator	NOUN
iajs-2563	97	95	10	10	NUM
iajs-2563	97	96	50	50	NUM
iajs-2563	97	97	100	100	NUM
iajs-2563	97	98	200	200	NUM
iajs-2563	97	99	mle	mle	NOUN
iajs-2563	97	100	0.000321	0.000321	NUM
iajs-2563	97	101	0.0000101	0.0000101	NUM
iajs-2563	97	102	0.0000024924	0.0000024924	NUM
iajs-2563	97	103	0.0000006246	0.0000006246	NUM
iajs-2563	97	104	ent	ent	NOUN
iajs-2563	97	105	0.000269	0.000269	NUM
iajs-2563	97	106	0.0000097	0.0000097	NUM
iajs-2563	97	107	0.0000024460	0.0000024460	NUM
iajs-2563	97	108	0.0000006185	0.0000006185	NUM
iajs-2563	97	109	lin	lin	PROPN
iajs-2563	97	110	0.000283	0.000283	NUM
iajs-2563	97	111	0.0000098	0.0000098	NUM
iajs-2563	97	112	0.0000024635	0.0000024635	NUM
iajs-2563	97	113	0.0000006209	0.0000006209	NUM
iajs-2563	97	114	best	good	ADJ
iajs-2563	97	115	ent	ent	PROPN
iajs-2563	97	116	ent	ent	PROPN
iajs-2563	97	117	ent	ent	PROPN
iajs-2563	97	118	ent	ent	PROPN
iajs-2563	97	119	132	132	NUM
iajs-2563	97	120	ibn	ibn	PROPN
iajs-2563	97	121	al	al	PROPN
iajs-2563	97	122	-	-	PUNCT
iajs-2563	97	123	haitham	haitham	PROPN
iajs-2563	97	124	jour	jour	X
iajs-2563	97	125	.	.	PROPN
iajs-2563	97	126	for	for	ADP
iajs-2563	97	127	pure	pure	ADJ
iajs-2563	97	128	&	&	CCONJ
iajs-2563	97	129	appl	appl	PROPN
iajs-2563	97	130	.	.	PUNCT
iajs-2563	98	1	sci	sci	PROPN
iajs-2563	98	2	.	.	PROPN
iajs-2563	99	1	34	34	NUM
iajs-2563	99	2	(	(	PUNCT
iajs-2563	99	3	1	1	NUM
iajs-2563	99	4	)	)	PUNCT
iajs-2563	99	5	2021	2021	NUM
iajs-2563	99	6	table	table	NOUN
iajs-2563	99	7	3	3	NUM
iajs-2563	99	8	.	.	X
iajs-2563	99	9	mse	mse	PROPN
iajs-2563	99	10	for	for	ADP
iajs-2563	99	11	parameter	parameter	NOUN
iajs-2563	99	12	𝜃	𝜃	NUM
iajs-2563	99	13	by	by	ADP
iajs-2563	99	14	using	use	VERB
iajs-2563	99	15	exponential	exponential	ADJ
iajs-2563	99	16	prior	prior	ADJ
iajs-2563	99	17	information	information	NOUN
iajs-2563	99	18	at	at	ADP
iajs-2563	99	19	𝜃	𝜃	NOUN
iajs-2563	99	20	=	=	SYM
iajs-2563	99	21	0.5	0.5	NUM
iajs-2563	99	22	n	n	NOUN
iajs-2563	99	23	estimator	estimator	NOUN
iajs-2563	99	24	10	10	NUM
iajs-2563	99	25	50	50	NUM
iajs-2563	99	26	100	100	NUM
iajs-2563	99	27	200	200	NUM
iajs-2563	99	28	ent	ent	NOUN
iajs-2563	99	29	𝜆	𝜆	NOUN
iajs-2563	99	30	=	=	SYM
iajs-2563	99	31	0.5	0.5	NUM
iajs-2563	99	32	0.2810	0.2810	NUM
iajs-2563	99	33	0.0472	0.0472	NUM
iajs-2563	99	34	0.0231	0.0231	NUM
iajs-2563	99	35	0.0114	0.0114	NUM
iajs-2563	99	36	𝜆	𝜆	PUNCT
iajs-2563	99	37	=	=	SYM
iajs-2563	99	38	1	1	NUM
iajs-2563	99	39	0.2968	0.2968	NUM
iajs-2563	99	40	0.0479	0.0479	NUM
iajs-2563	99	41	0.0232	0.0232	NUM
iajs-2563	99	42	0.0114	0.0114	NUM
iajs-2563	99	43	lin	lin	PROPN
iajs-2563	99	44	𝜆	𝜆	NOUN
iajs-2563	100	1	=	=	SYM
iajs-2563	100	2	0.5	0.5	NUM
iajs-2563	100	3	0.0250	0.0250	NUM
iajs-2563	100	4	0.0050	0.0050	NUM
iajs-2563	100	5	0.0025	0.0025	NUM
iajs-2563	100	6	0.0013	0.0013	NUM
iajs-2563	100	7	𝜆	𝜆	NOUN
iajs-2563	100	8	=	=	SYM
iajs-2563	100	9	1	1	NUM
iajs-2563	100	10	0.0250	0.0250	NUM
iajs-2563	100	11	0.0050	0.0050	NUM
iajs-2563	100	12	0.0025	0.0025	NUM
iajs-2563	100	13	0.0013	0.0013	NUM
iajs-2563	100	14	best	good	ADJ
iajs-2563	100	15	lin	lin	PROPN
iajs-2563	100	16	lin	lin	PROPN
iajs-2563	100	17	lin	lin	PROPN
iajs-2563	100	18	lin	lin	PROPN
iajs-2563	100	19	table	table	PROPN
iajs-2563	100	20	4	4	NUM
iajs-2563	100	21	.	.	PUNCT
iajs-2563	101	1	mse	mse	NOUN
iajs-2563	101	2	values	value	NOUN
iajs-2563	101	3	of	of	ADP
iajs-2563	101	4	the	the	DET
iajs-2563	101	5	reliability	reliability	NOUN
iajs-2563	101	6	function	function	NOUN
iajs-2563	101	7	estimators	estimator	NOUN
iajs-2563	101	8	by	by	ADP
iajs-2563	101	9	using	use	VERB
iajs-2563	101	10	exponential	exponential	ADJ
iajs-2563	101	11	prior	prior	ADJ
iajs-2563	101	12	information	information	NOUN
iajs-2563	101	13	at	at	ADP
iajs-2563	101	14	𝜃	𝜃	NOUN
iajs-2563	101	15	=	=	SYM
iajs-2563	101	16	0.5	0.5	NUM
iajs-2563	101	17	n	n	NOUN
iajs-2563	101	18	estimator	estimator	NOUN
iajs-2563	101	19	10	10	NUM
iajs-2563	101	20	50	50	NUM
iajs-2563	101	21	100	100	NUM
iajs-2563	101	22	200	200	NUM
iajs-2563	101	23	ent	ent	NOUN
iajs-2563	101	24	𝜆	𝜆	NOUN
iajs-2563	101	25	=	=	SYM
iajs-2563	101	26	0.5	0.5	NUM
iajs-2563	101	27	0.0090	0.0090	NUM
iajs-2563	101	28	0.0018	0.0018	NUM
iajs-2563	101	29	0.00087303	0.00087303	NUM
iajs-2563	101	30	0.00043568	0.00043568	NUM
iajs-2563	101	31	𝜆	𝜆	NOUN
iajs-2563	101	32	=	=	SYM
iajs-2563	101	33	1	1	NUM
iajs-2563	101	34	0.0094	0.0094	NUM
iajs-2563	101	35	0.0018	0.0018	NUM
iajs-2563	101	36	0.00087669	0.00087669	NUM
iajs-2563	101	37	0.00043659	0.00043659	NUM
iajs-2563	101	38	lin	lin	PROPN
iajs-2563	101	39	𝜆	𝜆	NOUN
iajs-2563	102	1	=	=	SYM
iajs-2563	102	2	0.5	0.5	NUM
iajs-2563	102	3	0.000317	0.000317	NUM
iajs-2563	102	4	0.0000101	0.0000101	NUM
iajs-2563	102	5	0.0000025078	0.0000025078	NUM
iajs-2563	102	6	0.0000006267	0.0000006267	NUM
iajs-2563	102	7	𝜆	𝜆	X
iajs-2563	102	8	=	=	SYM
iajs-2563	102	9	1	1	NUM
iajs-2563	102	10	0.000278	0.000278	NUM
iajs-2563	102	11	0.0000098	0.0000098	NUM
iajs-2563	102	12	0.0000024731	0.0000024731	NUM
iajs-2563	102	13	0.0000006223	0.0000006223	NUM
iajs-2563	102	14	best	good	ADJ
iajs-2563	102	15	lin	lin	PROPN
iajs-2563	102	16	lin	lin	PROPN
iajs-2563	102	17	lin	lin	PROPN
iajs-2563	102	18	lin	lin	PROPN
iajs-2563	102	19	table	table	PROPN
iajs-2563	102	20	5	5	NUM
iajs-2563	102	21	.	.	PUNCT
iajs-2563	102	22	mse	mse	PROPN
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iajs-2563	102	24	parameter	parameter	NOUN
iajs-2563	102	25	𝜃	𝜃	NUM
iajs-2563	102	26	by	by	ADP
iajs-2563	102	27	using	use	VERB
iajs-2563	102	28	jeffrey	jeffrey	PROPN
iajs-2563	102	29	's	's	PART
iajs-2563	102	30	prior	prior	ADJ
iajs-2563	102	31	information	information	NOUN
iajs-2563	102	32	at	at	ADP
iajs-2563	102	33	𝜃	𝜃	NOUN
iajs-2563	102	34	=	=	SYM
iajs-2563	102	35	1.5	1.5	NUM
iajs-2563	102	36	n	n	NOUN
iajs-2563	102	37	estimator	estimator	NOUN
iajs-2563	102	38	10	10	NUM
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iajs-2563	102	40	100	100	NUM
iajs-2563	102	41	200	200	NUM
iajs-2563	102	42	mle	mle	NOUN
iajs-2563	102	43	0.0391	0.0391	NUM
iajs-2563	102	44	0.00097346	0.00097346	NUM
iajs-2563	102	45	0.00023557	0.00023557	NUM
iajs-2563	102	46	0.00005862	0.00005862	NUM
iajs-2563	102	47	ent	ent	NOUN
iajs-2563	102	48	0.0293	0.0293	NUM
iajs-2563	102	49	0.00091708	0.00091708	NUM
iajs-2563	102	50	0.00022856	0.00022856	NUM
iajs-2563	102	51	0.000057715	0.000057715	NUM
iajs-2563	102	52	lin	lin	PROPN
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iajs-2563	102	55	0.0225	0.0225	NUM
iajs-2563	102	56	0.0113	0.0113	NUM
iajs-2563	102	57	best	good	ADJ
iajs-2563	102	58	ent	ent	PROPN
iajs-2563	102	59	ent	ent	PROPN
iajs-2563	102	60	ent	ent	PROPN
iajs-2563	102	61	ent	ent	PROPN
iajs-2563	102	62	133	133	NUM
iajs-2563	102	63	ibn	ibn	PROPN
iajs-2563	102	64	al	al	PROPN
iajs-2563	102	65	-	-	PUNCT
iajs-2563	102	66	haitham	haitham	PROPN
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iajs-2563	102	68	.	.	PROPN
iajs-2563	103	1	for	for	ADP
iajs-2563	103	2	pure	pure	ADJ
iajs-2563	103	3	&	&	CCONJ
iajs-2563	103	4	appl	appl	PROPN
iajs-2563	103	5	.	.	PUNCT
iajs-2563	104	1	sci	sci	PROPN
iajs-2563	104	2	.	.	PROPN
iajs-2563	105	1	34	34	NUM
iajs-2563	105	2	(	(	PUNCT
iajs-2563	105	3	1	1	NUM
iajs-2563	105	4	)	)	PUNCT
iajs-2563	105	5	2021	2021	NUM
iajs-2563	105	6	table	table	NOUN
iajs-2563	105	7	6	6	NUM
iajs-2563	105	8	.	.	PUNCT
iajs-2563	106	1	mse	mse	NOUN
iajs-2563	106	2	values	value	NOUN
iajs-2563	106	3	of	of	ADP
iajs-2563	106	4	the	the	DET
iajs-2563	106	5	reliability	reliability	NOUN
iajs-2563	106	6	function	function	NOUN
iajs-2563	106	7	estimators	estimator	NOUN
iajs-2563	106	8	by	by	ADP
iajs-2563	106	9	using	use	VERB
iajs-2563	106	10	jeffrey	jeffrey	PROPN
iajs-2563	106	11	's	's	PART
iajs-2563	106	12	prior	prior	ADJ
iajs-2563	106	13	information	information	NOUN
iajs-2563	106	14	at	at	ADP
iajs-2563	106	15	𝜃	𝜃	NOUN
iajs-2563	106	16	=	=	SYM
iajs-2563	106	17	1.5	1.5	NUM
iajs-2563	106	18	n	n	NOUN
iajs-2563	106	19	estimator	estimator	NOUN
iajs-2563	106	20	10	10	NUM
iajs-2563	106	21	50	50	NUM
iajs-2563	106	22	100	100	NUM
iajs-2563	106	23	200	200	NUM
iajs-2563	106	24	mle	mle	NOUN
iajs-2563	106	25	0.000691	0.000691	NUM
iajs-2563	106	26	0.000024581	0.000024581	NUM
iajs-2563	106	27	0.0000061457	0.0000061457	NUM
iajs-2563	106	28	0.0000015451	0.0000015451	NUM
iajs-2563	106	29	ent	ent	NOUN
iajs-2563	106	30	0.000647	0.000647	NUM
iajs-2563	106	31	0.000024264	0.000024264	NUM
iajs-2563	106	32	0.0000061043	0.0000061043	NUM
iajs-2563	106	33	0.0000015393	0.0000015393	NUM
iajs-2563	106	34	lin	lin	PROPN
iajs-2563	106	35	0.000551	0.000551	NUM
iajs-2563	106	36	0.000023534	0.000023534	NUM
iajs-2563	106	37	0.0000060124	0.0000060124	NUM
iajs-2563	106	38	0.0000015278	0.0000015278	NUM
iajs-2563	106	39	best	good	ADJ
iajs-2563	106	40	lin	lin	PROPN
iajs-2563	106	41	lin	lin	PROPN
iajs-2563	106	42	lin	lin	PROPN
iajs-2563	106	43	lin	lin	PROPN
iajs-2563	106	44	table	table	PROPN
iajs-2563	106	45	7	7	NUM
iajs-2563	106	46	.	.	PUNCT
iajs-2563	106	47	mse	mse	PROPN
iajs-2563	106	48	for	for	ADP
iajs-2563	106	49	parameter	parameter	NOUN
iajs-2563	106	50	𝜃	𝜃	NUM
iajs-2563	106	51	by	by	ADP
iajs-2563	106	52	using	use	VERB
iajs-2563	106	53	exponential	exponential	ADJ
iajs-2563	106	54	prior	prior	ADJ
iajs-2563	106	55	information	information	NOUN
iajs-2563	106	56	at	at	ADP
iajs-2563	106	57	𝜃	𝜃	NOUN
iajs-2563	106	58	=	=	SYM
iajs-2563	106	59	1.5	1.5	NUM
iajs-2563	106	60	n	n	NOUN
iajs-2563	106	61	estimator	estimator	NOUN
iajs-2563	106	62	10	10	NUM
iajs-2563	106	63	50	50	NUM
iajs-2563	106	64	100	100	NUM
iajs-2563	106	65	200	200	NUM
iajs-2563	106	66	ent	ent	NOUN
iajs-2563	106	67	𝜆	𝜆	NOUN
iajs-2563	106	68	=	=	SYM
iajs-2563	106	69	0.5	0.5	NUM
iajs-2563	106	70	0.0660	0.0660	NUM
iajs-2563	106	71	0.0137	0.0137	NUM
iajs-2563	106	72	0.0069	0.0069	NUM
iajs-2563	106	73	0.0035	0.0035	NUM
iajs-2563	106	74	𝜆	𝜆	X
iajs-2563	106	75	=	=	SYM
iajs-2563	106	76	1	1	NUM
iajs-2563	106	77	0.0584	0.0584	NUM
iajs-2563	106	78	0.0134	0.0134	NUM
iajs-2563	106	79	0.0068	0.0068	NUM
iajs-2563	106	80	0.0034	0.0034	NUM
iajs-2563	106	81	lin	lin	PROPN
iajs-2563	106	82	𝜆	𝜆	NOUN
iajs-2563	107	1	=	=	SYM
iajs-2563	107	2	0.5	0.5	NUM
iajs-2563	107	3	0.2250	0.2250	NUM
iajs-2563	107	4	0.0450	0.0450	NUM
iajs-2563	107	5	0.0225	0.0225	NUM
iajs-2563	107	6	0.0113	0.0113	NUM
iajs-2563	107	7	𝜆	𝜆	NOUN
iajs-2563	107	8	=	=	SYM
iajs-2563	107	9	1	1	NUM
iajs-2563	107	10	0.2250	0.2250	NUM
iajs-2563	107	11	0.0450	0.0450	NUM
iajs-2563	107	12	0.0225	0.0225	NUM
iajs-2563	107	13	0.0113	0.0113	NUM
iajs-2563	107	14	best	good	ADJ
iajs-2563	107	15	ent	ent	PROPN
iajs-2563	107	16	ent	ent	PROPN
iajs-2563	107	17	ent	ent	PROPN
iajs-2563	107	18	ent	ent	PROPN
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iajs-2563	107	20	8	8	NUM
iajs-2563	107	21	.	.	PUNCT
iajs-2563	107	22	mse	mse	NOUN
iajs-2563	107	23	values	value	NOUN
iajs-2563	107	24	of	of	ADP
iajs-2563	107	25	the	the	DET
iajs-2563	107	26	reliability	reliability	NOUN
iajs-2563	107	27	function	function	NOUN
iajs-2563	107	28	estimators	estimator	NOUN
iajs-2563	107	29	by	by	ADP
iajs-2563	107	30	using	use	VERB
iajs-2563	107	31	exponential	exponential	ADJ
iajs-2563	107	32	prior	prior	ADJ
iajs-2563	107	33	information	information	NOUN
iajs-2563	107	34	at	at	ADP
iajs-2563	107	35	𝜃	𝜃	NOUN
iajs-2563	107	36	=	=	SYM
iajs-2563	107	37	1.5	1.5	NUM
iajs-2563	107	38	n	n	NOUN
iajs-2563	107	39	estimator	estimator	NOUN
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iajs-2563	107	41	50	50	NUM
iajs-2563	107	42	100	100	NUM
iajs-2563	107	43	200	200	NUM
iajs-2563	107	44	ent	ent	NOUN
iajs-2563	107	45	𝜆	𝜆	NOUN
iajs-2563	107	46	=	=	SYM
iajs-2563	107	47	0.5	0.5	NUM
iajs-2563	107	48	0.00310	0.00310	NUM
iajs-2563	107	49	0.00061919	0.00061919	NUM
iajs-2563	107	50	0.00030974	0.00030974	NUM
iajs-2563	107	51	0.00015491	0.00015491	NUM
iajs-2563	107	52	𝜆	𝜆	X
iajs-2563	107	53	=	=	SYM
iajs-2563	107	54	1	1	NUM
iajs-2563	107	55	0.00260	0.00260	NUM
iajs-2563	107	56	0.00060029	0.00060029	NUM
iajs-2563	107	57	0.00030498	0.00030498	NUM
iajs-2563	107	58	0.0000015371	0.0000015371	NUM
iajs-2563	107	59	lin	lin	PROPN
iajs-2563	107	60	𝜆	𝜆	NOUN
iajs-2563	107	61	=	=	SYM
iajs-2563	107	62	0.5	0.5	NUM
iajs-2563	107	63	0.000474	0.000474	NUM
iajs-2563	107	64	0.000022883	0.000022883	NUM
iajs-2563	107	65	0.0000059292	0.0000059292	NUM
iajs-2563	107	66	0.000001517	0.000001517	NUM
iajs-2563	107	67	𝜆	𝜆	X
iajs-2563	107	68	=	=	SYM
iajs-2563	107	69	1	1	NUM
iajs-2563	107	70	0.000423	0.000423	NUM
iajs-2563	107	71	0.00002227	0.00002227	NUM
iajs-2563	107	72	0.0000058461	0.0000058461	NUM
iajs-2563	107	73	0.000001506	0.000001506	NUM
iajs-2563	107	74	best	good	ADJ
iajs-2563	107	75	lin	lin	PROPN
iajs-2563	107	76	lin	lin	PROPN
iajs-2563	107	77	lin	lin	PROPN
iajs-2563	107	78	lin	lin	PROPN
iajs-2563	107	79	11	11	NUM
iajs-2563	107	80	.	.	PUNCT
iajs-2563	108	1	simulation	simulation	NOUN
iajs-2563	108	2	results	result	NOUN
iajs-2563	108	3	and	and	CCONJ
iajs-2563	108	4	conclusions	conclusion	NOUN
iajs-2563	108	5	from	from	ADP
iajs-2563	108	6	our	our	PRON
iajs-2563	108	7	simulation	simulation	NOUN
iajs-2563	108	8	study	study	NOUN
iajs-2563	108	9	,	,	PUNCT
iajs-2563	108	10	the	the	DET
iajs-2563	108	11	following	follow	VERB
iajs-2563	108	12	conclusions	conclusion	NOUN
iajs-2563	108	13	are	be	AUX
iajs-2563	108	14	pointed	point	VERB
iajs-2563	108	15	out	out	ADP
iajs-2563	108	16	:	:	PUNCT
iajs-2563	108	17	1	1	X
iajs-2563	108	18	.	.	X
iajs-2563	108	19	when	when	SCONJ
iajs-2563	108	20	𝜃	𝜃	X
iajs-2563	108	21	=	=	SYM
iajs-2563	108	22	0.5	0.5	NUM
iajs-2563	108	23	,	,	PUNCT
iajs-2563	108	24	the	the	DET
iajs-2563	108	25	bayes	bayes	NOUN
iajs-2563	108	26	estimators	estimator	NOUN
iajs-2563	108	27	of	of	ADP
iajs-2563	108	28	the	the	DET
iajs-2563	108	29	scale	scale	NOUN
iajs-2563	108	30	parameter	parameter	NOUN
iajs-2563	108	31	and	and	CCONJ
iajs-2563	108	32	reliability	reliability	NOUN
iajs-2563	108	33	function	function	NOUN
iajs-2563	108	34	under	under	ADP
iajs-2563	108	35	entropy	entropy	NOUN
iajs-2563	108	36	loss	loss	NOUN
iajs-2563	108	37	function	function	NOUN
iajs-2563	108	38	with	with	ADP
iajs-2563	108	39	jeffrey	jeffrey	PROPN
iajs-2563	108	40	's	's	PART
iajs-2563	108	41	prior	prior	NOUN
iajs-2563	108	42	is	be	AUX
iajs-2563	108	43	the	the	DET
iajs-2563	108	44	best	good	ADJ
iajs-2563	108	45	for	for	ADP
iajs-2563	108	46	all	all	DET
iajs-2563	108	47	cases	case	NOUN
iajs-2563	108	48	as	as	SCONJ
iajs-2563	108	49	shown	show	VERB
iajs-2563	108	50	in	in	ADP
iajs-2563	108	51	134	134	NUM
iajs-2563	108	52	ibn	ibn	PROPN
iajs-2563	108	53	al	al	PROPN
iajs-2563	108	54	-	-	PUNCT
iajs-2563	108	55	haitham	haitham	PROPN
iajs-2563	108	56	jour	jour	X
iajs-2563	108	57	.	.	PROPN
iajs-2563	109	1	for	for	ADP
iajs-2563	109	2	pure	pure	ADJ
iajs-2563	109	3	&	&	CCONJ
iajs-2563	109	4	appl	appl	PROPN
iajs-2563	109	5	.	.	PUNCT
iajs-2563	110	1	sci	sci	PROPN
iajs-2563	110	2	.	.	PROPN
iajs-2563	111	1	34	34	NUM
iajs-2563	111	2	(	(	PUNCT
iajs-2563	111	3	1	1	NUM
iajs-2563	111	4	)	)	PUNCT
iajs-2563	111	5	2021	2021	NUM
iajs-2563	111	6	tables	table	NOUN
iajs-2563	111	7	(	(	PUNCT
iajs-2563	111	8	1	1	NUM
iajs-2563	111	9	̶	̶	PROPN
iajs-2563	111	10	4	4	NUM
iajs-2563	111	11	)	)	PUNCT
iajs-2563	111	12	.	.	PUNCT
iajs-2563	112	1	while	while	SCONJ
iajs-2563	112	2	the	the	DET
iajs-2563	112	3	estimators	estimator	NOUN
iajs-2563	112	4	under	under	ADP
iajs-2563	112	5	linear	linear	ADJ
iajs-2563	112	6	exponential	exponential	ADJ
iajs-2563	112	7	loss	loss	NOUN
iajs-2563	112	8	function	function	NOUN
iajs-2563	112	9	(	(	PUNCT
iajs-2563	112	10	linex	linex	ADV
iajs-2563	112	11	)	)	PUNCT
iajs-2563	112	12	are	be	AUX
iajs-2563	112	13	the	the	DET
iajs-2563	112	14	best	good	ADJ
iajs-2563	112	15	when	when	SCONJ
iajs-2563	112	16	the	the	DET
iajs-2563	112	17	prior	prior	ADJ
iajs-2563	112	18	information	information	NOUN
iajs-2563	112	19	is	be	AUX
iajs-2563	112	20	exponential	exponential	ADJ
iajs-2563	112	21	.	.	PUNCT
iajs-2563	113	1	2	2	X
iajs-2563	113	2	.	.	X
iajs-2563	113	3	at	at	ADP
iajs-2563	113	4	𝜃	𝜃	NOUN
iajs-2563	113	5	=	=	SYM
iajs-2563	113	6	1.5	1.5	NUM
iajs-2563	113	7	,	,	PUNCT
iajs-2563	113	8	the	the	DET
iajs-2563	113	9	bayes	bayes	PROPN
iajs-2563	113	10	estimator	estimator	NOUN
iajs-2563	113	11	of	of	ADP
iajs-2563	113	12	the	the	DET
iajs-2563	113	13	scale	scale	NOUN
iajs-2563	113	14	parameter	parameter	NOUN
iajs-2563	113	15	best	well	ADV
iajs-2563	113	16	on	on	ADP
iajs-2563	113	17	entropy	entropy	NOUN
iajs-2563	113	18	loss	loss	NOUN
iajs-2563	113	19	function	function	NOUN
iajs-2563	113	20	is	be	AUX
iajs-2563	113	21	the	the	DET
iajs-2563	113	22	best	good	ADJ
iajs-2563	113	23	for	for	ADP
iajs-2563	113	24	all	all	DET
iajs-2563	113	25	cases	case	NOUN
iajs-2563	113	26	,	,	PUNCT
iajs-2563	113	27	while	while	SCONJ
iajs-2563	113	28	the	the	DET
iajs-2563	113	29	bayes	bayes	PROPN
iajs-2563	113	30	estimator	estimator	NOUN
iajs-2563	113	31	of	of	ADP
iajs-2563	113	32	the	the	DET
iajs-2563	113	33	reliability	reliability	NOUN
iajs-2563	113	34	function	function	NOUN
iajs-2563	113	35	under	under	ADP
iajs-2563	113	36	linear	linear	ADJ
iajs-2563	113	37	exponential	exponential	ADJ
iajs-2563	113	38	loss	loss	NOUN
iajs-2563	113	39	function	function	NOUN
iajs-2563	113	40	(	(	PUNCT
iajs-2563	113	41	linex	linex	ADV
iajs-2563	113	42	)	)	PUNCT
iajs-2563	113	43	is	be	AUX
iajs-2563	113	44	the	the	DET
iajs-2563	113	45	best	good	ADJ
iajs-2563	113	46	for	for	ADP
iajs-2563	113	47	all	all	DET
iajs-2563	113	48	cases	case	NOUN
iajs-2563	113	49	as	as	SCONJ
iajs-2563	113	50	shown	show	VERB
iajs-2563	113	51	in	in	ADP
iajs-2563	113	52	tables	table	NOUN
iajs-2563	113	53	(	(	PUNCT
iajs-2563	113	54	5	5	NUM
iajs-2563	113	55	̶	̶	PROPN
iajs-2563	113	56	8)	8)	NUM
iajs-2563	113	57	.	.	PUNCT
iajs-2563	114	1	references	reference	NOUN
iajs-2563	114	2	1	1	NUM
iajs-2563	114	3	.	.	X
iajs-2563	115	1	voda	voda	PROPN
iajs-2563	115	2	,	,	PUNCT
iajs-2563	115	3	v.	v.	PROPN
iajs-2563	115	4	gh	gh	PROPN
iajs-2563	115	5	.	.	PROPN
iajs-2563	115	6	,	,	PUNCT
iajs-2563	115	7	on	on	ADP
iajs-2563	115	8	the	the	DET
iajs-2563	115	9	inverse	inverse	NOUN
iajs-2563	115	10	rayleigh	rayleigh	NOUN
iajs-2563	115	11	distributed	distribute	VERB
iajs-2563	115	12	random	random	ADJ
iajs-2563	115	13	variable	variable	NOUN
iajs-2563	115	14	,	,	PUNCT
iajs-2563	115	15	rep	rep	PROPN
iajs-2563	115	16	.	.	PROPN
iajs-2563	115	17	statis	statis	PROPN
iajs-2563	115	18	.	.	PROPN
iajs-2563	116	1	app	app	PROPN
iajs-2563	116	2	.	.	PUNCT
iajs-2563	117	1	res	res	PROPN
iajs-2563	117	2	.	.	PUNCT
iajs-2563	117	3	juse	juse	PROPN
iajs-2563	117	4	.	.	PROPN
iajs-2563	118	1	1972	1972	NUM
iajs-2563	118	2	,	,	PUNCT
iajs-2563	118	3	19	19	NUM
iajs-2563	118	4	,	,	PUNCT
iajs-2563	118	5	4	4	NUM
iajs-2563	118	6	,	,	PUNCT
iajs-2563	118	7	13	13	NUM
iajs-2563	118	8	-	-	SYM
iajs-2563	118	9	21	21	NUM
iajs-2563	118	10	.	.	PUNCT
iajs-2563	119	1	2	2	X
iajs-2563	119	2	.	.	X
iajs-2563	119	3	gharraph	gharraph	NOUN
iajs-2563	119	4	,	,	PUNCT
iajs-2563	119	5	m.	m.	PROPN
iajs-2563	119	6	k.	k.	PROPN
iajs-2563	119	7	,	,	PUNCT
iajs-2563	119	8	comparison	comparison	NOUN
iajs-2563	119	9	of	of	ADP
iajs-2563	119	10	estimators	estimator	NOUN
iajs-2563	119	11	of	of	ADP
iajs-2563	119	12	location	location	NOUN
iajs-2563	119	13	measures	measure	NOUN
iajs-2563	119	14	of	of	ADP
iajs-2563	119	15	an	an	DET
iajs-2563	119	16	inverse	inverse	ADJ
iajs-2563	119	17	rayleigh	rayleigh	NOUN
iajs-2563	119	18	distribution	distribution	NOUN
iajs-2563	119	19	,	,	PUNCT
iajs-2563	119	20	the	the	DET
iajs-2563	119	21	egyptian	egyptian	ADJ
iajs-2563	119	22	statistical	statistical	ADJ
iajs-2563	119	23	journal	journal	NOUN
iajs-2563	119	24	.	.	PUNCT
iajs-2563	120	1	1993	1993	NUM
iajs-2563	120	2	,	,	PUNCT
iajs-2563	120	3	37,2	37,2	NUM
iajs-2563	120	4	,	,	PUNCT
iajs-2563	120	5	295	295	NUM
iajs-2563	120	6	-	-	SYM
iajs-2563	120	7	309	309	NUM
iajs-2563	120	8	.	.	PUNCT
iajs-2563	121	1	3	3	X
iajs-2563	121	2	.	.	X
iajs-2563	121	3	soliman	soliman	PROPN
iajs-2563	121	4	,	,	PUNCT
iajs-2563	121	5	a.	a.	PROPN
iajs-2563	121	6	,	,	PUNCT
iajs-2563	121	7	amin	amin	PROPN
iajs-2563	121	8	,	,	PUNCT
iajs-2563	121	9	a.e	a.e	PROPN
iajs-2563	121	10	.	.	PROPN
iajs-2563	121	11	and	and	CCONJ
iajs-2563	121	12	aziz	aziz	PROPN
iajs-2563	121	13	,	,	PUNCT
iajs-2563	121	14	a.a	a.a	PROPN
iajs-2563	121	15	.	.	PROPN
iajs-2563	121	16	,	,	PUNCT
iajs-2563	121	17	estimation	estimation	NOUN
iajs-2563	121	18	and	and	CCONJ
iajs-2563	121	19	prediction	prediction	NOUN
iajs-2563	121	20	from	from	ADP
iajs-2563	121	21	inverse	inverse	ADJ
iajs-2563	121	22	rayleigh	rayleigh	NOUN
iajs-2563	121	23	distribution	distribution	NOUN
iajs-2563	121	24	based	base	VERB
iajs-2563	121	25	on	on	ADP
iajs-2563	121	26	lower	low	ADJ
iajs-2563	121	27	record	record	NOUN
iajs-2563	121	28	values	value	NOUN
iajs-2563	121	29	,	,	PUNCT
iajs-2563	121	30	applied	apply	VERB
iajs-2563	121	31	mathematical	mathematical	ADJ
iajs-2563	121	32	sciences	science	NOUN
iajs-2563	121	33	.	.	PUNCT
iajs-2563	122	1	2010	2010	NUM
iajs-2563	122	2	,	,	PUNCT
iajs-2563	122	3	4,62	4,62	NUM
iajs-2563	122	4	,	,	PUNCT
iajs-2563	122	5	3057	3057	NUM
iajs-2563	122	6	-	-	SYM
iajs-2563	122	7	3066	3066	NUM
iajs-2563	122	8	.	.	PUNCT
iajs-2563	123	1	4	4	NUM
iajs-2563	123	2	.	.	X
iajs-2563	123	3	dey	dey	PROPN
iajs-2563	123	4	,	,	PUNCT
iajs-2563	123	5	s.	s.	PROPN
iajs-2563	123	6	,	,	PUNCT
iajs-2563	123	7	bayesian	bayesian	NOUN
iajs-2563	123	8	estimation	estimation	NOUN
iajs-2563	123	9	of	of	ADP
iajs-2563	123	10	the	the	DET
iajs-2563	123	11	parameter	parameter	NOUN
iajs-2563	123	12	and	and	CCONJ
iajs-2563	123	13	reliability	reliability	NOUN
iajs-2563	123	14	function	function	NOUN
iajs-2563	123	15	of	of	ADP
iajs-2563	123	16	an	an	DET
iajs-2563	123	17	inverse	inverse	ADJ
iajs-2563	123	18	rayleigh	rayleigh	NOUN
iajs-2563	123	19	distribution	distribution	NOUN
iajs-2563	123	20	,	,	PUNCT
iajs-2563	123	21	malaysian	malaysian	ADJ
iajs-2563	123	22	journal	journal	NOUN
iajs-2563	123	23	of	of	ADP
iajs-2563	123	24	mathematical	mathematical	ADJ
iajs-2563	123	25	sciences	science	NOUN
iajs-2563	123	26	.	.	PUNCT
iajs-2563	123	27	2012	2012	NUM
iajs-2563	123	28	,	,	PUNCT
iajs-2563	123	29	6,1	6,1	NUM
iajs-2563	123	30	,	,	PUNCT
iajs-2563	123	31	113	113	NUM
iajs-2563	123	32	-	-	SYM
iajs-2563	123	33	124	124	NUM
iajs-2563	123	34	.	.	PUNCT
iajs-2563	124	1	5	5	NUM
iajs-2563	124	2	.	.	X
iajs-2563	124	3	hoff	hoff	PROPN
iajs-2563	124	4	,	,	PUNCT
iajs-2563	124	5	p.	p.	PROPN
iajs-2563	124	6	d.	d.	PROPN
iajs-2563	125	1	a	a	DET
iajs-2563	125	2	first	first	ADJ
iajs-2563	125	3	course	course	NOUN
iajs-2563	125	4	in	in	ADP
iajs-2563	125	5	bayesian	bayesian	NOUN
iajs-2563	125	6	statistical	statistical	ADJ
iajs-2563	125	7	methods	method	NOUN
iajs-2563	125	8	;	;	PUNCT
iajs-2563	125	9	casella	casella	PROPN
iajs-2563	125	10	g.	g.	PROPN
iajs-2563	125	11	,	,	PUNCT
iajs-2563	125	12	fienberg	fienberg	PROPN
iajs-2563	125	13	s.	s.	PROPN
iajs-2563	125	14	,	,	PUNCT
iajs-2563	125	15	olkin	olkin	NOUN
iajs-2563	125	16	i.	i.	NOUN
iajs-2563	125	17	,	,	PUNCT
iajs-2563	125	18	ed	ed	NOUN
iajs-2563	125	19	.	.	PUNCT
iajs-2563	125	20	;	;	PUNCT
iajs-2563	125	21	1st	1st	ADJ
iajs-2563	125	22	ed	ed	NOUN
iajs-2563	125	23	.	.	PUNCT
iajs-2563	125	24	;	;	PUNCT
iajs-2563	125	25	springer	springer	NOUN
iajs-2563	125	26	-	-	PUNCT
iajs-2563	125	27	verlag	verlag	PROPN
iajs-2563	125	28	new	new	PROPN
iajs-2563	125	29	york	york	PROPN
iajs-2563	125	30	:	:	PUNCT
iajs-2563	125	31	usa	usa	PROPN
iajs-2563	125	32	,	,	PUNCT
iajs-2563	125	33	2009	2009	NUM
iajs-2563	125	34	;	;	PUNCT
iajs-2563	125	35	isbn	isbn	ADJ
iajs-2563	125	36	978	978	NUM
iajs-2563	125	37	-	-	SYM
iajs-2563	125	38	0	0	NUM
iajs-2563	125	39	-	-	PUNCT
iajs-2563	125	40	387	387	NUM
iajs-2563	125	41	-	-	PUNCT
iajs-2563	125	42	92299	92299	NUM
iajs-2563	125	43	-	-	PUNCT
iajs-2563	125	44	7	7	NUM
iajs-2563	125	45	.	.	NOUN
iajs-2563	125	46	6	6	NUM
iajs-2563	125	47	.	.	NUM
iajs-2563	125	48	elfessi	elfessi	NOUN
iajs-2563	125	49	,	,	PUNCT
iajs-2563	125	50	a.	a.	NOUN
iajs-2563	125	51	,	,	PUNCT
iajs-2563	125	52	&	&	CCONJ
iajs-2563	125	53	reineke	reineke	ADJ
iajs-2563	125	54	,	,	PUNCT
iajs-2563	125	55	d.	d.	PROPN
iajs-2563	125	56	m.	m.	PROPN
iajs-2563	125	57	a	a	DET
iajs-2563	125	58	bayesian	bayesian	NOUN
iajs-2563	125	59	look	look	VERB
iajs-2563	125	60	at	at	ADP
iajs-2563	125	61	classical	classical	ADJ
iajs-2563	125	62	estimation	estimation	NOUN
iajs-2563	125	63	:	:	PUNCT
iajs-2563	125	64	the	the	DET
iajs-2563	125	65	exponential	exponential	ADJ
iajs-2563	125	66	distribution	distribution	NOUN
iajs-2563	125	67	.	.	PUNCT
iajs-2563	126	1	journal	journal	PROPN
iajs-2563	126	2	of	of	ADP
iajs-2563	126	3	statistics	statistics	PROPN
iajs-2563	126	4	education	education	NOUN
iajs-2563	126	5	,	,	PUNCT
iajs-2563	126	6	2017	2017	NUM
iajs-2563	126	7	,	,	PUNCT
iajs-2563	126	8	9,1	9,1	NUM
iajs-2563	126	9	,	,	PUNCT
iajs-2563	126	10	1	1	NUM
iajs-2563	126	11	-	-	SYM
iajs-2563	126	12	7	7	NUM
iajs-2563	126	13	.	.	NOUN
iajs-2563	126	14	7	7	NUM
iajs-2563	126	15	.	.	X
iajs-2563	126	16	ali	ali	PROPN
iajs-2563	126	17	,	,	PUNCT
iajs-2563	126	18	m.j	m.j	PROPN
iajs-2563	126	19	.	.	PROPN
iajs-2563	126	20	;	;	PUNCT
iajs-2563	126	21	gorgeees	gorgeees	PROPN
iajs-2563	126	22	,	,	PUNCT
iajs-2563	126	23	h.m	h.m	PROPN
iajs-2563	126	24	.	.	PROPN
iajs-2563	126	25	;	;	PUNCT
iajs-2563	126	26	hussian	hussian	PROPN
iajs-2563	126	27	,	,	PUNCT
iajs-2563	126	28	a.a	a.a	PROPN
iajs-2563	126	29	.	.	PROPN
iajs-2563	126	30	,	,	PUNCT
iajs-2563	126	31	the	the	DET
iajs-2563	126	32	comparison	comparison	NOUN
iajs-2563	126	33	between	between	ADP
iajs-2563	126	34	standard	standard	ADJ
iajs-2563	126	35	bayes	bayes	NOUN
iajs-2563	126	36	estimators	estimator	NOUN
iajs-2563	126	37	of	of	ADP
iajs-2563	126	38	the	the	DET
iajs-2563	126	39	reliability	reliability	NOUN
iajs-2563	126	40	function	function	NOUN
iajs-2563	126	41	of	of	ADP
iajs-2563	126	42	exponential	exponential	ADJ
iajs-2563	126	43	distribution	distribution	NOUN
iajs-2563	126	44	,	,	PUNCT
iajs-2563	126	45	ibn	ibn	PROPN
iajs-2563	126	46	al	al	PROPN
iajs-2563	126	47	-	-	PUNCT
iajs-2563	126	48	haitham	haitham	PROPN
iajs-2563	126	49	jour	jour	PROPN
iajs-2563	126	50	for	for	ADP
iajs-2563	126	51	pure	pure	ADJ
iajs-2563	126	52	&	&	CCONJ
iajs-2563	126	53	appl	appl	PROPN
iajs-2563	126	54	.	.	PUNCT
iajs-2563	127	1	sci	sci	PROPN
iajs-2563	127	2	.	.	PROPN
iajs-2563	127	3	2018	2018	NUM
iajs-2563	127	4	,	,	PUNCT
iajs-2563	127	5	32	32	NUM
iajs-2563	127	6	,	,	PUNCT
iajs-2563	127	7	1	1	NUM
iajs-2563	127	8	,	,	PUNCT
iajs-2563	127	9	101	101	NUM
iajs-2563	127	10	-	-	SYM
iajs-2563	127	11	109	109	NUM
iajs-2563	127	12	.	.	NOUN
iajs-2563	127	13	8	8	NUM
iajs-2563	127	14	.	.	PUNCT
iajs-2563	128	1	gholam	gholam	PROPN
iajs-2563	128	2	-	-	PUNCT
iajs-2563	128	3	hossein	hossein	PROPN
iajs-2563	128	4	,	,	PUNCT
iajs-2563	128	5	yari	yari	PROPN
iajs-2563	128	6	,	,	PUNCT
iajs-2563	128	7	g.r	g.r	PROPN
iajs-2563	128	8	.	.	PUNCT
iajs-2563	128	9	mohtashami	mohtashami	PROPN
iajs-2563	128	10	borzadaran	borzadaran	PROPN
iajs-2563	128	11	,	,	PUNCT
iajs-2563	128	12	entropy	entropy	NOUN
iajs-2563	128	13	for	for	ADP
iajs-2563	128	14	pareto	pareto	ADJ
iajs-2563	128	15	types	type	NOUN
iajs-2563	128	16	and	and	CCONJ
iajs-2563	128	17	its	its	PRON
iajs-2563	128	18	order	order	NOUN
iajs-2563	128	19	statistic	statistic	ADJ
iajs-2563	128	20	distribution	distribution	NOUN
iajs-2563	128	21	,	,	PUNCT
iajs-2563	128	22	communications	communication	NOUN
iajs-2563	128	23	in	in	ADP
iajs-2563	128	24	information	information	NOUN
iajs-2563	128	25	and	and	CCONJ
iajs-2563	128	26	system	system	NOUN
iajs-2563	128	27	,	,	PUNCT
iajs-2563	128	28	2010	2010	NUM
iajs-2563	128	29	,	,	PUNCT
iajs-2563	128	30	10,3	10,3	NUM
iajs-2563	128	31	,	,	PUNCT
iajs-2563	128	32	193202	193202	NUM
iajs-2563	128	33	.	.	PUNCT
iajs-2563	129	1	9	9	X
iajs-2563	129	2	.	.	X
iajs-2563	129	3	tawfiq	tawfiq	PROPN
iajs-2563	129	4	,	,	PUNCT
iajs-2563	129	5	lnm	lnm	PROPN
iajs-2563	129	6	;	;	PUNCT
iajs-2563	129	7	oraibi	oraibi	PROPN
iajs-2563	129	8	.	.	PUNCT
iajs-2563	130	1	ya	ya	INTJ
iajs-2563	130	2	.	.	PUNCT
iajs-2563	131	1	fast	fast	ADJ
iajs-2563	131	2	training	training	NOUN
iajs-2563	131	3	algorithms	algorithm	NOUN
iajs-2563	131	4	for	for	ADP
iajs-2563	131	5	feed	feed	NOUN
iajs-2563	131	6	forward	forward	ADV
iajs-2563	131	7	neural	neural	ADJ
iajs-2563	131	8	networks	network	NOUN
iajs-2563	131	9	.	.	PUNCT
iajs-2563	132	1	ibn	ibn	PROPN
iajs-2563	132	2	al	al	PROPN
iajs-2563	132	3	-	-	PUNCT
iajs-2563	132	4	haitham	haitham	PROPN
iajs-2563	132	5	journal	journal	PROPN
iajs-2563	132	6	for	for	ADP
iajs-2563	132	7	pure	pure	ADJ
iajs-2563	132	8	and	and	CCONJ
iajs-2563	132	9	applied	applied	ADJ
iajs-2563	132	10	science	science	NOUN
iajs-2563	132	11	.	.	PUNCT
iajs-2563	133	1	2017	2017	NUM
iajs-2563	133	2	,	,	PUNCT
iajs-2563	133	3	26	26	NUM
iajs-2563	133	4	,	,	PUNCT
iajs-2563	133	5	1	1	NUM
iajs-2563	133	6	:	:	SYM
iajs-2563	133	7	1275	1275	NUM
iajs-2563	133	8	-	-	SYM
iajs-2563	133	9	280	280	NUM
iajs-2563	133	10	.	.	PUNCT
iajs-2563	134	1	http://codental.uobaghdad.edu.iq/jih/index.php/j/article/view/534	http://codental.uobaghdad.edu.iq/jih/index.php/j/article/view/534	NOUN