id	sid	tid	token	lemma	pos
iajs-2946	1	1	ihjpas	ihjpas	PROPN
iajs-2946	1	2	.	.	PUNCT
iajs-2946	2	1	36(2)2023	36(2)2023	NUM
iajs-2946	2	2	289	289	NUM
iajs-2946	2	3	this	this	DET
iajs-2946	2	4	work	work	NOUN
iajs-2946	2	5	is	be	AUX
iajs-2946	2	6	licensed	license	VERB
iajs-2946	2	7	under	under	ADP
iajs-2946	2	8	a	a	DET
iajs-2946	2	9	creative	creative	ADJ
iajs-2946	2	10	commons	common	NOUN
iajs-2946	2	11	attribution	attribution	NOUN
iajs-2946	2	12	4.0	4.0	NUM
iajs-2946	2	13	international	international	ADJ
iajs-2946	2	14	license	license	NOUN
iajs-2946	2	15	abstract	abstract	NOUN
iajs-2946	2	16	in	in	ADP
iajs-2946	2	17	this	this	DET
iajs-2946	2	18	paper	paper	NOUN
iajs-2946	2	19	,	,	PUNCT
iajs-2946	2	20	two	two	NUM
iajs-2946	2	21	parameters	parameter	NOUN
iajs-2946	2	22	for	for	ADP
iajs-2946	2	23	the	the	DET
iajs-2946	2	24	exponential	exponential	ADJ
iajs-2946	2	25	distribution	distribution	NOUN
iajs-2946	2	26	were	be	AUX
iajs-2946	2	27	estimated	estimate	VERB
iajs-2946	2	28	using	use	VERB
iajs-2946	2	29	the	the	DET
iajs-2946	2	30	bayesian	bayesian	NOUN
iajs-2946	2	31	estimation	estimation	NOUN
iajs-2946	2	32	method	method	NOUN
iajs-2946	2	33	under	under	ADP
iajs-2946	2	34	three	three	NUM
iajs-2946	2	35	different	different	ADJ
iajs-2946	2	36	loss	loss	NOUN
iajs-2946	2	37	functions	function	NOUN
iajs-2946	2	38	:	:	PUNCT
iajs-2946	2	39	the	the	DET
iajs-2946	2	40	squared	square	VERB
iajs-2946	2	41	error	error	NOUN
iajs-2946	2	42	loss	loss	NOUN
iajs-2946	2	43	function	function	NOUN
iajs-2946	2	44	,	,	PUNCT
iajs-2946	2	45	the	the	DET
iajs-2946	2	46	precautionary	precautionary	ADJ
iajs-2946	2	47	loss	loss	NOUN
iajs-2946	2	48	function	function	NOUN
iajs-2946	2	49	,	,	PUNCT
iajs-2946	2	50	and	and	CCONJ
iajs-2946	2	51	the	the	DET
iajs-2946	2	52	entropy	entropy	NOUN
iajs-2946	2	53	loss	loss	NOUN
iajs-2946	2	54	function	function	NOUN
iajs-2946	2	55	.	.	PUNCT
iajs-2946	3	1	the	the	DET
iajs-2946	3	2	exponential	exponential	ADJ
iajs-2946	3	3	distribution	distribution	NOUN
iajs-2946	3	4	prior	prior	ADV
iajs-2946	3	5	and	and	CCONJ
iajs-2946	3	6	gamma	gamma	NOUN
iajs-2946	3	7	distribution	distribution	NOUN
iajs-2946	3	8	have	have	AUX
iajs-2946	3	9	been	be	AUX
iajs-2946	3	10	assumed	assume	VERB
iajs-2946	3	11	as	as	ADP
iajs-2946	3	12	the	the	DET
iajs-2946	3	13	priors	prior	NOUN
iajs-2946	3	14	of	of	ADP
iajs-2946	3	15	the	the	DET
iajs-2946	3	16	scale	scale	NOUN
iajs-2946	3	17	γ	γ	NOUN
iajs-2946	3	18	and	and	CCONJ
iajs-2946	3	19	location	location	NOUN
iajs-2946	3	20	δ	δ	PROPN
iajs-2946	3	21	parameters	parameter	NOUN
iajs-2946	3	22	respectively	respectively	ADV
iajs-2946	3	23	.	.	PUNCT
iajs-2946	4	1	in	in	ADP
iajs-2946	4	2	bayesian	bayesian	NOUN
iajs-2946	4	3	estimation	estimation	NOUN
iajs-2946	4	4	,	,	PUNCT
iajs-2946	4	5	maximum	maximum	ADJ
iajs-2946	4	6	likelihood	likelihood	NOUN
iajs-2946	4	7	estimators	estimator	NOUN
iajs-2946	4	8	have	have	AUX
iajs-2946	4	9	been	be	AUX
iajs-2946	4	10	used	use	VERB
iajs-2946	4	11	as	as	ADP
iajs-2946	4	12	the	the	DET
iajs-2946	4	13	initial	initial	ADJ
iajs-2946	4	14	estimators	estimator	NOUN
iajs-2946	4	15	,	,	PUNCT
iajs-2946	4	16	and	and	CCONJ
iajs-2946	4	17	the	the	DET
iajs-2946	4	18	tierney	tierney	NOUN
iajs-2946	4	19	-	-	PUNCT
iajs-2946	4	20	kadane	kadane	PROPN
iajs-2946	4	21	approximation	approximation	NOUN
iajs-2946	4	22	has	have	AUX
iajs-2946	4	23	been	be	AUX
iajs-2946	4	24	used	use	VERB
iajs-2946	4	25	effectively	effectively	ADV
iajs-2946	4	26	.	.	PUNCT
iajs-2946	5	1	based	base	VERB
iajs-2946	5	2	on	on	ADP
iajs-2946	5	3	the	the	DET
iajs-2946	5	4	montecarlo	montecarlo	PROPN
iajs-2946	5	5	simulation	simulation	NOUN
iajs-2946	5	6	method	method	NOUN
iajs-2946	5	7	,	,	PUNCT
iajs-2946	5	8	those	those	DET
iajs-2946	5	9	estimators	estimator	NOUN
iajs-2946	5	10	were	be	AUX
iajs-2946	5	11	compared	compare	VERB
iajs-2946	5	12	depending	depend	VERB
iajs-2946	5	13	on	on	ADP
iajs-2946	5	14	the	the	DET
iajs-2946	5	15	mean	mean	ADJ
iajs-2946	5	16	squared	square	VERB
iajs-2946	5	17	errors	error	NOUN
iajs-2946	5	18	(	(	PUNCT
iajs-2946	5	19	mses	ms	NOUN
iajs-2946	5	20	)	)	PUNCT
iajs-2946	5	21	.	.	PUNCT
iajs-2946	6	1	the	the	DET
iajs-2946	6	2	results	result	NOUN
iajs-2946	6	3	showed	show	VERB
iajs-2946	6	4	that	that	SCONJ
iajs-2946	6	5	the	the	DET
iajs-2946	6	6	bayesian	bayesian	NOUN
iajs-2946	6	7	estimation	estimation	NOUN
iajs-2946	6	8	under	under	ADP
iajs-2946	6	9	the	the	DET
iajs-2946	6	10	entropy	entropy	NOUN
iajs-2946	6	11	loss	loss	NOUN
iajs-2946	6	12	function	function	NOUN
iajs-2946	6	13	,	,	PUNCT
iajs-2946	6	14	assuming	assume	VERB
iajs-2946	6	15	exponential	exponential	ADJ
iajs-2946	6	16	distribution	distribution	NOUN
iajs-2946	6	17	and	and	CCONJ
iajs-2946	6	18	gamma	gamma	NOUN
iajs-2946	6	19	distribution	distribution	NOUN
iajs-2946	6	20	priors	prior	NOUN
iajs-2946	6	21	for	for	ADP
iajs-2946	6	22	the	the	DET
iajs-2946	6	23	scale	scale	NOUN
iajs-2946	6	24	and	and	CCONJ
iajs-2946	6	25	location	location	NOUN
iajs-2946	6	26	parameters	parameter	NOUN
iajs-2946	6	27	,	,	PUNCT
iajs-2946	6	28	respectively	respectively	ADV
iajs-2946	6	29	,	,	PUNCT
iajs-2946	6	30	is	be	AUX
iajs-2946	6	31	the	the	DET
iajs-2946	6	32	best	good	ADJ
iajs-2946	6	33	estimator	estimator	NOUN
iajs-2946	6	34	for	for	ADP
iajs-2946	6	35	the	the	DET
iajs-2946	6	36	scale	scale	NOUN
iajs-2946	6	37	parameter	parameter	NOUN
iajs-2946	6	38	.	.	PUNCT
iajs-2946	7	1	the	the	DET
iajs-2946	7	2	best	good	ADJ
iajs-2946	7	3	estimation	estimation	NOUN
iajs-2946	7	4	method	method	NOUN
iajs-2946	7	5	for	for	ADP
iajs-2946	7	6	location	location	NOUN
iajs-2946	7	7	is	be	AUX
iajs-2946	7	8	the	the	DET
iajs-2946	7	9	bayesian	bayesian	NOUN
iajs-2946	7	10	estimation	estimation	NOUN
iajs-2946	7	11	under	under	ADP
iajs-2946	7	12	the	the	DET
iajs-2946	7	13	entropy	entropy	NOUN
iajs-2946	7	14	loss	loss	NOUN
iajs-2946	7	15	function	function	NOUN
iajs-2946	7	16	in	in	ADP
iajs-2946	7	17	case	case	NOUN
iajs-2946	7	18	of	of	ADP
iajs-2946	7	19	a	a	DET
iajs-2946	7	20	small	small	ADJ
iajs-2946	7	21	value	value	NOUN
iajs-2946	7	22	of	of	ADP
iajs-2946	7	23	the	the	DET
iajs-2946	7	24	scale	scale	NOUN
iajs-2946	7	25	γ	γ	X
iajs-2946	7	26	(	(	PUNCT
iajs-2946	7	27	say	say	VERB
iajs-2946	7	28	γ	γ	X
iajs-2946	7	29	<	<	X
iajs-2946	7	30	1	1	NUM
iajs-2946	7	31	)	)	PUNCT
iajs-2946	7	32	.	.	PUNCT
iajs-2946	8	1	bayesian	bayesian	NOUN
iajs-2946	8	2	estimation	estimation	NOUN
iajs-2946	8	3	under	under	ADP
iajs-2946	8	4	the	the	DET
iajs-2946	8	5	precautionary	precautionary	ADJ
iajs-2946	8	6	loss	loss	NOUN
iajs-2946	8	7	function	function	NOUN
iajs-2946	8	8	is	be	AUX
iajs-2946	8	9	the	the	DET
iajs-2946	8	10	best	good	ADJ
iajs-2946	8	11	in	in	ADP
iajs-2946	8	12	case	case	NOUN
iajs-2946	8	13	of	of	ADP
iajs-2946	8	14	a	a	DET
iajs-2946	8	15	relatively	relatively	ADV
iajs-2946	8	16	large	large	ADJ
iajs-2946	8	17	value	value	NOUN
iajs-2946	8	18	of	of	ADP
iajs-2946	8	19	the	the	DET
iajs-2946	8	20	scale	scale	NOUN
iajs-2946	8	21	γ	γ	X
iajs-2946	8	22	(	(	PUNCT
iajs-2946	8	23	say	say	VERB
iajs-2946	8	24	γ	γ	X
iajs-2946	8	25	>	>	X
iajs-2946	8	26	1	1	NUM
iajs-2946	8	27	)	)	PUNCT
iajs-2946	8	28	.	.	PUNCT
iajs-2946	9	1	keywords	keyword	NOUN
iajs-2946	9	2	:	:	PUNCT
iajs-2946	9	3	exponential	exponential	ADJ
iajs-2946	9	4	distribution	distribution	NOUN
iajs-2946	9	5	,	,	PUNCT
iajs-2946	9	6	maximum	maximum	ADJ
iajs-2946	9	7	likelihood	likelihood	NOUN
iajs-2946	9	8	estimator	estimator	NOUN
iajs-2946	9	9	,	,	PUNCT
iajs-2946	9	10	squared	square	VERB
iajs-2946	9	11	error	error	NOUN
iajs-2946	9	12	loss	loss	NOUN
iajs-2946	9	13	function	function	NOUN
iajs-2946	9	14	,	,	PUNCT
iajs-2946	9	15	precautionary	precautionary	ADJ
iajs-2946	9	16	loss	loss	NOUN
iajs-2946	9	17	function	function	NOUN
iajs-2946	9	18	,	,	PUNCT
iajs-2946	9	19	entropy	entropy	VERB
iajs-2946	9	20	loss	loss	NOUN
iajs-2946	9	21	function	function	NOUN
iajs-2946	9	22	,	,	PUNCT
iajs-2946	9	23	tierney	tierney	PROPN
iajs-2946	9	24	and	and	CCONJ
iajs-2946	9	25	kadane	kadane	PROPN
iajs-2946	9	26	approximation	approximation	NOUN
iajs-2946	9	27	.	.	PUNCT
iajs-2946	10	1	1.introduction	1.introduction	NUM
iajs-2946	10	2	exponential	exponential	ADJ
iajs-2946	10	3	distribution	distribution	NOUN
iajs-2946	10	4	has	have	VERB
iajs-2946	10	5	great	great	ADJ
iajs-2946	10	6	importance	importance	NOUN
iajs-2946	10	7	and	and	CCONJ
iajs-2946	10	8	a	a	DET
iajs-2946	10	9	great	great	ADJ
iajs-2946	10	10	role	role	NOUN
iajs-2946	10	11	in	in	ADP
iajs-2946	10	12	different	different	ADJ
iajs-2946	10	13	industrial	industrial	ADJ
iajs-2946	10	14	and	and	CCONJ
iajs-2946	10	15	engineering	engineering	NOUN
iajs-2946	10	16	applications	application	NOUN
iajs-2946	10	17	,	,	PUNCT
iajs-2946	10	18	in	in	ADP
iajs-2946	10	19	addition	addition	NOUN
iajs-2946	10	20	to	to	ADP
iajs-2946	10	21	the	the	DET
iajs-2946	10	22	theory	theory	NOUN
iajs-2946	10	23	of	of	ADP
iajs-2946	10	24	waiting	wait	VERB
iajs-2946	10	25	in	in	ADP
iajs-2946	10	26	lines	line	NOUN
iajs-2946	10	27	or	or	CCONJ
iajs-2946	10	28	queues	queue	NOUN
iajs-2946	10	29	(	(	PUNCT
iajs-2946	10	30	queuing	queue	VERB
iajs-2946	10	31	theory	theory	NOUN
iajs-2946	10	32	)	)	PUNCT
iajs-2946	10	33	,	,	PUNCT
iajs-2946	10	34	which	which	PRON
iajs-2946	10	35	exists	exist	VERB
iajs-2946	10	36	in	in	ADP
iajs-2946	10	37	different	different	ADJ
iajs-2946	10	38	situations	situation	NOUN
iajs-2946	10	39	.	.	PUNCT
iajs-2946	11	1	also	also	ADV
iajs-2946	11	2	,	,	PUNCT
iajs-2946	11	3	it	it	PRON
iajs-2946	11	4	is	be	AUX
iajs-2946	11	5	used	use	VERB
iajs-2946	11	6	when	when	SCONJ
iajs-2946	11	7	the	the	DET
iajs-2946	11	8	failure	failure	NOUN
iajs-2946	11	9	rate	rate	NOUN
iajs-2946	11	10	is	be	AUX
iajs-2946	11	11	constant	constant	ADJ
iajs-2946	11	12	with	with	ADP
iajs-2946	11	13	time	time	NOUN
iajs-2946	11	14	,	,	PUNCT
iajs-2946	11	15	where	where	SCONJ
iajs-2946	11	16	sometimes	sometimes	ADV
iajs-2946	11	17	there	there	PRON
iajs-2946	11	18	is	be	VERB
iajs-2946	11	19	a	a	DET
iajs-2946	11	20	need	need	NOUN
iajs-2946	11	21	to	to	PART
iajs-2946	11	22	find	find	VERB
iajs-2946	11	23	reliability	reliability	NOUN
iajs-2946	11	24	that	that	PRON
iajs-2946	11	25	starts	start	VERB
iajs-2946	11	26	from	from	ADP
iajs-2946	11	27	a	a	DET
iajs-2946	11	28	specific	specific	ADJ
iajs-2946	11	29	time	time	NOUN
iajs-2946	11	30	and	and	CCONJ
iajs-2946	11	31	not	not	PART
iajs-2946	11	32	from	from	ADP
iajs-2946	11	33	zero	zero	NUM
iajs-2946	11	34	.	.	PUNCT
iajs-2946	12	1	even	even	ADV
iajs-2946	12	2	though	though	SCONJ
iajs-2946	12	3	the	the	DET
iajs-2946	12	4	importance	importance	NOUN
iajs-2946	12	5	of	of	ADP
iajs-2946	12	6	exponential	exponential	ADJ
iajs-2946	12	7	distribution	distribution	NOUN
iajs-2946	12	8	has	have	VERB
iajs-2946	12	9	both	both	CCONJ
iajs-2946	12	10	theoretical	theoretical	ADJ
iajs-2946	12	11	and	and	CCONJ
iajs-2946	12	12	practical	practical	ADJ
iajs-2946	12	13	sides	side	NOUN
iajs-2946	12	14	,	,	PUNCT
iajs-2946	12	15	it	it	PRON
iajs-2946	12	16	remains	remain	VERB
iajs-2946	12	17	poorly	poorly	ADV
iajs-2946	12	18	studied	study	VERB
iajs-2946	12	19	.	.	PUNCT
iajs-2946	13	1	therefore	therefore	ADV
iajs-2946	13	2	,	,	PUNCT
iajs-2946	13	3	the	the	DET
iajs-2946	13	4	main	main	ADJ
iajs-2946	13	5	objective	objective	NOUN
iajs-2946	13	6	of	of	ADP
iajs-2946	13	7	this	this	DET
iajs-2946	13	8	paper	paper	NOUN
iajs-2946	13	9	is	be	AUX
iajs-2946	13	10	to	to	PART
iajs-2946	13	11	find	find	VERB
iajs-2946	13	12	the	the	DET
iajs-2946	13	13	best	good	ADJ
iajs-2946	13	14	estimator	estimator	NOUN
iajs-2946	13	15	for	for	ADP
iajs-2946	13	16	the	the	DET
iajs-2946	13	17	location	location	NOUN
iajs-2946	13	18	and	and	CCONJ
iajs-2946	13	19	the	the	DET
iajs-2946	13	20	scale	scale	NOUN
iajs-2946	13	21	parameters	parameter	NOUN
iajs-2946	13	22	using	use	VERB
iajs-2946	13	23	bayesian	bayesian	NOUN
iajs-2946	13	24	estimation	estimation	NOUN
iajs-2946	13	25	and	and	CCONJ
iajs-2946	13	26	compare	compare	VERB
iajs-2946	13	27	the	the	DET
iajs-2946	13	28	doi.org/10.30526/36.2.2946	doi.org/10.30526/36.2.2946	ADJ
iajs-2946	13	29	article	article	NOUN
iajs-2946	13	30	history	history	NOUN
iajs-2946	13	31	:	:	PUNCT
iajs-2946	13	32	received	receive	VERB
iajs-2946	13	33	3	3	NUM
iajs-2946	13	34	august	august	PROPN
iajs-2946	13	35	2022	2022	NUM
iajs-2946	13	36	,	,	PUNCT
iajs-2946	13	37	accepted	accept	VERB
iajs-2946	13	38	4	4	NUM
iajs-2946	13	39	september	september	PROPN
iajs-2946	13	40	2022	2022	NUM
iajs-2946	13	41	,	,	PUNCT
iajs-2946	13	42	published	publish	VERB
iajs-2946	13	43	in	in	ADP
iajs-2946	13	44	april	april	PROPN
iajs-2946	13	45	2023	2023	NUM
iajs-2946	13	46	.	.	PUNCT
iajs-2946	14	1	ibn	ibn	PROPN
iajs-2946	14	2	al	al	PROPN
iajs-2946	14	3	-	-	PUNCT
iajs-2946	14	4	haitham	haitham	PROPN
iajs-2946	14	5	journal	journal	PROPN
iajs-2946	14	6	for	for	ADP
iajs-2946	14	7	pure	pure	ADJ
iajs-2946	14	8	and	and	CCONJ
iajs-2946	14	9	applied	applied	ADJ
iajs-2946	14	10	sciences	sciences	PROPN
iajs-2946	14	11	journal	journal	PROPN
iajs-2946	14	12	homepage	homepage	NOUN
iajs-2946	14	13	:	:	PUNCT
iajs-2946	14	14	jih.uobaghdad.edu.iq	jih.uobaghdad.edu.iq	NOUN
iajs-2946	14	15	bayesian	bayesian	NOUN
iajs-2946	14	16	estimation	estimation	NOUN
iajs-2946	14	17	for	for	ADP
iajs-2946	14	18	two	two	NUM
iajs-2946	14	19	parameters	parameter	NOUN
iajs-2946	14	20	of	of	ADP
iajs-2946	14	21	exponential	exponential	ADJ
iajs-2946	14	22	distribution	distribution	NOUN
iajs-2946	14	23	under	under	ADP
iajs-2946	14	24	different	different	ADJ
iajs-2946	14	25	loss	loss	NOUN
iajs-2946	14	26	functions	function	NOUN
iajs-2946	14	27	maryam	maryam	PROPN
iajs-2946	14	28	n.	n.	PROPN
iajs-2946	14	29	abd	abd	PROPN
iajs-2946	14	30	department	department	PROPN
iajs-2946	14	31	of	of	ADP
iajs-2946	14	32	mathematics	mathematics	PROPN
iajs-2946	14	33	,	,	PUNCT
iajs-2946	14	34	college	college	NOUN
iajs-2946	14	35	of	of	ADP
iajs-2946	14	36	science	science	NOUN
iajs-2946	14	37	,	,	PUNCT
iajs-2946	14	38	mustansiriyah	mustansiriyah	NOUN
iajs-2946	14	39	university	university	NOUN
iajs-2946	14	40	,	,	PUNCT
iajs-2946	14	41	baghdad	baghdad	PROPN
iajs-2946	14	42	,	,	PUNCT
iajs-2946	14	43	iraq	iraq	PROPN
iajs-2946	14	44	.	.	PUNCT
iajs-2946	15	1	memealzubaydi@gmail.com	memealzubaydi@gmail.com	X
iajs-2946	16	1	huda	huda	PROPN
iajs-2946	16	2	a.	a.	PROPN
iajs-2946	16	3	rasheed	rasheed	PROPN
iajs-2946	16	4	department	department	PROPN
iajs-2946	16	5	of	of	ADP
iajs-2946	16	6	mathematics	mathematics	PROPN
iajs-2946	16	7	,	,	PUNCT
iajs-2946	16	8	college	college	NOUN
iajs-2946	16	9	of	of	ADP
iajs-2946	16	10	science	science	NOUN
iajs-2946	16	11	,	,	PUNCT
iajs-2946	16	12	mustansiriyah	mustansiriyah	NOUN
iajs-2946	16	13	university	university	NOUN
iajs-2946	16	14	,	,	PUNCT
iajs-2946	16	15	baghdad	baghdad	PROPN
iajs-2946	16	16	,	,	PUNCT
iajs-2946	16	17	iraq	iraq	PROPN
iajs-2946	16	18	.	.	PUNCT
iajs-2946	17	1	iraqalnoor1@gmail.com	iraqalnoor1@gmail.com	X
iajs-2946	17	2	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
iajs-2946	17	3	mailto:memealzubaydi@gmail.com	mailto:memealzubaydi@gmail.com	PROPN
iajs-2946	17	4	ihjpas	ihjpa	VERB
iajs-2946	17	5	.	.	PUNCT
iajs-2946	18	1	36(2)2023	36(2)2023	NUM
iajs-2946	18	2	290	290	NUM
iajs-2946	18	3	performance	performance	NOUN
iajs-2946	18	4	of	of	ADP
iajs-2946	18	5	these	these	DET
iajs-2946	18	6	estimators	estimator	NOUN
iajs-2946	18	7	under	under	ADP
iajs-2946	18	8	a	a	DET
iajs-2946	18	9	mean	mean	ADJ
iajs-2946	18	10	squared	square	VERB
iajs-2946	18	11	error	error	NOUN
iajs-2946	18	12	(	(	PUNCT
iajs-2946	18	13	mse)-based	mse)-base	VERB
iajs-2946	18	14	monte	monte	PROPN
iajs-2946	18	15	carlo	carlo	PROPN
iajs-2946	18	16	simulation	simulation	PROPN
iajs-2946	18	17	study	study	PROPN
iajs-2946	18	18	.	.	PUNCT
iajs-2946	19	1	the	the	DET
iajs-2946	19	2	probability	probability	NOUN
iajs-2946	19	3	density	density	NOUN
iajs-2946	19	4	function	function	NOUN
iajs-2946	19	5	(	(	PUNCT
iajs-2946	19	6	p.d.f	p.d.f	ADJ
iajs-2946	19	7	)	)	PUNCT
iajs-2946	19	8	of	of	ADP
iajs-2946	19	9	the	the	DET
iajs-2946	19	10	two	two	NUM
iajs-2946	19	11	parameters	parameter	NOUN
iajs-2946	19	12	exponential	exponential	ADJ
iajs-2946	19	13	distribution	distribution	NOUN
iajs-2946	19	14	is	be	AUX
iajs-2946	19	15	given	give	VERB
iajs-2946	19	16	by	by	ADP
iajs-2946	19	17	[	[	X
iajs-2946	19	18	1	1	NUM
iajs-2946	19	19	]	]	NUM
iajs-2946	19	20	:	:	PUNCT
iajs-2946	19	21	𝑓(𝑥	𝑓(𝑥	NOUN
iajs-2946	19	22	;	;	PUNCT
iajs-2946	19	23	𝛾	𝛾	NOUN
iajs-2946	19	24	,	,	PUNCT
iajs-2946	19	25	𝛿	𝛿	ADJ
iajs-2946	19	26	)	)	PUNCT
iajs-2946	19	27	=	=	SYM
iajs-2946	20	1	1	1	NUM
iajs-2946	20	2	𝛾	𝛾	NOUN
iajs-2946	20	3	𝑒	𝑒	PROPN
iajs-2946	20	4	−	−	NOUN
iajs-2946	20	5	(	(	PUNCT
iajs-2946	20	6	𝑥−𝛿	𝑥−𝛿	NOUN
iajs-2946	20	7	)	)	PUNCT
iajs-2946	20	8	𝛾	𝛾	NOUN
iajs-2946	20	9	;	;	PUNCT
iajs-2946	20	10	𝑥	𝑥	X
iajs-2946	20	11	>	>	X
iajs-2946	20	12	𝛿	𝛿	X
iajs-2946	20	13	,	,	PUNCT
iajs-2946	20	14	𝛾	𝛾	X
iajs-2946	20	15	>	>	X
iajs-2946	20	16	0	0	PUNCT
iajs-2946	21	1	,	,	PUNCT
iajs-2946	21	2	𝛿	𝛿	DET
iajs-2946	21	3	≥	≥	NOUN
iajs-2946	21	4	0	0	NUM
iajs-2946	21	5	(	(	PUNCT
iajs-2946	21	6	1	1	NUM
iajs-2946	21	7	)	)	PUNCT
iajs-2946	21	8	where	where	SCONJ
iajs-2946	21	9	,	,	PUNCT
iajs-2946	21	10	γ	γ	PROPN
iajs-2946	21	11	and	and	CCONJ
iajs-2946	21	12	δ	δ	PROPN
iajs-2946	21	13	are	be	AUX
iajs-2946	21	14	the	the	DET
iajs-2946	21	15	scale	scale	NOUN
iajs-2946	21	16	and	and	CCONJ
iajs-2946	21	17	location	location	NOUN
iajs-2946	21	18	parameters	parameter	NOUN
iajs-2946	21	19	,	,	PUNCT
iajs-2946	21	20	respectively	respectively	ADV
iajs-2946	21	21	.	.	PUNCT
iajs-2946	22	1	the	the	DET
iajs-2946	22	2	exponential	exponential	ADJ
iajs-2946	22	3	distribution	distribution	NOUN
iajs-2946	22	4	is	be	AUX
iajs-2946	22	5	a	a	DET
iajs-2946	22	6	special	special	ADJ
iajs-2946	22	7	case	case	NOUN
iajs-2946	22	8	of	of	ADP
iajs-2946	22	9	the	the	DET
iajs-2946	22	10	weibull	weibull	NOUN
iajs-2946	22	11	distribution	distribution	NOUN
iajs-2946	22	12	where	where	SCONJ
iajs-2946	22	13	γ	γ	X
iajs-2946	22	14	=	=	SYM
iajs-2946	22	15	1	1	NUM
iajs-2946	22	16	[	[	X
iajs-2946	22	17	2	2	NUM
iajs-2946	22	18	]	]	PUNCT
iajs-2946	22	19	.	.	PUNCT
iajs-2946	23	1	the	the	DET
iajs-2946	23	2	cumulative	cumulative	ADJ
iajs-2946	23	3	distribution	distribution	NOUN
iajs-2946	23	4	function	function	NOUN
iajs-2946	23	5	(	(	PUNCT
iajs-2946	23	6	cdf	cdf	PROPN
iajs-2946	23	7	)	)	PUNCT
iajs-2946	23	8	of	of	ADP
iajs-2946	23	9	the	the	DET
iajs-2946	23	10	exponential	exponential	ADJ
iajs-2946	23	11	distribution	distribution	NOUN
iajs-2946	23	12	is	be	AUX
iajs-2946	23	13	:	:	PUNCT
iajs-2946	23	14	𝐹(𝑥	𝐹(𝑥	NUM
iajs-2946	23	15	;	;	PUNCT
iajs-2946	23	16	𝛾	𝛾	NOUN
iajs-2946	23	17	,	,	PUNCT
iajs-2946	23	18	𝛿	𝛿	ADJ
iajs-2946	23	19	)	)	PUNCT
iajs-2946	23	20	=	=	SYM
iajs-2946	24	1	1	1	NUM
iajs-2946	24	2	−	−	NOUN
iajs-2946	24	3	𝑒	𝑒	PROPN
iajs-2946	24	4	−	−	PROPN
iajs-2946	24	5	(	(	PUNCT
iajs-2946	24	6	𝑥−𝛿	𝑥−𝛿	NOUN
iajs-2946	24	7	)	)	PUNCT
iajs-2946	24	8	𝛾	𝛾	NOUN
iajs-2946	24	9	.	.	PUNCT
iajs-2946	25	1	(	(	PUNCT
iajs-2946	25	2	2	2	X
iajs-2946	25	3	)	)	PUNCT
iajs-2946	25	4	in	in	ADP
iajs-2946	25	5	general	general	ADJ
iajs-2946	25	6	,	,	PUNCT
iajs-2946	25	7	the	the	DET
iajs-2946	25	8	reliability	reliability	NOUN
iajs-2946	25	9	function	function	NOUN
iajs-2946	25	10	is	be	AUX
iajs-2946	25	11	defined	define	VERB
iajs-2946	25	12	as	as	SCONJ
iajs-2946	25	13	follows	follow	VERB
iajs-2946	25	14	:	:	PUNCT
iajs-2946	25	15	𝑅(𝑥	𝑅(𝑥	NUM
iajs-2946	25	16	;	;	PUNCT
iajs-2946	25	17	𝛾	𝛾	NOUN
iajs-2946	25	18	,	,	PUNCT
iajs-2946	25	19	𝛿	𝛿	ADJ
iajs-2946	25	20	)	)	PUNCT
iajs-2946	25	21	=	=	SYM
iajs-2946	25	22	1	1	NUM
iajs-2946	25	23	−	−	NOUN
iajs-2946	25	24	𝐹(𝑥	𝐹(𝑥	NUM
iajs-2946	25	25	;	;	PUNCT
iajs-2946	25	26	𝛾	𝛾	NOUN
iajs-2946	25	27	,	,	PUNCT
iajs-2946	25	28	𝛿	𝛿	ADJ
iajs-2946	25	29	)	)	PUNCT
iajs-2946	25	30	.	.	PUNCT
iajs-2946	26	1	therefore	therefore	ADV
iajs-2946	26	2	,	,	PUNCT
iajs-2946	26	3	the	the	DET
iajs-2946	26	4	reliability	reliability	NOUN
iajs-2946	26	5	function	function	NOUN
iajs-2946	26	6	r(t	r(t	NOUN
iajs-2946	26	7	)	)	PUNCT
iajs-2946	26	8	of	of	ADP
iajs-2946	26	9	the	the	DET
iajs-2946	26	10	exponential	exponential	ADJ
iajs-2946	26	11	distribution	distribution	NOUN
iajs-2946	26	12	is	be	AUX
iajs-2946	26	13	:	:	PUNCT
iajs-2946	26	14	𝑅(𝑥	𝑅(𝑥	NUM
iajs-2946	26	15	;	;	PUNCT
iajs-2946	26	16	𝛾	𝛾	NOUN
iajs-2946	26	17	,	,	PUNCT
iajs-2946	26	18	𝛿	𝛿	ADJ
iajs-2946	26	19	)	)	PUNCT
iajs-2946	26	20	=	=	SYM
iajs-2946	26	21	𝑒	𝑒	PROPN
iajs-2946	26	22	−	−	PROPN
iajs-2946	26	23	(	(	PUNCT
iajs-2946	26	24	𝑥−𝛿	𝑥−𝛿	NOUN
iajs-2946	26	25	)	)	PUNCT
iajs-2946	26	26	𝛾	𝛾	NOUN
iajs-2946	26	27	.	.	PUNCT
iajs-2946	27	1	(	(	PUNCT
iajs-2946	27	2	3	3	X
iajs-2946	27	3	)	)	PUNCT
iajs-2946	27	4	the	the	DET
iajs-2946	27	5	hazard	hazard	NOUN
iajs-2946	27	6	function	function	NOUN
iajs-2946	27	7	is	be	AUX
iajs-2946	27	8	given	give	VERB
iajs-2946	27	9	by	by	ADP
iajs-2946	27	10	:	:	PUNCT
iajs-2946	27	11	ℎ(𝑥	ℎ(𝑥	NUM
iajs-2946	27	12	;	;	PUNCT
iajs-2946	27	13	𝛾	𝛾	NOUN
iajs-2946	27	14	,	,	PUNCT
iajs-2946	27	15	𝛿	𝛿	ADJ
iajs-2946	27	16	)	)	PUNCT
iajs-2946	27	17	=	=	SYM
iajs-2946	27	18	𝑓(𝑥	𝑓(𝑥	NOUN
iajs-2946	27	19	;	;	PUNCT
iajs-2946	27	20	𝛾	𝛾	NOUN
iajs-2946	27	21	,	,	PUNCT
iajs-2946	27	22	𝛿	𝛿	ADJ
iajs-2946	27	23	)	)	PUNCT
iajs-2946	27	24	𝑅(𝑥	𝑅(𝑥	NOUN
iajs-2946	27	25	;	;	PUNCT
iajs-2946	27	26	𝛾	𝛾	NOUN
iajs-2946	27	27	,	,	PUNCT
iajs-2946	27	28	𝛿	𝛿	ADJ
iajs-2946	27	29	)	)	PUNCT
iajs-2946	27	30	.	.	PUNCT
iajs-2946	28	1	after	after	ADP
iajs-2946	28	2	substituting	substitute	VERB
iajs-2946	28	3	(	(	PUNCT
iajs-2946	28	4	1	1	NUM
iajs-2946	28	5	)	)	PUNCT
iajs-2946	28	6	and	and	CCONJ
iajs-2946	28	7	(	(	PUNCT
iajs-2946	28	8	2	2	X
iajs-2946	28	9	)	)	PUNCT
iajs-2946	28	10	into	into	ADP
iajs-2946	28	11	ℎ(𝑥	ℎ(𝑥	NUM
iajs-2946	28	12	;	;	PUNCT
iajs-2946	28	13	𝛾	𝛾	NOUN
iajs-2946	28	14	,	,	PUNCT
iajs-2946	28	15	𝛿	𝛿	ADJ
iajs-2946	28	16	)	)	PUNCT
iajs-2946	28	17	,	,	PUNCT
iajs-2946	28	18	the	the	DET
iajs-2946	28	19	hazard	hazard	NOUN
iajs-2946	28	20	function	function	NOUN
iajs-2946	28	21	of	of	ADP
iajs-2946	28	22	exponential	exponential	ADJ
iajs-2946	28	23	distribution	distribution	NOUN
iajs-2946	28	24	becomes	become	VERB
iajs-2946	28	25	as	as	SCONJ
iajs-2946	28	26	follows	follow	VERB
iajs-2946	28	27	:	:	PUNCT
iajs-2946	28	28	ℎ(𝑥	ℎ(𝑥	NUM
iajs-2946	28	29	;	;	PUNCT
iajs-2946	28	30	𝛾	𝛾	NOUN
iajs-2946	28	31	,	,	PUNCT
iajs-2946	28	32	𝛿	𝛿	ADJ
iajs-2946	28	33	)	)	PUNCT
iajs-2946	28	34	=	=	SYM
iajs-2946	28	35	1	1	NUM
iajs-2946	28	36	𝛾	𝛾	NOUN
iajs-2946	28	37	.	.	PUNCT
iajs-2946	29	1	(	(	PUNCT
iajs-2946	29	2	4	4	NUM
iajs-2946	29	3	)	)	SYM
iajs-2946	29	4	2	2	NUM
iajs-2946	29	5	.	.	X
iajs-2946	29	6	estimation	estimation	NOUN
iajs-2946	29	7	methods	method	NOUN
iajs-2946	29	8	this	this	DET
iajs-2946	29	9	section	section	NOUN
iajs-2946	29	10	focuses	focus	VERB
iajs-2946	29	11	on	on	ADP
iajs-2946	29	12	some	some	DET
iajs-2946	29	13	bayesian	bayesian	NOUN
iajs-2946	29	14	estimators	estimator	NOUN
iajs-2946	29	15	of	of	ADP
iajs-2946	29	16	the	the	DET
iajs-2946	29	17	two	two	NUM
iajs-2946	29	18	unknown	unknown	ADJ
iajs-2946	29	19	parameters	parameter	NOUN
iajs-2946	29	20	of	of	ADP
iajs-2946	29	21	exponential	exponential	ADJ
iajs-2946	29	22	distribution	distribution	NOUN
iajs-2946	29	23	using	use	VERB
iajs-2946	29	24	the	the	DET
iajs-2946	29	25	maximum	maximum	ADJ
iajs-2946	29	26	likelihood	likelihood	NOUN
iajs-2946	29	27	estimator	estimator	NOUN
iajs-2946	29	28	(	(	PUNCT
iajs-2946	29	29	mle	mle	PROPN
iajs-2946	29	30	)	)	PUNCT
iajs-2946	29	31	as	as	ADP
iajs-2946	29	32	an	an	DET
iajs-2946	29	33	initial	initial	ADJ
iajs-2946	29	34	values	value	NOUN
iajs-2946	29	35	for	for	ADP
iajs-2946	29	36	bayesian	bayesian	NOUN
iajs-2946	29	37	estimators	estimator	NOUN
iajs-2946	29	38	.	.	PUNCT
iajs-2946	30	1	2.1	2.1	NUM
iajs-2946	30	2	maximum	maximum	ADJ
iajs-2946	30	3	likelihood	likelihood	NOUN
iajs-2946	30	4	estimator	estimator	NOUN
iajs-2946	30	5	(	(	PUNCT
iajs-2946	30	6	mle	mle	PROPN
iajs-2946	30	7	)	)	PUNCT
iajs-2946	30	8	the	the	DET
iajs-2946	30	9	maximum	maximum	ADJ
iajs-2946	30	10	likelihood	likelihood	NOUN
iajs-2946	30	11	(	(	PUNCT
iajs-2946	30	12	ml	ml	NOUN
iajs-2946	30	13	)	)	PUNCT
iajs-2946	30	14	method	method	NOUN
iajs-2946	30	15	was	be	AUX
iajs-2946	30	16	developed	develop	VERB
iajs-2946	30	17	by	by	ADP
iajs-2946	30	18	r.	r.	PROPN
iajs-2946	30	19	a.	a.	PROPN
iajs-2946	30	20	fisher	fisher	PROPN
iajs-2946	30	21	(	(	PUNCT
iajs-2946	30	22	1912	1912	NUM
iajs-2946	30	23	)	)	PUNCT
iajs-2946	30	24	and	and	CCONJ
iajs-2946	30	25	has	have	AUX
iajs-2946	30	26	been	be	AUX
iajs-2946	30	27	widely	widely	ADV
iajs-2946	30	28	used	use	VERB
iajs-2946	30	29	since	since	SCONJ
iajs-2946	30	30	then	then	ADV
iajs-2946	30	31	[	[	X
iajs-2946	30	32	3	3	NUM
iajs-2946	30	33	]	]	PUNCT
iajs-2946	30	34	.	.	PUNCT
iajs-2946	31	1	the	the	DET
iajs-2946	31	2	maximum	maximum	ADJ
iajs-2946	31	3	likelihood	likelihood	NOUN
iajs-2946	31	4	method	method	NOUN
iajs-2946	31	5	aims	aim	VERB
iajs-2946	31	6	to	to	PART
iajs-2946	31	7	maximize	maximize	VERB
iajs-2946	31	8	the	the	DET
iajs-2946	31	9	likelihood	likelihood	NOUN
iajs-2946	31	10	function	function	NOUN
iajs-2946	31	11	.	.	PUNCT
iajs-2946	32	1	assume	assume	VERB
iajs-2946	32	2	that	that	SCONJ
iajs-2946	32	3	𝑥1	𝑥1	NOUN
iajs-2946	32	4	,	,	PUNCT
iajs-2946	32	5	𝑥2	𝑥2	NOUN
iajs-2946	32	6	,	,	PUNCT
iajs-2946	32	7	…	…	PUNCT
iajs-2946	32	8	,	,	PUNCT
iajs-2946	32	9	𝑥𝑛	𝑥𝑛	PROPN
iajs-2946	32	10	are	be	AUX
iajs-2946	32	11	a	a	DET
iajs-2946	32	12	random	random	ADJ
iajs-2946	32	13	samples	sample	NOUN
iajs-2946	32	14	of	of	ADP
iajs-2946	32	15	size	size	NOUN
iajs-2946	32	16	(	(	PUNCT
iajs-2946	32	17	𝑛	𝑛	NOUN
iajs-2946	32	18	)	)	PUNCT
iajs-2946	32	19	drawn	draw	VERB
iajs-2946	32	20	from	from	ADP
iajs-2946	32	21	an	an	DET
iajs-2946	32	22	exponential	exponential	ADJ
iajs-2946	32	23	distribution	distribution	NOUN
iajs-2946	32	24	with	with	ADP
iajs-2946	32	25	scale	scale	NOUN
iajs-2946	32	26	parameter	parameter	NOUN
iajs-2946	32	27	γ	γ	NOUN
iajs-2946	32	28	and	and	CCONJ
iajs-2946	32	29	the	the	DET
iajs-2946	32	30	location	location	NOUN
iajs-2946	32	31	parameter	parameter	PROPN
iajs-2946	32	32	δ	δ	PROPN
iajs-2946	32	33	.	.	PUNCT
iajs-2946	33	1	then	then	ADV
iajs-2946	33	2	,	,	PUNCT
iajs-2946	33	3	the	the	DET
iajs-2946	33	4	maximum	maximum	ADJ
iajs-2946	33	5	likelihood	likelihood	NOUN
iajs-2946	33	6	estimator	estimator	NOUN
iajs-2946	33	7	can	can	AUX
iajs-2946	33	8	be	be	AUX
iajs-2946	33	9	obtained	obtain	VERB
iajs-2946	33	10	by	by	ADP
iajs-2946	33	11	deriving	derive	VERB
iajs-2946	33	12	the	the	DET
iajs-2946	33	13	logarithm	logarithm	NOUN
iajs-2946	33	14	of	of	ADP
iajs-2946	33	15	the	the	DET
iajs-2946	33	16	likelihood	likelihood	NOUN
iajs-2946	33	17	function	function	NOUN
iajs-2946	33	18	and	and	CCONJ
iajs-2946	33	19	its	its	PRON
iajs-2946	33	20	equality	equality	NOUN
iajs-2946	33	21	to	to	ADP
iajs-2946	33	22	zero	zero	NUM
iajs-2946	33	23	.	.	PUNCT
iajs-2946	34	1	the	the	DET
iajs-2946	34	2	likelihood	likelihood	NOUN
iajs-2946	34	3	function	function	NOUN
iajs-2946	34	4	for	for	ADP
iajs-2946	34	5	the	the	DET
iajs-2946	34	6	two	two	NUM
iajs-2946	34	7	-	-	PUNCT
iajs-2946	34	8	parameter	parameter	NOUN
iajs-2946	34	9	the	the	DET
iajs-2946	34	10	exponential	exponential	ADJ
iajs-2946	34	11	distribution	distribution	NOUN
iajs-2946	34	12	will	will	AUX
iajs-2946	34	13	be	be	AUX
iajs-2946	34	14	as	as	SCONJ
iajs-2946	34	15	follows	follow	VERB
iajs-2946	34	16	:	:	PUNCT
iajs-2946	34	17	𝐿(𝛾	𝐿(𝛾	NUM
iajs-2946	34	18	,	,	PUNCT
iajs-2946	34	19	δ|	δ|	NOUN
iajs-2946	34	20	𝑥	𝑥	X
iajs-2946	34	21	)	)	PUNCT
iajs-2946	35	1	=	=	SYM
iajs-2946	35	2	∏	∏	PROPN
iajs-2946	35	3	𝑓(𝑥𝑖	𝑓(𝑥𝑖	PROPN
iajs-2946	35	4	;	;	PUNCT
iajs-2946	35	5	𝑛	𝑛	PRON
iajs-2946	35	6	𝑖=1	𝑖=1	PROPN
iajs-2946	35	7	𝛾	𝛾	PROPN
iajs-2946	35	8	,	,	PUNCT
iajs-2946	35	9	δ	δ	X
iajs-2946	35	10	)	)	PUNCT
iajs-2946	35	11	=	=	SYM
iajs-2946	35	12	∏	∏	PROPN
iajs-2946	35	13	[	[	PUNCT
iajs-2946	35	14	1	1	NUM
iajs-2946	35	15	𝛾	𝛾	NOUN
iajs-2946	35	16	𝑒	𝑒	ADP
iajs-2946	35	17	−	−	NOUN
iajs-2946	35	18	(	(	PUNCT
iajs-2946	35	19	𝑥−𝛿	𝑥−𝛿	NOUN
iajs-2946	35	20	)	)	PUNCT
iajs-2946	35	21	𝛾	𝛾	ADP
iajs-2946	35	22	]	]	X
iajs-2946	35	23	𝑛	𝑛	PRON
iajs-2946	35	24	𝑖=1	𝑖=1	PUNCT
iajs-2946	35	25	=	=	SYM
iajs-2946	35	26	1	1	NUM
iajs-2946	35	27	𝛾𝑛	𝛾𝑛	NOUN
iajs-2946	35	28	𝑒	𝑒	PROPN
iajs-2946	35	29	−	−	PROPN
iajs-2946	35	30	1	1	NUM
iajs-2946	35	31	𝛾	𝛾	NOUN
iajs-2946	35	32	∑	∑	PUNCT
iajs-2946	35	33	(	(	PUNCT
iajs-2946	35	34	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	35	35	𝑖=1	𝑖=1	PROPN
iajs-2946	35	36	.	.	PUNCT
iajs-2946	36	1	(	(	PUNCT
iajs-2946	36	2	5	5	X
iajs-2946	36	3	)	)	PUNCT
iajs-2946	36	4	the	the	DET
iajs-2946	36	5	logarithm	logarithm	NOUN
iajs-2946	36	6	of	of	ADP
iajs-2946	36	7	the	the	DET
iajs-2946	36	8	likelihood	likelihood	NOUN
iajs-2946	36	9	function	function	NOUN
iajs-2946	36	10	is	be	AUX
iajs-2946	36	11	given	give	VERB
iajs-2946	36	12	by	by	ADP
iajs-2946	36	13	.	.	PUNCT
iajs-2946	37	1	ℓ𝑀𝐿	ℓ𝑀𝐿	PROPN
iajs-2946	37	2	=	=	PUNCT
iajs-2946	38	1	−	−	PROPN
iajs-2946	38	2	nln	nln	NOUN
iajs-2946	38	3	𝛾−	𝛾−	PROPN
iajs-2946	38	4	1	1	NUM
iajs-2946	38	5	𝛾	𝛾	PROPN
iajs-2946	38	6	∑	∑	PUNCT
iajs-2946	38	7	(	(	PUNCT
iajs-2946	38	8	𝑥𝑖	𝑥𝑖	ADV
iajs-2946	38	9	−	−	PROPN
iajs-2946	38	10	𝛿)𝑛	𝛿)𝑛	NOUN
iajs-2946	38	11	𝑖=1	𝑖=1	PUNCT
iajs-2946	38	12	.	.	PUNCT
iajs-2946	39	1	(	(	PUNCT
iajs-2946	39	2	6	6	X
iajs-2946	39	3	)	)	PUNCT
iajs-2946	39	4	differentiating	differentiate	VERB
iajs-2946	39	5	ℓ𝑀𝐿	ℓ𝑀𝐿	PROPN
iajs-2946	39	6	partially	partially	ADV
iajs-2946	39	7	with	with	ADP
iajs-2946	39	8	respect	respect	NOUN
iajs-2946	39	9	to	to	ADP
iajs-2946	39	10	𝛾	𝛾	PROPN
iajs-2946	39	11	and	and	CCONJ
iajs-2946	39	12	𝛿	𝛿	ADJ
iajs-2946	39	13	,	,	PUNCT
iajs-2946	39	14	respectively	respectively	ADV
iajs-2946	39	15	and	and	CCONJ
iajs-2946	39	16	equating	equate	VERB
iajs-2946	39	17	to	to	ADP
iajs-2946	39	18	zero	zero	NUM
iajs-2946	39	19	yields	yield	NOUN
iajs-2946	39	20	:	:	PUNCT
iajs-2946	39	21	𝜕ℓ𝑀𝐿	𝜕ℓ𝑀𝐿	NUM
iajs-2946	39	22	𝜕δ	𝜕δ	NOUN
iajs-2946	39	23	=	=	PUNCT
iajs-2946	39	24	−𝑛	−𝑛	NOUN
iajs-2946	39	25	𝛾	𝛾	NOUN
iajs-2946	39	26	=	=	SYM
iajs-2946	39	27	0	0	X
iajs-2946	39	28	.	.	PUNCT
iajs-2946	39	29	ihjpas	ihjpas	PROPN
iajs-2946	39	30	.	.	PUNCT
iajs-2946	40	1	36(2)2023	36(2)2023	NUM
iajs-2946	40	2	291	291	NUM
iajs-2946	40	3	notice	notice	NOUN
iajs-2946	40	4	that	that	SCONJ
iajs-2946	40	5	,	,	PUNCT
iajs-2946	40	6	δ	δ	PROPN
iajs-2946	40	7	̂	̂	PUNCT
iajs-2946	40	8	that	that	PRON
iajs-2946	40	9	maximizes	maximize	VERB
iajs-2946	40	10	the	the	DET
iajs-2946	40	11	likelihood	likelihood	NOUN
iajs-2946	40	12	function	function	NOUN
iajs-2946	40	13	can	can	AUX
iajs-2946	40	14	be	be	AUX
iajs-2946	40	15	obtained	obtain	VERB
iajs-2946	40	16	using	use	VERB
iajs-2946	40	17	order	order	NOUN
iajs-2946	40	18	statistic	statistic	NOUN
iajs-2946	40	19	where	where	SCONJ
iajs-2946	40	20	,	,	PUNCT
iajs-2946	40	21	δ̂	δ̂	NOUN
iajs-2946	40	22	=	=	SYM
iajs-2946	40	23	min(x1	min(x1	PROPN
iajs-2946	40	24	,	,	PUNCT
iajs-2946	40	25	x2	x2	PROPN
iajs-2946	40	26	,	,	PUNCT
iajs-2946	40	27	…	…	PUNCT
iajs-2946	40	28	,	,	PUNCT
iajs-2946	40	29	xn	xn	X
iajs-2946	40	30	)	)	PUNCT
iajs-2946	40	31	=	=	PUNCT
iajs-2946	40	32	𝑋(1	𝑋(1	NUM
iajs-2946	40	33	)	)	PUNCT
iajs-2946	40	34	.	.	PUNCT
iajs-2946	41	1	𝜕ℓ𝑀𝐿	𝜕ℓ𝑀𝐿	PROPN
iajs-2946	41	2	𝜕γ	𝜕γ	PROPN
iajs-2946	41	3	=	=	PRON
iajs-2946	41	4	−𝑛	−𝑛	VERB
iajs-2946	41	5	𝛾	𝛾	ADP
iajs-2946	41	6	+	+	ADJ
iajs-2946	41	7	1	1	NUM
iajs-2946	41	8	𝛾2	𝛾2	NOUN
iajs-2946	41	9	∑	∑	PUNCT
iajs-2946	41	10	(	(	PUNCT
iajs-2946	41	11	𝑥𝑖	𝑥𝑖	ADV
iajs-2946	41	12	−	−	PROPN
iajs-2946	41	13	𝛿)𝑛	𝛿)𝑛	X
iajs-2946	41	14	𝑖=1	𝑖=1	PUNCT
iajs-2946	42	1	=	=	SYM
iajs-2946	42	2	0	0	X
iajs-2946	42	3	.	.	PUNCT
iajs-2946	43	1	after	after	ADP
iajs-2946	43	2	some	some	DET
iajs-2946	43	3	simplification	simplification	NOUN
iajs-2946	43	4	,	,	PUNCT
iajs-2946	43	5	we	we	PRON
iajs-2946	43	6	get	get	VERB
iajs-2946	43	7	:	:	PUNCT
iajs-2946	43	8	𝛾	𝛾	X
iajs-2946	43	9	=	=	SYM
iajs-2946	43	10	1	1	NUM
iajs-2946	43	11	𝑛	𝑛	NOUN
iajs-2946	43	12	∑	∑	PUNCT
iajs-2946	43	13	(	(	PUNCT
iajs-2946	43	14	𝑥𝑖	𝑥𝑖	ADP
iajs-2946	43	15	−	−	PROPN
iajs-2946	43	16	𝑋(1))𝑛	𝑋(1))𝑛	NUM
iajs-2946	43	17	𝑖=1	𝑖=1	PROPN
iajs-2946	43	18	.	.	PUNCT
iajs-2946	44	1	3	3	X
iajs-2946	44	2	.	.	X
iajs-2946	44	3	bayesian	bayesian	NOUN
iajs-2946	44	4	estimation	estimation	NOUN
iajs-2946	44	5	3.1	3.1	NUM
iajs-2946	44	6	posterior	posterior	ADJ
iajs-2946	44	7	density	density	NOUN
iajs-2946	44	8	function	function	NOUN
iajs-2946	44	9	using	use	VERB
iajs-2946	44	10	exponential	exponential	NOUN
iajs-2946	44	11	and	and	CCONJ
iajs-2946	44	12	gamma	gamma	NOUN
iajs-2946	44	13	priors	prior	NOUN
iajs-2946	44	14	to	to	PART
iajs-2946	44	15	estimate	estimate	VERB
iajs-2946	44	16	the	the	DET
iajs-2946	44	17	two	two	NUM
iajs-2946	44	18	unknown	unknown	ADJ
iajs-2946	44	19	parameters	parameter	NOUN
iajs-2946	44	20	for	for	ADP
iajs-2946	44	21	exponential	exponential	ADJ
iajs-2946	44	22	distribution	distribution	NOUN
iajs-2946	44	23	𝛾	𝛾	NOUN
iajs-2946	44	24	and	and	CCONJ
iajs-2946	44	25	δ	δ	PROPN
iajs-2946	44	26	,	,	PUNCT
iajs-2946	44	27	the	the	DET
iajs-2946	44	28	prior	prior	NOUN
iajs-2946	44	29	for	for	ADP
iajs-2946	44	30	𝛾	𝛾	PROPN
iajs-2946	44	31	j1	j1	PROPN
iajs-2946	44	32	(	(	PUNCT
iajs-2946	44	33	.	.	PUNCT
iajs-2946	44	34	)	)	PUNCT
iajs-2946	44	35	is	be	AUX
iajs-2946	44	36	assumed	assume	VERB
iajs-2946	44	37	as	as	ADP
iajs-2946	44	38	exponential	exponential	ADJ
iajs-2946	44	39	distribution	distribution	NOUN
iajs-2946	44	40	with	with	ADP
iajs-2946	44	41	the	the	DET
iajs-2946	44	42	scale	scale	NOUN
iajs-2946	44	43	parameter	parameter	NOUN
iajs-2946	44	44	c	c	NOUN
iajs-2946	44	45	,	,	PUNCT
iajs-2946	44	46	i.e.	i.e.	X
iajs-2946	44	47	[	[	X
iajs-2946	44	48	4	4	NUM
iajs-2946	44	49	]	]	PUNCT
iajs-2946	44	50	:	:	PUNCT
iajs-2946	44	51	j1(𝛾)=	j1(𝛾)=	PROPN
iajs-2946	44	52	{	{	PUNCT
iajs-2946	44	53	𝑐𝑒−𝑐𝛾	𝑐𝑒−𝑐𝛾	NOUN
iajs-2946	44	54	;	;	PUNCT
iajs-2946	44	55	𝑐	𝑐	X
iajs-2946	44	56	>	>	X
iajs-2946	44	57	0	0	NUM
iajs-2946	44	58	,	,	PUNCT
iajs-2946	44	59	𝛾	𝛾	X
iajs-2946	44	60	>	>	X
iajs-2946	44	61	0	0	NUM
iajs-2946	44	62	0	0	NUM
iajs-2946	44	63	;	;	PUNCT
iajs-2946	44	64	0	0	X
iajs-2946	45	1	.	.	X
iajs-2946	45	2	𝑤	𝑤	X
iajs-2946	45	3	on	on	ADP
iajs-2946	45	4	the	the	DET
iajs-2946	45	5	other	other	ADJ
iajs-2946	45	6	hand	hand	NOUN
iajs-2946	45	7	,	,	PUNCT
iajs-2946	45	8	the	the	DET
iajs-2946	45	9	prior	prior	ADJ
iajs-2946	45	10	distribution	distribution	NOUN
iajs-2946	45	11	j2	j2	NOUN
iajs-2946	45	12	(	(	PUNCT
iajs-2946	45	13	.	.	PUNCT
iajs-2946	45	14	)	)	PUNCT
iajs-2946	46	1	for	for	SCONJ
iajs-2946	46	2	δ	δ	PROPN
iajs-2946	46	3	is	be	AUX
iajs-2946	46	4	assumed	assume	VERB
iajs-2946	46	5	as	as	ADP
iajs-2946	46	6	the	the	DET
iajs-2946	46	7	gamma	gamma	NOUN
iajs-2946	46	8	distribution	distribution	NOUN
iajs-2946	46	9	with	with	ADP
iajs-2946	46	10	two	two	NUM
iajs-2946	46	11	unknown	unknown	ADJ
iajs-2946	46	12	parameters	parameter	NOUN
iajs-2946	46	13	(	(	PUNCT
iajs-2946	46	14	a	a	DET
iajs-2946	46	15	,	,	PUNCT
iajs-2946	46	16	b	b	NOUN
iajs-2946	46	17	)	)	PUNCT
iajs-2946	46	18	as	as	ADP
iajs-2946	46	19	a	a	DET
iajs-2946	46	20	scale	scale	NOUN
iajs-2946	46	21	and	and	CCONJ
iajs-2946	46	22	shape	shape	NOUN
iajs-2946	46	23	parameters	parameter	NOUN
iajs-2946	46	24	for	for	ADP
iajs-2946	46	25	𝜇	𝜇	ADP
iajs-2946	46	26	respectively	respectively	ADV
iajs-2946	46	27	.	.	PUNCT
iajs-2946	47	1	i.e.	i.e.	X
iajs-2946	47	2	[	[	X
iajs-2946	47	3	4	4	NUM
iajs-2946	47	4	]	]	PUNCT
iajs-2946	47	5	:	:	PUNCT
iajs-2946	47	6	j2(δ	j2(δ	X
iajs-2946	47	7	)	)	PUNCT
iajs-2946	47	8	=	=	PRON
iajs-2946	47	9	{	{	PUNCT
iajs-2946	47	10	(	(	PUNCT
iajs-2946	47	11	𝑏)𝑎δ𝑎−1𝑒−𝑏δ	𝑏)𝑎δ𝑎−1𝑒−𝑏δ	NOUN
iajs-2946	47	12	γ(𝑎	γ(𝑎	PROPN
iajs-2946	47	13	)	)	PUNCT
iajs-2946	47	14	;	;	PUNCT
iajs-2946	47	15	a	a	DET
iajs-2946	47	16	>	>	X
iajs-2946	47	17	0	0	NUM
iajs-2946	47	18	,	,	PUNCT
iajs-2946	47	19	b	b	X
iajs-2946	47	20	>	>	X
iajs-2946	47	21	0	0	PROPN
iajs-2946	47	22	,	,	PUNCT
iajs-2946	47	23	δ	δ	X
iajs-2946	47	24	>	>	X
iajs-2946	47	25	0	0	NUM
iajs-2946	47	26	0	0	NUM
iajs-2946	47	27	;	;	PUNCT
iajs-2946	47	28	0	0	X
iajs-2946	47	29	.	.	X
iajs-2946	47	30	𝑤	𝑤	ADP
iajs-2946	47	31	furthermore	furthermore	ADV
iajs-2946	47	32	,	,	PUNCT
iajs-2946	47	33	γ	γ	PROPN
iajs-2946	47	34	and	and	CCONJ
iajs-2946	47	35	μ	μ	PROPN
iajs-2946	47	36	are	be	AUX
iajs-2946	47	37	assumed	assume	VERB
iajs-2946	47	38	as	as	ADP
iajs-2946	47	39	independent	independent	ADJ
iajs-2946	47	40	random	random	ADJ
iajs-2946	47	41	variables	variable	NOUN
iajs-2946	47	42	.	.	PUNCT
iajs-2946	48	1	therefore	therefore	ADV
iajs-2946	48	2	,	,	PUNCT
iajs-2946	48	3	the	the	DET
iajs-2946	48	4	joint	joint	ADJ
iajs-2946	48	5	prior	prior	ADJ
iajs-2946	48	6	distribution	distribution	NOUN
iajs-2946	48	7	of	of	ADP
iajs-2946	48	8	γ	γ	PROPN
iajs-2946	48	9	and	and	CCONJ
iajs-2946	48	10	δ	δ	PROPN
iajs-2946	48	11	will	will	AUX
iajs-2946	48	12	be	be	AUX
iajs-2946	48	13	as	as	SCONJ
iajs-2946	48	14	follows	follow	VERB
iajs-2946	48	15	:	:	PUNCT
iajs-2946	48	16	j(γ	j(γ	PROPN
iajs-2946	48	17	,	,	PUNCT
iajs-2946	48	18	δ	δ	X
iajs-2946	48	19	)	)	PUNCT
iajs-2946	48	20	=	=	SYM
iajs-2946	48	21	j1(γ	j1(γ	PROPN
iajs-2946	48	22	)	)	PUNCT
iajs-2946	48	23	j2(δ	j2(δ	X
iajs-2946	48	24	)	)	PUNCT
iajs-2946	48	25	=	=	SYM
iajs-2946	48	26	𝑐𝑒−𝑐𝛾	𝑐𝑒−𝑐𝛾	NOUN
iajs-2946	48	27	(	(	PUNCT
iajs-2946	48	28	𝑏)𝑎δ𝑎−1𝑒−𝑏δ	𝑏)𝑎δ𝑎−1𝑒−𝑏δ	NOUN
iajs-2946	48	29	γ(𝑎	γ(𝑎	NOUN
iajs-2946	48	30	)	)	PUNCT
iajs-2946	48	31	.	.	PUNCT
iajs-2946	49	1	hence	hence	ADV
iajs-2946	49	2	,	,	PUNCT
iajs-2946	49	3	the	the	DET
iajs-2946	49	4	joint	joint	ADJ
iajs-2946	49	5	posterior	posterior	ADJ
iajs-2946	49	6	density	density	NOUN
iajs-2946	49	7	function	function	NOUN
iajs-2946	49	8	of	of	ADP
iajs-2946	49	9	γ	γ	PROPN
iajs-2946	49	10	and	and	CCONJ
iajs-2946	49	11	δ	δ	PROPN
iajs-2946	49	12	is	be	AUX
iajs-2946	49	13	given	give	VERB
iajs-2946	49	14	by	by	ADP
iajs-2946	49	15	:	:	PUNCT
iajs-2946	49	16	h(γ	h(γ	PROPN
iajs-2946	49	17	,	,	PUNCT
iajs-2946	49	18	δ|x1	δ|x1	PROPN
iajs-2946	49	19	,	,	PUNCT
iajs-2946	49	20	x2	x2	PROPN
iajs-2946	49	21	,	,	PUNCT
iajs-2946	49	22	…	…	PUNCT
iajs-2946	49	23	,	,	PUNCT
iajs-2946	49	24	xn	xn	X
iajs-2946	49	25	)	)	PUNCT
iajs-2946	49	26	=	=	SYM
iajs-2946	49	27	l(x1	l(x1	NOUN
iajs-2946	49	28	,	,	PUNCT
iajs-2946	49	29	x2	x2	PROPN
iajs-2946	49	30	,	,	PUNCT
iajs-2946	49	31	…	…	PUNCT
iajs-2946	49	32	,	,	PUNCT
iajs-2946	49	33	xn	xn	PROPN
iajs-2946	49	34	,	,	PUNCT
iajs-2946	49	35	;	;	PUNCT
iajs-2946	49	36	γ	γ	X
iajs-2946	49	37	,	,	PUNCT
iajs-2946	49	38	δ	δ	PROPN
iajs-2946	49	39	)	)	PUNCT
iajs-2946	49	40	j(γ	j(γ	PROPN
iajs-2946	49	41	,	,	PUNCT
iajs-2946	49	42	δ	δ	PROPN
iajs-2946	49	43	)	)	PUNCT
iajs-2946	49	44	∫	∫	PROPN
iajs-2946	49	45	∫	∫	PROPN
iajs-2946	49	46	l(x1	l(x1	PROPN
iajs-2946	49	47	,	,	PUNCT
iajs-2946	49	48	x2	x2	PROPN
iajs-2946	49	49	,	,	PUNCT
iajs-2946	49	50	…	…	PUNCT
iajs-2946	49	51	,	,	PUNCT
iajs-2946	49	52	xn	xn	PROPN
iajs-2946	49	53	,	,	PUNCT
iajs-2946	49	54	;	;	PUNCT
iajs-2946	49	55	γ	γ	X
iajs-2946	49	56	,	,	PUNCT
iajs-2946	49	57	δ	δ	PROPN
iajs-2946	49	58	)	)	PUNCT
iajs-2946	49	59	j(γ	j(γ	PROPN
iajs-2946	49	60	,	,	PUNCT
iajs-2946	49	61	δ)dγdδ	δ)dγdδ	PROPN
iajs-2946	49	62	∞	∞	PROPN
iajs-2946	49	63	0	0	NUM
iajs-2946	50	1	∞	∞	NUM
iajs-2946	50	2	0	0	NUM
iajs-2946	50	3	,	,	PUNCT
iajs-2946	50	4	ℎ(𝛾	ℎ(𝛾	PROPN
iajs-2946	50	5	,	,	PUNCT
iajs-2946	50	6	δ	δ	PROPN
iajs-2946	50	7	│	│	NOUN
iajs-2946	50	8	x	x	X
iajs-2946	50	9	)	)	PUNCT
iajs-2946	50	10	=	=	PUNCT
iajs-2946	50	11	𝛾−𝒏	𝛾−𝒏	X
iajs-2946	50	12	𝒆	𝒆	X
iajs-2946	50	13	−	−	NOUN
iajs-2946	50	14	∑	∑	INTJ
iajs-2946	50	15	(	(	PUNCT
iajs-2946	50	16	𝒙𝒊−𝜹)𝒏	𝒙𝒊−𝜹)𝒏	NUM
iajs-2946	50	17	𝒊=𝟏	𝒊=𝟏	PROPN
iajs-2946	50	18	𝛾	𝛾	NOUN
iajs-2946	50	19	𝑐𝑒−𝑐𝛾	𝑐𝑒−𝑐𝛾	ADV
iajs-2946	50	20	𝑏𝑎	𝑏𝑎	X
iajs-2946	50	21	δ𝑎−1𝑒−𝑏δ	δ𝑎−1𝑒−𝑏δ	PROPN
iajs-2946	50	22	∫	∫	PROPN
iajs-2946	50	23	∫	∫	PROPN
iajs-2946	51	1	𝛾−𝒏	𝛾−𝒏	PROPN
iajs-2946	51	2	𝒆	𝒆	X
iajs-2946	51	3	−	−	PROPN
iajs-2946	51	4	∑	∑	INTJ
iajs-2946	51	5	(	(	PUNCT
iajs-2946	51	6	𝒙𝒊−𝜹)𝒏	𝒙𝒊−𝜹)𝒏	NUM
iajs-2946	51	7	𝒊=𝟏	𝒊=𝟏	PROPN
iajs-2946	51	8	𝛾	𝛾	NOUN
iajs-2946	51	9	𝑐𝑒−𝑐𝛾	𝑐𝑒−𝑐𝛾	ADV
iajs-2946	51	10	𝑏𝑎	𝑏𝑎	X
iajs-2946	51	11	δ𝑎−1𝑒−𝑏δ	δ𝑎−1𝑒−𝑏δ	NOUN
iajs-2946	51	12	dγdδ	dγdδ	NOUN
iajs-2946	51	13	∞	∞	PROPN
iajs-2946	51	14	𝟎	𝟎	PROPN
iajs-2946	51	15	∞	∞	PROPN
iajs-2946	51	16	𝟎	𝟎	NUM
iajs-2946	51	17	.	.	PUNCT
iajs-2946	52	1	3.2	3.2	NUM
iajs-2946	52	2	tierney	tierney	NOUN
iajs-2946	52	3	-	-	PUNCT
iajs-2946	52	4	kadane	kadane	PROPN
iajs-2946	52	5	approximation	approximation	NOUN
iajs-2946	52	6	assume	assume	VERB
iajs-2946	52	7	that	that	SCONJ
iajs-2946	52	8	u(γ	u(γ	PROPN
iajs-2946	52	9	,	,	PUNCT
iajs-2946	52	10	δ	δ	PROPN
iajs-2946	52	11	)	)	PUNCT
iajs-2946	52	12	be	be	VERB
iajs-2946	52	13	any	any	DET
iajs-2946	52	14	function	function	NOUN
iajs-2946	52	15	for	for	ADP
iajs-2946	52	16	γ	γ	PROPN
iajs-2946	52	17	and	and	CCONJ
iajs-2946	52	18	δ	δ	PROPN
iajs-2946	52	19	.	.	PUNCT
iajs-2946	53	1	therefore	therefore	ADV
iajs-2946	53	2	,	,	PUNCT
iajs-2946	53	3	e[u(γ	e[u(γ	PROPN
iajs-2946	53	4	,	,	PUNCT
iajs-2946	53	5	δ	δ	PROPN
iajs-2946	53	6	)	)	PUNCT
iajs-2946	53	7	]	]	PUNCT
iajs-2946	54	1	=	=	PUNCT
iajs-2946	54	2	∫	∫	PROPN
iajs-2946	54	3	∫	∫	PROPN
iajs-2946	54	4	u(γ	u(γ	PROPN
iajs-2946	54	5	,	,	PUNCT
iajs-2946	54	6	δ	δ	PROPN
iajs-2946	54	7	)	)	PUNCT
iajs-2946	54	8	∞	∞	NOUN
iajs-2946	54	9	0	0	NUM
iajs-2946	55	1	∞	∞	NUM
iajs-2946	55	2	0	0	NUM
iajs-2946	56	1	h(γ	h(γ	PROPN
iajs-2946	56	2	,	,	PUNCT
iajs-2946	56	3	δ|x1	δ|x1	PROPN
iajs-2946	56	4	,	,	PUNCT
iajs-2946	56	5	…	…	PUNCT
iajs-2946	56	6	xn)dγ	xn)dγ	X
iajs-2946	56	7	dδ	dδ	ADP
iajs-2946	56	8	=	=	PUNCT
iajs-2946	56	9	∫	∫	PROPN
iajs-2946	56	10	∫	∫	PROPN
iajs-2946	56	11	u(γ	u(γ	PROPN
iajs-2946	56	12	,	,	PUNCT
iajs-2946	56	13	δ	δ	PROPN
iajs-2946	56	14	)	)	PUNCT
iajs-2946	56	15	∞	∞	NOUN
iajs-2946	56	16	0	0	NUM
iajs-2946	57	1	∞	∞	NUM
iajs-2946	57	2	0	0	NUM
iajs-2946	57	3	l(x1,x2,	l(x1,x2,	NUM
iajs-2946	57	4	…	…	SYM
iajs-2946	57	5	,xn;γ	,xn;γ	PUNCT
iajs-2946	57	6	,	,	PUNCT
iajs-2946	57	7	δ	δ	PROPN
iajs-2946	57	8	)	)	PUNCT
iajs-2946	57	9	j(γ	j(γ	PROPN
iajs-2946	57	10	,	,	PUNCT
iajs-2946	57	11	δ	δ	NOUN
iajs-2946	57	12	)	)	PUNCT
iajs-2946	57	13	dγ	dγ	ADP
iajs-2946	57	14	dδ	dδ	ADP
iajs-2946	57	15	∫	∫	PROPN
iajs-2946	57	16	∫	∫	PROPN
iajs-2946	57	17	l(x1,x2,	l(x1,x2,	PROPN
iajs-2946	57	18	…	…	PUNCT
iajs-2946	57	19	,xn;γ	,xn;γ	PUNCT
iajs-2946	57	20	,	,	PUNCT
iajs-2946	57	21	δ	δ	PROPN
iajs-2946	57	22	)	)	PUNCT
iajs-2946	57	23	j(γ	j(γ	PROPN
iajs-2946	57	24	,	,	PUNCT
iajs-2946	57	25	δ	δ	NOUN
iajs-2946	57	26	)	)	PUNCT
iajs-2946	57	27	dγ	dγ	ADP
iajs-2946	57	28	dδ	dδ	ADP
iajs-2946	57	29	∞	∞	PROPN
iajs-2946	57	30	0	0	NUM
iajs-2946	57	31	∞	∞	NUM
iajs-2946	57	32	0	0	NUM
iajs-2946	57	33	.	.	PUNCT
iajs-2946	58	1	notice	notice	VERB
iajs-2946	58	2	that	that	SCONJ
iajs-2946	58	3	,	,	PUNCT
iajs-2946	58	4	there	there	PRON
iajs-2946	58	5	is	be	VERB
iajs-2946	58	6	a	a	DET
iajs-2946	58	7	difficulty	difficulty	NOUN
iajs-2946	58	8	in	in	ADP
iajs-2946	58	9	obtaining	obtain	VERB
iajs-2946	58	10	the	the	DET
iajs-2946	58	11	solution	solution	NOUN
iajs-2946	58	12	of	of	ADP
iajs-2946	58	13	the	the	DET
iajs-2946	58	14	ratio	ratio	NOUN
iajs-2946	58	15	of	of	ADP
iajs-2946	58	16	two	two	NUM
iajs-2946	58	17	integrals	integral	NOUN
iajs-2946	58	18	.	.	PUNCT
iajs-2946	59	1	therefore	therefore	ADV
iajs-2946	59	2	,	,	PUNCT
iajs-2946	59	3	many	many	ADJ
iajs-2946	59	4	approximation	approximation	NOUN
iajs-2946	59	5	methods	method	NOUN
iajs-2946	59	6	exist	exist	VERB
iajs-2946	59	7	for	for	ADP
iajs-2946	59	8	this	this	DET
iajs-2946	59	9	purpose	purpose	NOUN
iajs-2946	59	10	.	.	PUNCT
iajs-2946	60	1	one	one	NUM
iajs-2946	60	2	of	of	ADP
iajs-2946	60	3	them	they	PRON
iajs-2946	60	4	is	be	AUX
iajs-2946	60	5	the	the	DET
iajs-2946	60	6	tierney	tierney	NOUN
iajs-2946	60	7	-	-	PUNCT
iajs-2946	60	8	kadane	kadane	PROPN
iajs-2946	60	9	approximation	approximation	NOUN
iajs-2946	60	10	which	which	PRON
iajs-2946	60	11	can	can	AUX
iajs-2946	60	12	be	be	AUX
iajs-2946	60	13	applied	apply	VERB
iajs-2946	60	14	as	as	SCONJ
iajs-2946	60	15	follows	follow	VERB
iajs-2946	60	16	:	:	PUNCT
iajs-2946	60	17	consider	consider	VERB
iajs-2946	60	18	the	the	DET
iajs-2946	60	19	functions	function	NOUN
iajs-2946	60	20	δ(γ	δ(γ	NOUN
iajs-2946	60	21	,	,	PUNCT
iajs-2946	60	22	δ	δ	PROPN
iajs-2946	60	23	)	)	PUNCT
iajs-2946	60	24	and	and	CCONJ
iajs-2946	60	25	𝛿𝛾	𝛿𝛾	PROPN
iajs-2946	60	26	∗(𝛾	∗(𝛾	PROPN
iajs-2946	60	27	,	,	PUNCT
iajs-2946	60	28	𝛿	𝛿	ADJ
iajs-2946	60	29	)	)	PUNCT
iajs-2946	60	30	are	be	AUX
iajs-2946	60	31	defined	define	VERB
iajs-2946	60	32	as	as	ADP
iajs-2946	60	33	follows	follow	NOUN
iajs-2946	60	34	,	,	PUNCT
iajs-2946	60	35	respectively	respectively	ADV
iajs-2946	60	36	:	:	PUNCT
iajs-2946	60	37	𝛿(𝛾	𝛿(𝛾	ADJ
iajs-2946	60	38	,	,	PUNCT
iajs-2946	60	39	𝛿	𝛿	ADJ
iajs-2946	60	40	)	)	PUNCT
iajs-2946	60	41	=	=	SYM
iajs-2946	60	42	𝑙𝑛𝐿(𝛾,𝛿)+𝑙𝑛𝐽(𝛾,𝛿	𝑙𝑛𝐿(𝛾,𝛿)+𝑙𝑛𝐽(𝛾,𝛿	X
iajs-2946	60	43	)	)	PUNCT
iajs-2946	60	44	𝑛	𝑛	NOUN
iajs-2946	60	45	.	.	PUNCT
iajs-2946	61	1	(	(	PUNCT
iajs-2946	61	2	7	7	X
iajs-2946	61	3	)	)	PUNCT
iajs-2946	61	4	𝛿𝛾	𝛿𝛾	NOUN
iajs-2946	61	5	∗(𝛾	∗(𝛾	PROPN
iajs-2946	61	6	,	,	PUNCT
iajs-2946	61	7	𝛿	𝛿	ADJ
iajs-2946	61	8	)	)	PUNCT
iajs-2946	61	9	=	=	SYM
iajs-2946	61	10	δ(γ	δ(γ	NOUN
iajs-2946	61	11	,	,	PUNCT
iajs-2946	61	12	δ	δ	NOUN
iajs-2946	61	13	)	)	PUNCT
iajs-2946	62	1	+	+	CCONJ
iajs-2946	62	2	ln	ln	ADJ
iajs-2946	62	3	𝑢(𝛾,𝛿	𝑢(𝛾,𝛿	NOUN
iajs-2946	62	4	)	)	PUNCT
iajs-2946	62	5	𝑛	𝑛	NOUN
iajs-2946	62	6	.	.	PUNCT
iajs-2946	63	1	(	(	PUNCT
iajs-2946	63	2	8)	8)	NUM
iajs-2946	63	3	furthermore	furthermore	ADV
iajs-2946	63	4	,	,	PUNCT
iajs-2946	63	5	assume	assume	VERB
iajs-2946	63	6	that	that	SCONJ
iajs-2946	63	7	δ(𝛾𝛿,𝛿𝛿	δ(𝛾𝛿,𝛿𝛿	NUM
iajs-2946	63	8	)	)	PUNCT
iajs-2946	63	9	and	and	CCONJ
iajs-2946	63	10	𝛿𝛾	𝛿𝛾	PROPN
iajs-2946	63	11	∗(𝛾𝛿∗	∗(𝛾𝛿∗	PROPN
iajs-2946	63	12	,	,	PUNCT
iajs-2946	63	13	𝛿𝛿∗	𝛿𝛿∗	NOUN
iajs-2946	63	14	)	)	PUNCT
iajs-2946	63	15	maximize	maximize	VERB
iajs-2946	63	16	the	the	DET
iajs-2946	63	17	functions	function	NOUN
iajs-2946	63	18	δ(γ	δ(γ	NOUN
iajs-2946	63	19	,	,	PUNCT
iajs-2946	63	20	δ	δ	PROPN
iajs-2946	63	21	)	)	PUNCT
iajs-2946	63	22	and	and	CCONJ
iajs-2946	63	23	𝛿𝛾	𝛿𝛾	PROPN
iajs-2946	63	24	∗(𝛾	∗(𝛾	PROPN
iajs-2946	63	25	,	,	PUNCT
iajs-2946	63	26	𝛿	𝛿	ADJ
iajs-2946	63	27	)	)	PUNCT
iajs-2946	63	28	,	,	PUNCT
iajs-2946	63	29	respectively	respectively	ADV
iajs-2946	63	30	,	,	PUNCT
iajs-2946	63	31	where	where	SCONJ
iajs-2946	63	32	𝛾𝛿∗	𝛾𝛿∗	PROPN
iajs-2946	63	33	is	be	AUX
iajs-2946	63	34	the	the	DET
iajs-2946	63	35	initial	initial	ADJ
iajs-2946	63	36	value	value	NOUN
iajs-2946	63	37	for	for	ADP
iajs-2946	63	38	γ	γ	NOUN
iajs-2946	63	39	and	and	CCONJ
iajs-2946	63	40	𝛿𝛿∗	𝛿𝛿∗	ADJ
iajs-2946	63	41	is	be	AUX
iajs-2946	63	42	the	the	DET
iajs-2946	63	43	initial	initial	ADJ
iajs-2946	63	44	value	value	NOUN
iajs-2946	63	45	for	for	ADP
iajs-2946	63	46	δ	δ	PROPN
iajs-2946	63	47	.	.	PUNCT
iajs-2946	64	1	ihjpas	ihjpas	PROPN
iajs-2946	64	2	.	.	PUNCT
iajs-2946	65	1	36(2)2023	36(2)2023	NUM
iajs-2946	65	2	292	292	NUM
iajs-2946	65	3	assume	assume	VERB
iajs-2946	65	4	that	that	SCONJ
iajs-2946	65	5	│	│	VERB
iajs-2946	65	6	∑	∑	PUNCT
iajs-2946	65	7	│	│	ADJ
iajs-2946	65	8	𝑎𝑛𝑑	𝑎𝑛𝑑	ADJ
iajs-2946	65	9	|∑γ	|∑γ	PROPN
iajs-2946	65	10	∗	∗	NOUN
iajs-2946	65	11	|	|	ADV
iajs-2946	65	12	denote	denote	VERB
iajs-2946	65	13	the	the	DET
iajs-2946	65	14	determinants	determinant	NOUN
iajs-2946	65	15	of	of	ADP
iajs-2946	65	16	negative	negative	ADJ
iajs-2946	65	17	inverse	inverse	NOUN
iajs-2946	65	18	hessian	hessian	NOUN
iajs-2946	65	19	of	of	ADP
iajs-2946	65	20	δ(γ	δ(γ	PROPN
iajs-2946	65	21	,	,	PUNCT
iajs-2946	65	22	δ	δ	PROPN
iajs-2946	65	23	)	)	PUNCT
iajs-2946	65	24	and	and	CCONJ
iajs-2946	65	25	𝛿𝛾	𝛿𝛾	PROPN
iajs-2946	65	26	∗(𝛾	∗(𝛾	PROPN
iajs-2946	65	27	,	,	PUNCT
iajs-2946	65	28	𝛿	𝛿	ADJ
iajs-2946	65	29	)	)	PUNCT
iajs-2946	65	30	,	,	PUNCT
iajs-2946	65	31	where	where	SCONJ
iajs-2946	65	32	│	│	VERB
iajs-2946	65	33	∑	∑	ADJ
iajs-2946	65	34	│	│	NOUN
iajs-2946	65	35	=	=	PUNCT
iajs-2946	65	36	[	[	PUNCT
iajs-2946	65	37	∂2δ	∂2δ	PROPN
iajs-2946	65	38	∂γ2	∂γ2	PROPN
iajs-2946	65	39	∂2δ	∂2δ	VERB
iajs-2946	65	40	∂δ2	∂δ2	NOUN
iajs-2946	65	41	−	−	PROPN
iajs-2946	65	42	∂2δ	∂2δ	PROPN
iajs-2946	65	43	∂γ	∂γ	PROPN
iajs-2946	65	44	∂δ	∂δ	PROPN
iajs-2946	66	1	∂2δ	∂2δ	NOUN
iajs-2946	66	2	∂δ	∂δ	PROPN
iajs-2946	66	3	∂γ	∂γ	PROPN
iajs-2946	66	4	]	]	PUNCT
iajs-2946	66	5	−1	−1	NOUN
iajs-2946	66	6	.	.	PUNCT
iajs-2946	67	1	and	and	CCONJ
iajs-2946	67	2	|∑γ	|∑γ	PROPN
iajs-2946	67	3	∗	∗	VERB
iajs-2946	67	4	|	|	ADV
iajs-2946	67	5	=	=	PRON
iajs-2946	67	6	[	[	PUNCT
iajs-2946	67	7	∂2𝛿𝛾	∂2𝛿𝛾	NOUN
iajs-2946	67	8	∗	∗	X
iajs-2946	67	9	∂γ2	∂γ2	PROPN
iajs-2946	67	10	∂2𝛿𝛾	∂2𝛿𝛾	PART
iajs-2946	67	11	∗	∗	NOUN
iajs-2946	67	12	∂δ2	∂δ2	NOUN
iajs-2946	68	1	−	−	NOUN
iajs-2946	68	2	∂2𝛿𝛾	∂2𝛿𝛾	ADJ
iajs-2946	68	3	∗	∗	NOUN
iajs-2946	68	4	∂γ	∂γ	PROPN
iajs-2946	68	5	∂δ	∂δ	PROPN
iajs-2946	68	6	∂2𝛿𝛾	∂2𝛿𝛾	NOUN
iajs-2946	68	7	∗	∗	X
iajs-2946	68	8	∂δ	∂δ	PROPN
iajs-2946	68	9	∂γ	∂γ	PROPN
iajs-2946	68	10	]	]	PUNCT
iajs-2946	68	11	−1	−1	NOUN
iajs-2946	68	12	.	.	PUNCT
iajs-2946	69	1	therefore	therefore	ADV
iajs-2946	69	2	,	,	PUNCT
iajs-2946	69	3	e[u(γ	e[u(γ	PROPN
iajs-2946	69	4	,	,	PUNCT
iajs-2946	69	5	δ	δ	PROPN
iajs-2946	69	6	)	)	PUNCT
iajs-2946	69	7	]	]	PUNCT
iajs-2946	69	8	can	can	AUX
iajs-2946	69	9	be	be	AUX
iajs-2946	69	10	approximated	approximate	VERB
iajs-2946	69	11	as	as	ADP
iajs-2946	69	12	the	the	DET
iajs-2946	69	13	following	following	NOUN
iajs-2946	69	14	:	:	PUNCT
iajs-2946	69	15	e[u(γ	e[u(γ	NOUN
iajs-2946	69	16	,	,	PUNCT
iajs-2946	69	17	δ	δ	PROPN
iajs-2946	69	18	)	)	PUNCT
iajs-2946	69	19	]	]	PUNCT
iajs-2946	70	1	=	=	PUNCT
iajs-2946	70	2	√	√	PROPN
iajs-2946	70	3	|∑γ	|∑γ	PROPN
iajs-2946	70	4	∗	∗	NOUN
iajs-2946	70	5	|	|	ADV
iajs-2946	70	6	│	│	VERB
iajs-2946	70	7	∑	∑	PROPN
iajs-2946	70	8	│	│	X
iajs-2946	70	9	𝑒[𝑛{𝛿𝛾	𝑒[𝑛{𝛿𝛾	VERB
iajs-2946	70	10	∗	∗	NOUN
iajs-2946	70	11	(	(	PUNCT
iajs-2946	70	12	�	�	NOUN
iajs-2946	70	13	̂	̂	NOUN
iajs-2946	70	14	�	�	NOUN
iajs-2946	70	15	𝛿∗	𝛿∗	PROPN
iajs-2946	70	16	,	,	PUNCT
iajs-2946	70	17	�	�	PROPN
iajs-2946	70	18	̂	̂	NOUN
iajs-2946	70	19	�	�	NOUN
iajs-2946	70	20	𝛿∗)−	𝛿∗)−	PROPN
iajs-2946	70	21	𝛿(	𝛿(	NOUN
iajs-2946	70	22	�	�	NOUN
iajs-2946	70	23	̂	̂	SYM
iajs-2946	70	24	�	�	NOUN
iajs-2946	70	25	𝛿,	𝛿,	NOUN
iajs-2946	70	26	�	�	PROPN
iajs-2946	70	27	̂	̂	NOUN
iajs-2946	70	28	�	�	NOUN
iajs-2946	70	29	𝛿	𝛿	NOUN
iajs-2946	70	30	)	)	PUNCT
iajs-2946	70	31	}	}	PUNCT
iajs-2946	70	32	]	]	X
iajs-2946	70	33	.	.	PUNCT
iajs-2946	70	34	3.3	3.3	NUM
iajs-2946	70	35	bayes	bayes	PROPN
iajs-2946	70	36	estimator	estimator	NOUN
iajs-2946	70	37	under	under	ADP
iajs-2946	70	38	squared	square	VERB
iajs-2946	70	39	error	error	NOUN
iajs-2946	70	40	loss	loss	NOUN
iajs-2946	70	41	function	function	NOUN
iajs-2946	70	42	the	the	DET
iajs-2946	70	43	squared	square	VERB
iajs-2946	70	44	error	error	NOUN
iajs-2946	70	45	loss	loss	NOUN
iajs-2946	70	46	function	function	NOUN
iajs-2946	70	47	is	be	AUX
iajs-2946	70	48	one	one	NUM
iajs-2946	70	49	of	of	ADP
iajs-2946	70	50	the	the	DET
iajs-2946	70	51	symmetric	symmetric	ADJ
iajs-2946	70	52	functions	function	NOUN
iajs-2946	70	53	of	of	ADP
iajs-2946	70	54	γ	γ	PROPN
iajs-2946	70	55	̂	̂	VERB
iajs-2946	70	56	given	give	VERB
iajs-2946	70	57	by	by	ADP
iajs-2946	70	58	mood	mood	NOUN
iajs-2946	70	59	,	,	PUNCT
iajs-2946	70	60	graybill	graybill	NOUN
iajs-2946	70	61	,	,	PUNCT
iajs-2946	70	62	and	and	CCONJ
iajs-2946	70	63	boes	boes	PROPN
iajs-2946	70	64	(	(	PUNCT
iajs-2946	70	65	1974	1974	NUM
iajs-2946	70	66	)	)	PUNCT
iajs-2946	70	67	.	.	PUNCT
iajs-2946	71	1	it	it	PRON
iajs-2946	71	2	is	be	AUX
iajs-2946	71	3	widely	widely	ADV
iajs-2946	71	4	used	use	VERB
iajs-2946	71	5	for	for	ADP
iajs-2946	71	6	most	most	ADJ
iajs-2946	71	7	estimation	estimation	NOUN
iajs-2946	71	8	problems	problem	NOUN
iajs-2946	71	9	.	.	PUNCT
iajs-2946	72	1	it	it	PRON
iajs-2946	72	2	can	can	AUX
iajs-2946	72	3	be	be	AUX
iajs-2946	72	4	defined	define	VERB
iajs-2946	72	5	as	as	ADP
iajs-2946	72	6	[	[	X
iajs-2946	72	7	5	5	NUM
iajs-2946	72	8	]	]	X
iajs-2946	72	9	:	:	PUNCT
iajs-2946	72	10	l(γ̂	l(γ̂	ADJ
iajs-2946	72	11	,	,	PUNCT
iajs-2946	72	12	γ	γ	NOUN
iajs-2946	72	13	)	)	PUNCT
iajs-2946	72	14	=	=	PUNCT
iajs-2946	73	1	(	(	PUNCT
iajs-2946	73	2	γ̂	γ̂	NUM
iajs-2946	73	3	−	−	PROPN
iajs-2946	73	4	γ)2	γ)2	NOUN
iajs-2946	73	5	.	.	PUNCT
iajs-2946	74	1	the	the	DET
iajs-2946	74	2	risk	risk	NOUN
iajs-2946	74	3	function	function	NOUN
iajs-2946	74	4	rs(γ̂	rs(γ̂	NOUN
iajs-2946	74	5	,	,	PUNCT
iajs-2946	74	6	γ	γ	NOUN
iajs-2946	74	7	)	)	PUNCT
iajs-2946	74	8	is	be	AUX
iajs-2946	74	9	the	the	DET
iajs-2946	74	10	posterior	posterior	ADJ
iajs-2946	74	11	expectation	expectation	NOUN
iajs-2946	74	12	of	of	ADP
iajs-2946	74	13	the	the	DET
iajs-2946	74	14	loss	loss	NOUN
iajs-2946	74	15	function	function	NOUN
iajs-2946	74	16	l(γ̂	l(γ̂	PROPN
iajs-2946	74	17	,	,	PUNCT
iajs-2946	74	18	γ	γ	NOUN
iajs-2946	74	19	)	)	PUNCT
iajs-2946	74	20	with	with	ADP
iajs-2946	74	21	respect	respect	NOUN
iajs-2946	74	22	to	to	ADP
iajs-2946	74	23	h(γ|x	h(γ|x	NOUN
iajs-2946	74	24	)	)	PUNCT
iajs-2946	74	25	.	.	PUNCT
iajs-2946	75	1	that	that	PRON
iajs-2946	75	2	is	be	AUX
iajs-2946	75	3	:	:	PUNCT
iajs-2946	75	4	rs(γ̂	rs(γ̂	NOUN
iajs-2946	75	5	,	,	PUNCT
iajs-2946	75	6	γ	γ	NOUN
iajs-2946	75	7	)	)	PUNCT
iajs-2946	75	8	=	=	SYM
iajs-2946	75	9	e[l(γ̂	e[l(γ̂	NOUN
iajs-2946	75	10	,	,	PUNCT
iajs-2946	75	11	γ	γ	NOUN
iajs-2946	75	12	)	)	PUNCT
iajs-2946	75	13	]	]	PUNCT
iajs-2946	75	14	,	,	PUNCT
iajs-2946	75	15	rs(γ̂	rs(γ̂	NOUN
iajs-2946	75	16	,	,	PUNCT
iajs-2946	75	17	γ	γ	NOUN
iajs-2946	75	18	)	)	PUNCT
iajs-2946	75	19	=	=	SYM
iajs-2946	76	1	∫	∫	PROPN
iajs-2946	76	2	l(γ̂	l(γ̂	PROPN
iajs-2946	76	3	,	,	PUNCT
iajs-2946	76	4	γ)h(γ|x)dγ	γ)h(γ|x)dγ	VERB
iajs-2946	76	5	∞	∞	PROPN
iajs-2946	76	6	0	0	NUM
iajs-2946	76	7	,	,	PUNCT
iajs-2946	76	8	rs(γ̂	rs(γ̂	NOUN
iajs-2946	76	9	,	,	PUNCT
iajs-2946	76	10	γ	γ	NOUN
iajs-2946	76	11	)	)	PUNCT
iajs-2946	76	12	=	=	SYM
iajs-2946	76	13	∫	∫	PROPN
iajs-2946	76	14	(	(	PUNCT
iajs-2946	76	15	γ̂	γ̂	NUM
iajs-2946	76	16	−	−	PROPN
iajs-2946	76	17	γ)2∞	γ)2∞	PROPN
iajs-2946	76	18	0	0	NUM
iajs-2946	76	19	h(γ|x)dγ	h(γ|x)dγ	NOUN
iajs-2946	76	20	,	,	PUNCT
iajs-2946	76	21	rs(γ̂	rs(γ̂	NOUN
iajs-2946	76	22	,	,	PUNCT
iajs-2946	76	23	γ	γ	NOUN
iajs-2946	76	24	)	)	PUNCT
iajs-2946	76	25	=	=	SYM
iajs-2946	76	26	γ̂2	γ̂2	PROPN
iajs-2946	76	27	−	−	PROPN
iajs-2946	76	28	2γ̂e(γ|x	2γ̂e(γ|x	NUM
iajs-2946	76	29	)	)	PUNCT
iajs-2946	76	30	+	+	CCONJ
iajs-2946	76	31	e(γ2|x	e(γ2|x	NOUN
iajs-2946	76	32	)	)	PUNCT
iajs-2946	76	33	.	.	PUNCT
iajs-2946	77	1	(	(	PUNCT
iajs-2946	77	2	9	9	NUM
iajs-2946	77	3	)	)	PUNCT
iajs-2946	77	4	thus	thus	ADV
iajs-2946	77	5	,	,	PUNCT
iajs-2946	77	6	the	the	DET
iajs-2946	77	7	value	value	NOUN
iajs-2946	77	8	of	of	ADP
iajs-2946	77	9	γ̂	γ̂	PUNCT
iajs-2946	77	10	that	that	PRON
iajs-2946	77	11	minimizes	minimize	VERB
iajs-2946	77	12	the	the	DET
iajs-2946	77	13	posterior	posterior	ADJ
iajs-2946	77	14	risk	risk	NOUN
iajs-2946	77	15	(	(	PUNCT
iajs-2946	77	16	9	9	NUM
iajs-2946	77	17	)	)	PUNCT
iajs-2946	77	18	is	be	AUX
iajs-2946	77	19	obtained	obtain	VERB
iajs-2946	77	20	by	by	ADP
iajs-2946	77	21	setting	set	VERB
iajs-2946	77	22	its	its	PRON
iajs-2946	77	23	first	first	ADJ
iajs-2946	77	24	partial	partial	ADJ
iajs-2946	77	25	derivative	derivative	NOUN
iajs-2946	77	26	with	with	ADP
iajs-2946	77	27	respect	respect	NOUN
iajs-2946	77	28	to	to	ADP
iajs-2946	77	29	γ̂	γ̂	X
iajs-2946	77	30	equal	equal	ADJ
iajs-2946	77	31	to	to	ADP
iajs-2946	77	32	zero	zero	NUM
iajs-2946	77	33	.	.	PUNCT
iajs-2946	78	1	that	that	PRON
iajs-2946	78	2	is	be	AUX
iajs-2946	78	3	,	,	PUNCT
iajs-2946	78	4	γ̂s	γ̂s	PRON
iajs-2946	78	5	is	be	AUX
iajs-2946	78	6	the	the	DET
iajs-2946	78	7	posterior	posterior	ADJ
iajs-2946	78	8	mean	mean	NOUN
iajs-2946	78	9	.	.	PUNCT
iajs-2946	79	1	taking	take	VERB
iajs-2946	79	2	the	the	DET
iajs-2946	79	3	partial	partial	ADJ
iajs-2946	79	4	derivative	derivative	NOUN
iajs-2946	79	5	for	for	ADP
iajs-2946	79	6	rs(γ̂	rs(γ̂	NOUN
iajs-2946	79	7	,	,	PUNCT
iajs-2946	79	8	γ	γ	NOUN
iajs-2946	79	9	)	)	PUNCT
iajs-2946	79	10	with	with	ADP
iajs-2946	79	11	respect	respect	NOUN
iajs-2946	79	12	to	to	ADP
iajs-2946	79	13	γ̂	γ̂	PUNCT
iajs-2946	79	14	and	and	CCONJ
iajs-2946	79	15	setting	set	VERB
iajs-2946	79	16	it	it	PRON
iajs-2946	79	17	equal	equal	ADJ
iajs-2946	79	18	to	to	ADP
iajs-2946	79	19	zero	zero	NUM
iajs-2946	79	20	yields	yield	NOUN
iajs-2946	79	21	,	,	PUNCT
iajs-2946	79	22	2γ̂	2γ̂	NUM
iajs-2946	79	23	−	−	NOUN
iajs-2946	79	24	2e(γ|x	2e(γ|x	NUM
iajs-2946	79	25	)	)	PUNCT
iajs-2946	79	26	=	=	SYM
iajs-2946	79	27	0	0	NUM
iajs-2946	79	28	,	,	PUNCT
iajs-2946	79	29	γ̂s	γ̂s	X
iajs-2946	79	30	=	=	SYM
iajs-2946	79	31	e(γ|x	e(γ|x	PROPN
iajs-2946	79	32	)	)	PUNCT
iajs-2946	79	33	.	.	PUNCT
iajs-2946	80	1	where	where	SCONJ
iajs-2946	80	2	γ̂s	γ̂s	PRON
iajs-2946	80	3	is	be	AUX
iajs-2946	80	4	denoted	denote	VERB
iajs-2946	80	5	by	by	ADP
iajs-2946	80	6	the	the	DET
iajs-2946	80	7	bayesian	bayesian	NOUN
iajs-2946	80	8	estimation	estimation	NOUN
iajs-2946	80	9	for	for	ADP
iajs-2946	80	10	γ	γ	NOUN
iajs-2946	80	11	under	under	ADP
iajs-2946	80	12	the	the	DET
iajs-2946	80	13	squared	square	VERB
iajs-2946	80	14	error	error	NOUN
iajs-2946	80	15	loss	loss	NOUN
iajs-2946	80	16	function	function	NOUN
iajs-2946	80	17	.	.	PUNCT
iajs-2946	81	1	i	i	PRON
iajs-2946	81	2	)	)	PUNCT
iajs-2946	81	3	bayesian	bayesian	NOUN
iajs-2946	81	4	estimation	estimation	NOUN
iajs-2946	81	5	for	for	ADP
iajs-2946	81	6	γ	γ	NOUN
iajs-2946	81	7	under	under	ADP
iajs-2946	81	8	squared	square	VERB
iajs-2946	81	9	error	error	NOUN
iajs-2946	81	10	loss	loss	NOUN
iajs-2946	81	11	function	function	NOUN
iajs-2946	81	12	to	to	PART
iajs-2946	81	13	obtain	obtain	VERB
iajs-2946	81	14	bayesian	bayesian	NOUN
iajs-2946	81	15	estimation	estimation	NOUN
iajs-2946	81	16	for	for	ADP
iajs-2946	81	17	𝛾	𝛾	PROPN
iajs-2946	81	18	under	under	ADP
iajs-2946	81	19	self	self	NOUN
iajs-2946	81	20	,	,	PUNCT
iajs-2946	81	21	assume	assume	VERB
iajs-2946	81	22	that	that	SCONJ
iajs-2946	81	23	:	:	PUNCT
iajs-2946	81	24	u(γ	u(γ	PROPN
iajs-2946	81	25	,	,	PUNCT
iajs-2946	81	26	δ	δ	PROPN
iajs-2946	81	27	)	)	PUNCT
iajs-2946	81	28	=	=	PUNCT
iajs-2946	82	1	γ	γ	X
iajs-2946	82	2	.	.	PROPN
iajs-2946	82	3	hence	hence	ADV
iajs-2946	82	4	,	,	PUNCT
iajs-2946	82	5	𝐸[γ	𝐸[γ	NOUN
iajs-2946	82	6	│	│	ADJ
iajs-2946	82	7	𝑋	𝑋	NOUN
iajs-2946	82	8	]	]	PUNCT
iajs-2946	82	9	=	=	SYM
iajs-2946	83	1	∫	∫	PROPN
iajs-2946	83	2	∫	∫	PROPN
iajs-2946	83	3	γ	γ	X
iajs-2946	83	4	∞	∞	PROPN
iajs-2946	83	5	0	0	NUM
iajs-2946	84	1	∞	∞	NOUN
iajs-2946	84	2	0	0	NUM
iajs-2946	84	3	γ−n	γ−n	NOUN
iajs-2946	84	4	e	e	X
iajs-2946	84	5	−	−	PROPN
iajs-2946	84	6	∑	∑	PUNCT
iajs-2946	84	7	(	(	PUNCT
iajs-2946	84	8	xi−δ)n	xi−δ)n	NOUN
iajs-2946	84	9	i=1	i=1	PROPN
iajs-2946	84	10	γ	γ	PROPN
iajs-2946	84	11	𝑐𝑒−𝑐𝛾	𝑐𝑒−𝑐𝛾	ADV
iajs-2946	84	12	𝑏𝑎	𝑏𝑎	X
iajs-2946	84	13	δ𝑎−1𝑒−𝑏δ𝑑𝛾𝑑𝛿	δ𝑎−1𝑒−𝑏δ𝑑𝛾𝑑𝛿	NOUN
iajs-2946	84	14	∫	∫	PROPN
iajs-2946	84	15	∫	∫	PROPN
iajs-2946	84	16	γ−n	γ−n	PROPN
iajs-2946	84	17	e	e	X
iajs-2946	84	18	−	−	PROPN
iajs-2946	84	19	∑	∑	PUNCT
iajs-2946	84	20	(	(	PUNCT
iajs-2946	84	21	xi−δ)n	xi−δ)n	NOUN
iajs-2946	84	22	i=1	i=1	PROPN
iajs-2946	84	23	γ	γ	PROPN
iajs-2946	84	24	𝑐𝑒−𝑐𝛾	𝑐𝑒−𝑐𝛾	PUNCT
iajs-2946	84	25	𝑏𝑎	𝑏𝑎	X
iajs-2946	84	26	δ𝑎−1𝑒−𝑏δ	δ𝑎−1𝑒−𝑏δ	NOUN
iajs-2946	84	27	𝑑𝛾𝑑𝛿	𝑑𝛾𝑑𝛿	NOUN
iajs-2946	84	28	∞	∞	NOUN
iajs-2946	84	29	0	0	NUM
iajs-2946	85	1	∞	∞	NUM
iajs-2946	85	2	0	0	NUM
iajs-2946	85	3	.	.	PUNCT
iajs-2946	86	1	therefore	therefore	ADV
iajs-2946	86	2	,	,	PUNCT
iajs-2946	86	3	the	the	DET
iajs-2946	86	4	tierney	tierney	NOUN
iajs-2946	86	5	-	-	PUNCT
iajs-2946	86	6	kadane	kadane	PROPN
iajs-2946	86	7	approximation	approximation	NOUN
iajs-2946	86	8	will	will	AUX
iajs-2946	86	9	be	be	AUX
iajs-2946	86	10	used	use	VERB
iajs-2946	86	11	as	as	SCONJ
iajs-2946	86	12	follows	follow	VERB
iajs-2946	86	13	:	:	PUNCT
iajs-2946	86	14	𝑙𝑛𝐽(𝛾	𝑙𝑛𝐽(𝛾	PROPN
iajs-2946	86	15	,	,	PUNCT
iajs-2946	86	16	𝛿	𝛿	ADJ
iajs-2946	86	17	)	)	PUNCT
iajs-2946	86	18	=	=	SYM
iajs-2946	86	19	𝑙𝑛𝑐	𝑙𝑛𝑐	NOUN
iajs-2946	87	1	−	−	AUX
iajs-2946	87	2	𝑐	𝑐	NOUN
iajs-2946	87	3	𝛾	𝛾	PROPN
iajs-2946	87	4	+	+	NUM
iajs-2946	87	5	𝑎𝑙𝑛𝑏	𝑎𝑙𝑛𝑏	VERB
iajs-2946	87	6	+	+	CCONJ
iajs-2946	87	7	(	(	PUNCT
iajs-2946	87	8	𝑎	𝑎	DET
iajs-2946	87	9	−	−	PROPN
iajs-2946	87	10	1	1	NUM
iajs-2946	87	11	)	)	PUNCT
iajs-2946	87	12	𝑙𝑛𝛿	𝑙𝑛𝛿	NOUN
iajs-2946	87	13	−	−	PROPN
iajs-2946	87	14	𝑏𝛿	𝑏𝛿	INTJ
iajs-2946	87	15	−	−	NOUN
iajs-2946	87	16	𝑙𝑛𝛤(𝑎	𝑙𝑛𝛤(𝑎	PROPN
iajs-2946	87	17	)	)	PUNCT
iajs-2946	87	18	.	.	PUNCT
iajs-2946	88	1	(	(	PUNCT
iajs-2946	88	2	10	10	NUM
iajs-2946	88	3	)	)	PUNCT
iajs-2946	88	4	substituting	substitute	VERB
iajs-2946	88	5	(	(	PUNCT
iajs-2946	88	6	6	6	NUM
iajs-2946	88	7	)	)	PUNCT
iajs-2946	88	8	and	and	CCONJ
iajs-2946	88	9	(	(	PUNCT
iajs-2946	88	10	10	10	NUM
iajs-2946	88	11	)	)	PUNCT
iajs-2946	88	12	in	in	ADP
iajs-2946	88	13	(	(	PUNCT
iajs-2946	88	14	7	7	X
iajs-2946	88	15	)	)	PUNCT
iajs-2946	88	16	yields	yield	NOUN
iajs-2946	88	17	,	,	PUNCT
iajs-2946	88	18	𝛿	𝛿	X
iajs-2946	88	19	(	(	PUNCT
iajs-2946	88	20	𝛾	𝛾	PROPN
iajs-2946	88	21	,	,	PUNCT
iajs-2946	88	22	𝛿	𝛿	ADJ
iajs-2946	88	23	)	)	PUNCT
iajs-2946	88	24	=	=	SYM
iajs-2946	88	25	1	1	NUM
iajs-2946	88	26	𝑛	𝑛	NOUN
iajs-2946	89	1	[	[	X
iajs-2946	89	2	−𝑛	−𝑛	NOUN
iajs-2946	89	3	𝑙𝑛	𝑙𝑛	NOUN
iajs-2946	89	4	𝛾	𝛾	ADP
iajs-2946	89	5	−	−	PROPN
iajs-2946	89	6	∑	∑	PUNCT
iajs-2946	89	7	(	(	PUNCT
iajs-2946	89	8	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	89	9	𝑖=1	𝑖=1	PROPN
iajs-2946	89	10	𝛾	𝛾	ADP
iajs-2946	90	1	+	+	CCONJ
iajs-2946	90	2	𝑎	𝑎	ADJ
iajs-2946	90	3	𝑙𝑛	𝑙𝑛	NOUN
iajs-2946	90	4	𝑏	𝑏	NOUN
iajs-2946	90	5	+	+	CCONJ
iajs-2946	90	6	(	(	PUNCT
iajs-2946	90	7	𝑎	𝑎	DET
iajs-2946	90	8	−	−	PROPN
iajs-2946	90	9	1	1	NUM
iajs-2946	90	10	)	)	PUNCT
iajs-2946	90	11	𝑙𝑛	𝑙𝑛	NOUN
iajs-2946	90	12	𝛿	𝛿	ADJ
iajs-2946	90	13	−	−	PROPN
iajs-2946	90	14	𝑏𝛿	𝑏𝛿	NOUN
iajs-2946	90	15	+	+	NUM
iajs-2946	90	16	𝑙𝑛	𝑙𝑛	NOUN
iajs-2946	90	17	𝑐	𝑐	NOUN
iajs-2946	90	18	−	−	PROPN
iajs-2946	90	19	𝛾𝑐	𝛾𝑐	PROPN
iajs-2946	90	20	−	−	PROPN
iajs-2946	90	21	𝑙𝑛	𝑙𝑛	NOUN
iajs-2946	90	22	𝛤(𝑎	𝛤(𝑎	NOUN
iajs-2946	90	23	)	)	PUNCT
iajs-2946	90	24	]	]	PUNCT
iajs-2946	90	25	.	.	PUNCT
iajs-2946	91	1	now	now	ADV
iajs-2946	91	2	,	,	PUNCT
iajs-2946	91	3	according	accord	VERB
iajs-2946	91	4	to	to	ADP
iajs-2946	91	5	(	(	PUNCT
iajs-2946	91	6	8)	8)	NUM
iajs-2946	91	7	,	,	PUNCT
iajs-2946	91	8	𝛿𝛾	𝛿𝛾	PROPN
iajs-2946	91	9	∗(𝛾	∗(𝛾	PROPN
iajs-2946	91	10	,	,	PUNCT
iajs-2946	91	11	𝛿	𝛿	ADJ
iajs-2946	91	12	)	)	PUNCT
iajs-2946	91	13	can	can	AUX
iajs-2946	91	14	be	be	AUX
iajs-2946	91	15	obtained	obtain	VERB
iajs-2946	91	16	as	as	SCONJ
iajs-2946	91	17	follows	follow	VERB
iajs-2946	91	18	:	:	PUNCT
iajs-2946	91	19	𝛿𝛾	𝛿𝛾	PROPN
iajs-2946	91	20	∗(𝛾	∗(𝛾	PROPN
iajs-2946	91	21	,	,	PUNCT
iajs-2946	91	22	𝛿	𝛿	ADJ
iajs-2946	91	23	)	)	PUNCT
iajs-2946	91	24	=	=	SYM
iajs-2946	91	25	1	1	NUM
iajs-2946	91	26	𝑛	𝑛	NOUN
iajs-2946	92	1	[	[	X
iajs-2946	92	2	−𝑛	−𝑛	NOUN
iajs-2946	92	3	𝑙𝑛	𝑙𝑛	NOUN
iajs-2946	92	4	𝛾	𝛾	ADP
iajs-2946	92	5	−	−	PROPN
iajs-2946	92	6	∑	∑	PUNCT
iajs-2946	92	7	(	(	PUNCT
iajs-2946	92	8	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	92	9	𝑖=1	𝑖=1	PROPN
iajs-2946	92	10	𝛾	𝛾	ADP
iajs-2946	93	1	+	+	CCONJ
iajs-2946	93	2	𝑎	𝑎	ADJ
iajs-2946	93	3	𝑙𝑛	𝑙𝑛	NOUN
iajs-2946	93	4	𝑏	𝑏	NOUN
iajs-2946	93	5	+	+	CCONJ
iajs-2946	93	6	(	(	PUNCT
iajs-2946	93	7	𝑎	𝑎	DET
iajs-2946	93	8	−	−	PROPN
iajs-2946	93	9	1	1	NUM
iajs-2946	93	10	)	)	PUNCT
iajs-2946	93	11	𝑙𝑛	𝑙𝑛	NOUN
iajs-2946	93	12	𝛿	𝛿	ADJ
iajs-2946	93	13	−	−	PROPN
iajs-2946	93	14	𝑏𝛿	𝑏𝛿	NOUN
iajs-2946	93	15	+	+	NUM
iajs-2946	93	16	𝑙𝑛	𝑙𝑛	NOUN
iajs-2946	93	17	𝑐	𝑐	NOUN
iajs-2946	93	18	−	−	PROPN
iajs-2946	93	19	𝛾𝑐	𝛾𝑐	PROPN
iajs-2946	93	20	−	−	PROPN
iajs-2946	93	21	𝑙𝑛	𝑙𝑛	NOUN
iajs-2946	93	22	𝛤(𝑎	𝛤(𝑎	NOUN
iajs-2946	93	23	)	)	PUNCT
iajs-2946	93	24	]	]	PUNCT
iajs-2946	94	1	+	+	CCONJ
iajs-2946	94	2	ln	ln	ADJ
iajs-2946	94	3	𝛾	𝛾	NOUN
iajs-2946	94	4	𝑛	𝑛	PRON
iajs-2946	94	5	,	,	PUNCT
iajs-2946	94	6	𝜕𝛿	𝜕𝛿	NOUN
iajs-2946	94	7	𝜕𝛾	𝜕𝛾	NOUN
iajs-2946	94	8	=	=	SYM
iajs-2946	94	9	1	1	NUM
iajs-2946	94	10	𝑛	𝑛	PROPN
iajs-2946	94	11	[	[	PUNCT
iajs-2946	94	12	−𝑛	−𝑛	NOUN
iajs-2946	94	13	𝛾	𝛾	ADP
iajs-2946	94	14	+	+	ADV
iajs-2946	94	15	∑	∑	PUNCT
iajs-2946	94	16	(	(	PUNCT
iajs-2946	94	17	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	94	18	𝑖=1	𝑖=1	PROPN
iajs-2946	94	19	𝛾2	𝛾2	NOUN
iajs-2946	94	20	–	–	PUNCT
iajs-2946	94	21	𝑐	𝑐	NOUN
iajs-2946	94	22	]	]	PUNCT
iajs-2946	94	23	,	,	PUNCT
iajs-2946	94	24	ihjpas	ihjpas	PROPN
iajs-2946	94	25	.	.	PUNCT
iajs-2946	95	1	36(2)2023	36(2)2023	NUM
iajs-2946	95	2	293	293	NUM
iajs-2946	95	3	∂2δ	∂2δ	NOUN
iajs-2946	95	4	∂γ2	∂γ2	PROPN
iajs-2946	95	5	=	=	SYM
iajs-2946	95	6	1	1	NUM
iajs-2946	95	7	𝑛	𝑛	PROPN
iajs-2946	95	8	[	[	PUNCT
iajs-2946	95	9	𝑛	𝑛	PROPN
iajs-2946	95	10	𝛾2	𝛾2	NOUN
iajs-2946	95	11	−	−	PROPN
iajs-2946	95	12	2	2	NUM
iajs-2946	95	13	∑	∑	PUNCT
iajs-2946	95	14	(	(	PUNCT
iajs-2946	95	15	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	95	16	𝑖=1	𝑖=1	PROPN
iajs-2946	95	17	𝛾3	𝛾3	PROPN
iajs-2946	95	18	]	]	PUNCT
iajs-2946	95	19	,	,	PUNCT
iajs-2946	95	20	𝜕𝛿	𝜕𝛿	NOUN
iajs-2946	95	21	𝜕𝛿	𝜕𝛿	NOUN
iajs-2946	95	22	=	=	SYM
iajs-2946	95	23	1	1	NUM
iajs-2946	95	24	𝑛	𝑛	PROPN
iajs-2946	95	25	[	[	PUNCT
iajs-2946	95	26	𝑛	𝑛	PRON
iajs-2946	95	27	𝛾	𝛾	NOUN
iajs-2946	95	28	+	+	CCONJ
iajs-2946	95	29	(	(	PUNCT
iajs-2946	95	30	𝑎−1	𝑎−1	PROPN
iajs-2946	95	31	)	)	PUNCT
iajs-2946	95	32	𝛿	𝛿	ADJ
iajs-2946	95	33	−	−	PROPN
iajs-2946	95	34	𝑏	𝑏	NOUN
iajs-2946	95	35	]	]	PUNCT
iajs-2946	95	36	,	,	PUNCT
iajs-2946	95	37	∂2δ	∂2δ	PROPN
iajs-2946	95	38	∂δ2	∂δ2	NOUN
iajs-2946	95	39	=	=	PUNCT
iajs-2946	95	40	(	(	PUNCT
iajs-2946	95	41	1−𝑎	1−𝑎	X
iajs-2946	95	42	)	)	PUNCT
iajs-2946	95	43	𝑛𝛿2	𝑛𝛿2	NOUN
iajs-2946	95	44	,	,	PUNCT
iajs-2946	95	45	∂2δ	∂2δ	PROPN
iajs-2946	95	46	∂γ	∂γ	PROPN
iajs-2946	95	47	∂δ	∂δ	PROPN
iajs-2946	96	1	=	=	PUNCT
iajs-2946	97	1	−1	−1	NOUN
iajs-2946	97	2	𝛾2	𝛾2	VERB
iajs-2946	97	3	,	,	PUNCT
iajs-2946	97	4	│	│	ADJ
iajs-2946	97	5	∑	∑	NOUN
iajs-2946	97	6	│	│	ADJ
iajs-2946	97	7	=	=	SYM
iajs-2946	97	8	[	[	PUNCT
iajs-2946	97	9	1	1	NUM
iajs-2946	97	10	𝑛	𝑛	PROPN
iajs-2946	97	11	[	[	PUNCT
iajs-2946	97	12	𝑛	𝑛	PROPN
iajs-2946	97	13	𝛾2	𝛾2	NOUN
iajs-2946	97	14	−	−	PROPN
iajs-2946	97	15	2	2	NUM
iajs-2946	97	16	∑	∑	PUNCT
iajs-2946	97	17	(	(	PUNCT
iajs-2946	97	18	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	97	19	𝑖=1	𝑖=1	PROPN
iajs-2946	97	20	𝛾3	𝛾3	PROPN
iajs-2946	97	21	]	]	PUNCT
iajs-2946	97	22	(	(	PUNCT
iajs-2946	97	23	1−𝑎	1−𝑎	X
iajs-2946	97	24	)	)	PUNCT
iajs-2946	97	25	𝑛𝛿2	𝑛𝛿2	VERB
iajs-2946	97	26	−	−	PROPN
iajs-2946	97	27	1	1	NUM
iajs-2946	97	28	𝛾4	𝛾4	NOUN
iajs-2946	97	29	]	]	PUNCT
iajs-2946	97	30	−1	−1	NOUN
iajs-2946	97	31	.	.	PUNCT
iajs-2946	98	1	in	in	ADP
iajs-2946	98	2	order	order	NOUN
iajs-2946	98	3	to	to	PART
iajs-2946	98	4	compute	compute	VERB
iajs-2946	98	5	|∑𝛾𝑆𝐸𝐿	|∑𝛾𝑆𝐸𝐿	NOUN
iajs-2946	98	6	∗	∗	NOUN
iajs-2946	98	7	|	|	ADV
iajs-2946	98	8	,	,	PUNCT
iajs-2946	98	9	we	we	PRON
iajs-2946	98	10	first	first	ADV
iajs-2946	98	11	get	get	VERB
iajs-2946	98	12	the	the	DET
iajs-2946	98	13	following	follow	VERB
iajs-2946	98	14	expressions	expression	NOUN
iajs-2946	98	15	:	:	PUNCT
iajs-2946	98	16	𝜕𝛿∗	𝜕𝛿∗	PROPN
iajs-2946	98	17	𝜕𝛾	𝜕𝛾	NOUN
iajs-2946	98	18	=	=	SYM
iajs-2946	98	19	1	1	NUM
iajs-2946	98	20	𝑛	𝑛	PROPN
iajs-2946	98	21	[	[	PUNCT
iajs-2946	98	22	−𝑛	−𝑛	NOUN
iajs-2946	98	23	𝛾	𝛾	ADP
iajs-2946	98	24	+	+	ADV
iajs-2946	98	25	∑	∑	PUNCT
iajs-2946	98	26	(	(	PUNCT
iajs-2946	98	27	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	98	28	𝑖=1	𝑖=1	PROPN
iajs-2946	98	29	𝛾2	𝛾2	NOUN
iajs-2946	98	30	–	–	PUNCT
iajs-2946	98	31	𝑐	𝑐	X
iajs-2946	98	32	]	]	X
iajs-2946	98	33	+	+	CCONJ
iajs-2946	98	34	1	1	NUM
iajs-2946	98	35	𝑛𝛾	𝑛𝛾	VERB
iajs-2946	98	36	,	,	PUNCT
iajs-2946	98	37	∂2𝛿∗	∂2𝛿∗	X
iajs-2946	98	38	∂γ2	∂γ2	PROPN
iajs-2946	98	39	=	=	SYM
iajs-2946	98	40	1	1	NUM
iajs-2946	98	41	𝑛	𝑛	PROPN
iajs-2946	98	42	[	[	PUNCT
iajs-2946	98	43	𝑛	𝑛	PROPN
iajs-2946	98	44	𝛾2	𝛾2	NOUN
iajs-2946	98	45	−	−	PROPN
iajs-2946	98	46	2	2	NUM
iajs-2946	98	47	∑	∑	PUNCT
iajs-2946	98	48	(	(	PUNCT
iajs-2946	98	49	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	98	50	𝑖=1	𝑖=1	PROPN
iajs-2946	98	51	𝛾3	𝛾3	PROPN
iajs-2946	98	52	]	]	PUNCT
iajs-2946	98	53	−	−	PROPN
iajs-2946	98	54	1	1	NUM
iajs-2946	98	55	𝑛𝛾2	𝑛𝛾2	NOUN
iajs-2946	98	56	,	,	PUNCT
iajs-2946	98	57	𝜕𝛿∗	𝜕𝛿∗	ADJ
iajs-2946	98	58	𝜕𝛿	𝜕𝛿	NOUN
iajs-2946	98	59	=	=	SYM
iajs-2946	98	60	1	1	NUM
iajs-2946	98	61	𝑛	𝑛	PROPN
iajs-2946	98	62	[	[	PUNCT
iajs-2946	98	63	𝑛	𝑛	PRON
iajs-2946	98	64	𝛾	𝛾	NOUN
iajs-2946	98	65	+	+	CCONJ
iajs-2946	98	66	(	(	PUNCT
iajs-2946	98	67	𝑎−1	𝑎−1	PROPN
iajs-2946	98	68	)	)	PUNCT
iajs-2946	98	69	𝛿	𝛿	ADJ
iajs-2946	98	70	−	−	PROPN
iajs-2946	98	71	𝑏	𝑏	NOUN
iajs-2946	98	72	]	]	PUNCT
iajs-2946	98	73	,	,	PUNCT
iajs-2946	98	74	∂2𝛿∗	∂2𝛿∗	X
iajs-2946	98	75	∂δ2	∂δ2	NOUN
iajs-2946	98	76	=	=	SYM
iajs-2946	98	77	(	(	PUNCT
iajs-2946	98	78	1−𝑎	1−𝑎	X
iajs-2946	98	79	)	)	PUNCT
iajs-2946	98	80	𝑛𝛿2	𝑛𝛿2	VERB
iajs-2946	98	81	,	,	PUNCT
iajs-2946	98	82	∂2𝛿∗	∂2𝛿∗	NUM
iajs-2946	99	1	∂γ	∂γ	PROPN
iajs-2946	100	1	∂δ	∂δ	PROPN
iajs-2946	101	1	=	=	SYM
iajs-2946	102	1	−1	−1	NOUN
iajs-2946	102	2	𝛾2	𝛾2	NOUN
iajs-2946	102	3	,	,	PUNCT
iajs-2946	102	4	|∑𝛾𝑆𝐸𝐿	|∑𝛾𝑆𝐸𝐿	NOUN
iajs-2946	102	5	∗	∗	NOUN
iajs-2946	102	6	|	|	NOUN
iajs-2946	103	1	=	=	PRON
iajs-2946	104	1	[	[	PUNCT
iajs-2946	104	2	1	1	NUM
iajs-2946	104	3	𝑛	𝑛	PROPN
iajs-2946	104	4	[	[	PUNCT
iajs-2946	104	5	𝑛	𝑛	PROPN
iajs-2946	104	6	𝛾2	𝛾2	NOUN
iajs-2946	104	7	−	−	PROPN
iajs-2946	104	8	2	2	NUM
iajs-2946	104	9	∑	∑	PUNCT
iajs-2946	104	10	(	(	PUNCT
iajs-2946	104	11	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	104	12	𝑖=1	𝑖=1	PROPN
iajs-2946	104	13	𝛾3	𝛾3	NOUN
iajs-2946	104	14	−	−	NOUN
iajs-2946	104	15	1	1	NUM
iajs-2946	104	16	𝛾2	𝛾2	NOUN
iajs-2946	104	17	]	]	PUNCT
iajs-2946	104	18	(	(	PUNCT
iajs-2946	104	19	1−𝑎	1−𝑎	X
iajs-2946	104	20	)	)	PUNCT
iajs-2946	104	21	𝑛𝛿2	𝑛𝛿2	VERB
iajs-2946	104	22	−	−	PROPN
iajs-2946	104	23	1	1	NUM
iajs-2946	104	24	𝛾4]−1	𝛾4]−1	NOUN
iajs-2946	104	25	,	,	PUNCT
iajs-2946	104	26	𝛾𝑆=	𝛾𝑆=	PROPN
iajs-2946	104	27	√	√	VERB
iajs-2946	105	1	|∑𝛾𝑆𝐸𝐿	|∑𝛾𝑆𝐸𝐿	NOUN
iajs-2946	105	2	∗	∗	NOUN
iajs-2946	105	3	|	|	ADV
iajs-2946	105	4	│	│	VERB
iajs-2946	105	5	∑	∑	PROPN
iajs-2946	105	6	│	│	X
iajs-2946	105	7	𝑒[𝑛{𝛿𝛾	𝑒[𝑛{𝛿𝛾	VERB
iajs-2946	105	8	∗	∗	NOUN
iajs-2946	105	9	(	(	PUNCT
iajs-2946	105	10	�	�	NOUN
iajs-2946	105	11	̂	̂	NOUN
iajs-2946	105	12	�	�	NOUN
iajs-2946	105	13	𝛿∗	𝛿∗	PROPN
iajs-2946	105	14	,	,	PUNCT
iajs-2946	105	15	�	�	PROPN
iajs-2946	105	16	̂	̂	NOUN
iajs-2946	105	17	�	�	NOUN
iajs-2946	105	18	𝛿∗)−	𝛿∗)−	PROPN
iajs-2946	105	19	δ(	δ(	PROPN
iajs-2946	105	20	�	�	PROPN
iajs-2946	105	21	̂	̂	NOUN
iajs-2946	105	22	�	�	NOUN
iajs-2946	105	23	𝛿,	𝛿,	NOUN
iajs-2946	105	24	�	�	PROPN
iajs-2946	105	25	̂	̂	NOUN
iajs-2946	105	26	�	�	NOUN
iajs-2946	105	27	𝛿	𝛿	NOUN
iajs-2946	105	28	)	)	PUNCT
iajs-2946	105	29	}	}	PUNCT
iajs-2946	105	30	]	]	PUNCT
iajs-2946	105	31	.	.	PUNCT
iajs-2946	106	1	(	(	PUNCT
iajs-2946	106	2	11	11	NUM
iajs-2946	106	3	)	)	SYM
iajs-2946	106	4	ii	ii	NOUN
iajs-2946	106	5	)	)	PUNCT
iajs-2946	106	6	bayesian	bayesian	NOUN
iajs-2946	106	7	estimation	estimation	NOUN
iajs-2946	106	8	for	for	ADP
iajs-2946	106	9	δ	δ	PROPN
iajs-2946	106	10	under	under	ADP
iajs-2946	106	11	squared	square	VERB
iajs-2946	106	12	error	error	NOUN
iajs-2946	106	13	loss	loss	NOUN
iajs-2946	106	14	function	function	NOUN
iajs-2946	106	15	similarly	similarly	ADV
iajs-2946	106	16	,	,	PUNCT
iajs-2946	106	17	𝛿	𝛿	PROPN
iajs-2946	106	18	can	can	AUX
iajs-2946	106	19	be	be	AUX
iajs-2946	106	20	estimated	estimate	VERB
iajs-2946	106	21	as	as	SCONJ
iajs-2946	106	22	follows	follow	VERB
iajs-2946	106	23	:	:	PUNCT
iajs-2946	106	24	assume	assume	VERB
iajs-2946	106	25	that	that	SCONJ
iajs-2946	106	26	,	,	PUNCT
iajs-2946	106	27	𝑢(𝛾	𝑢(𝛾	PRON
iajs-2946	106	28	,	,	PUNCT
iajs-2946	106	29	𝛿	𝛿	ADJ
iajs-2946	106	30	)	)	PUNCT
iajs-2946	106	31	=	=	SYM
iajs-2946	107	1	𝛿.	𝛿.	NOUN
iajs-2946	107	2	and	and	CCONJ
iajs-2946	107	3	therefore	therefore	ADV
iajs-2946	107	4	,	,	PUNCT
iajs-2946	107	5	𝛿𝛿	𝛿𝛿	PROPN
iajs-2946	107	6	∗(𝛾	∗(𝛾	PROPN
iajs-2946	107	7	,	,	PUNCT
iajs-2946	107	8	𝛿	𝛿	ADJ
iajs-2946	107	9	)	)	PUNCT
iajs-2946	107	10	=	=	SYM
iajs-2946	107	11	δ(γ	δ(γ	NOUN
iajs-2946	107	12	,	,	PUNCT
iajs-2946	107	13	δ	δ	NOUN
iajs-2946	107	14	)	)	PUNCT
iajs-2946	108	1	+	+	CCONJ
iajs-2946	108	2	ln	ln	ADJ
iajs-2946	108	3	𝛿	𝛿	ADJ
iajs-2946	108	4	𝑛	𝑛	NOUN
iajs-2946	108	5	.	.	PUNCT
iajs-2946	109	1	in	in	ADP
iajs-2946	109	2	order	order	NOUN
iajs-2946	109	3	to	to	PART
iajs-2946	109	4	compute	compute	VERB
iajs-2946	109	5	|∑𝛿𝑆𝐸𝐿	|∑𝛿𝑆𝐸𝐿	PROPN
iajs-2946	109	6	∗	∗	NOUN
iajs-2946	109	7	|	|	ADV
iajs-2946	109	8	,	,	PUNCT
iajs-2946	109	9	we	we	PRON
iajs-2946	109	10	first	first	ADV
iajs-2946	109	11	get	get	VERB
iajs-2946	109	12	the	the	DET
iajs-2946	109	13	following	follow	VERB
iajs-2946	109	14	expressions	expression	NOUN
iajs-2946	109	15	:	:	PUNCT
iajs-2946	109	16	𝜕𝛿∗	𝜕𝛿∗	PROPN
iajs-2946	109	17	𝜕𝛾	𝜕𝛾	NOUN
iajs-2946	109	18	=	=	SYM
iajs-2946	109	19	1	1	NUM
iajs-2946	109	20	𝑛	𝑛	PROPN
iajs-2946	109	21	[	[	PUNCT
iajs-2946	109	22	−𝑛	−𝑛	NOUN
iajs-2946	109	23	𝛾	𝛾	ADP
iajs-2946	109	24	+	+	ADV
iajs-2946	109	25	∑	∑	PUNCT
iajs-2946	109	26	(	(	PUNCT
iajs-2946	109	27	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	109	28	𝑖=1	𝑖=1	PROPN
iajs-2946	109	29	𝛾2	𝛾2	NOUN
iajs-2946	109	30	–	–	PUNCT
iajs-2946	109	31	𝑐	𝑐	NOUN
iajs-2946	109	32	]	]	X
iajs-2946	109	33	,	,	PUNCT
iajs-2946	109	34	∂2𝛿∗	∂2𝛿∗	X
iajs-2946	109	35	∂γ2	∂γ2	PROPN
iajs-2946	109	36	=	=	SYM
iajs-2946	109	37	1	1	NUM
iajs-2946	109	38	𝑛	𝑛	PROPN
iajs-2946	109	39	[	[	PUNCT
iajs-2946	109	40	𝑛	𝑛	PROPN
iajs-2946	109	41	𝛾2	𝛾2	NOUN
iajs-2946	109	42	−	−	PROPN
iajs-2946	109	43	2	2	NUM
iajs-2946	109	44	∑	∑	PUNCT
iajs-2946	109	45	(	(	PUNCT
iajs-2946	109	46	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	109	47	𝑖=1	𝑖=1	PROPN
iajs-2946	109	48	𝛾3	𝛾3	PROPN
iajs-2946	109	49	]	]	PUNCT
iajs-2946	109	50	,	,	PUNCT
iajs-2946	109	51	𝜕𝛿∗	𝜕𝛿∗	ADJ
iajs-2946	109	52	𝜕𝛿	𝜕𝛿	NOUN
iajs-2946	109	53	=	=	SYM
iajs-2946	109	54	1	1	NUM
iajs-2946	109	55	𝑛	𝑛	PROPN
iajs-2946	109	56	[	[	PUNCT
iajs-2946	109	57	𝑛	𝑛	PRON
iajs-2946	109	58	𝛾	𝛾	NOUN
iajs-2946	109	59	+	+	CCONJ
iajs-2946	109	60	(	(	PUNCT
iajs-2946	109	61	𝑎−1	𝑎−1	PROPN
iajs-2946	109	62	)	)	PUNCT
iajs-2946	109	63	𝛿	𝛿	ADJ
iajs-2946	109	64	−	−	PROPN
iajs-2946	109	65	𝑏	𝑏	NOUN
iajs-2946	109	66	]	]	PUNCT
iajs-2946	110	1	+	+	CCONJ
iajs-2946	110	2	1	1	NUM
iajs-2946	110	3	𝑛𝛿	𝑛𝛿	NOUN
iajs-2946	110	4	,	,	PUNCT
iajs-2946	110	5	∂2𝛿∗	∂2𝛿∗	X
iajs-2946	111	1	∂δ2	∂δ2	NOUN
iajs-2946	111	2	=	=	SYM
iajs-2946	111	3	(	(	PUNCT
iajs-2946	111	4	1−𝑎	1−𝑎	X
iajs-2946	111	5	)	)	PUNCT
iajs-2946	111	6	𝑛𝛿2	𝑛𝛿2	VERB
iajs-2946	111	7	−	−	NOUN
iajs-2946	111	8	1	1	NUM
iajs-2946	111	9	𝑛δ2	𝑛δ2	NOUN
iajs-2946	111	10	,	,	PUNCT
iajs-2946	111	11	∂2𝛿∗	∂2𝛿∗	NUM
iajs-2946	112	1	∂γ	∂γ	PROPN
iajs-2946	112	2	∂δ	∂δ	PROPN
iajs-2946	113	1	=	=	SYM
iajs-2946	113	2	−1	−1	NOUN
iajs-2946	113	3	𝛾2	𝛾2	NOUN
iajs-2946	113	4	,	,	PUNCT
iajs-2946	113	5	|∑𝛿𝑆𝐸𝐿	|∑𝛿𝑆𝐸𝐿	PROPN
iajs-2946	113	6	∗	∗	NOUN
iajs-2946	113	7	|	|	NOUN
iajs-2946	114	1	=	=	PRON
iajs-2946	115	1	[	[	PUNCT
iajs-2946	115	2	1	1	NUM
iajs-2946	115	3	𝑛	𝑛	PROPN
iajs-2946	115	4	[	[	PUNCT
iajs-2946	115	5	𝑛	𝑛	PROPN
iajs-2946	115	6	𝛾2	𝛾2	NOUN
iajs-2946	115	7	−	−	PROPN
iajs-2946	115	8	2	2	NUM
iajs-2946	115	9	∑	∑	PUNCT
iajs-2946	115	10	(	(	PUNCT
iajs-2946	115	11	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	115	12	𝑖=1	𝑖=1	PROPN
iajs-2946	115	13	𝛾3	𝛾3	PROPN
iajs-2946	115	14	]	]	PUNCT
iajs-2946	115	15	(	(	PUNCT
iajs-2946	115	16	1−𝑎	1−𝑎	X
iajs-2946	115	17	)	)	PUNCT
iajs-2946	115	18	𝑛𝛿2	𝑛𝛿2	VERB
iajs-2946	115	19	−	−	NOUN
iajs-2946	115	20	1	1	NUM
iajs-2946	115	21	𝑛δ2	𝑛δ2	NOUN
iajs-2946	115	22	−	−	NOUN
iajs-2946	115	23	1	1	NUM
iajs-2946	115	24	𝛾4	𝛾4	NOUN
iajs-2946	115	25	]	]	PUNCT
iajs-2946	115	26	−1	−1	NOUN
iajs-2946	115	27	.	.	PUNCT
iajs-2946	116	1	then	then	ADV
iajs-2946	116	2	,	,	PUNCT
iajs-2946	116	3	ihjpas	ihjpas	PROPN
iajs-2946	116	4	.	.	PUNCT
iajs-2946	117	1	36(2)2023	36(2)2023	NUM
iajs-2946	117	2	294	294	NUM
iajs-2946	117	3	�	�	PROPN
iajs-2946	117	4	̂	̂	NOUN
iajs-2946	117	5	�	�	NOUN
iajs-2946	117	6	𝑺=	𝑺=	NOUN
iajs-2946	117	7	√	√	NUM
iajs-2946	117	8	|∑𝜹𝑺𝑬𝑳	|∑𝜹𝑺𝑬𝑳	NOUN
iajs-2946	117	9	∗	∗	NOUN
iajs-2946	117	10	|	|	ADV
iajs-2946	117	11	│	│	VERB
iajs-2946	117	12	∑	∑	NUM
iajs-2946	117	13	│	│	X
iajs-2946	117	14	𝒆[𝒏{𝜹𝜹	𝒆[𝒏{𝜹𝜹	NOUN
iajs-2946	117	15	∗	∗	NOUN
iajs-2946	117	16	(	(	PUNCT
iajs-2946	117	17	�	�	NOUN
iajs-2946	117	18	̂	̂	NOUN
iajs-2946	117	19	�	�	NOUN
iajs-2946	117	20	𝜹∗	𝜹∗	NOUN
iajs-2946	117	21	,	,	PUNCT
iajs-2946	117	22	�	�	PROPN
iajs-2946	117	23	̂	̂	NOUN
iajs-2946	117	24	�	�	PROPN
iajs-2946	117	25	𝜹∗)−	𝜹∗)−	PRON
iajs-2946	117	26	𝛅(	𝛅(	NUM
iajs-2946	117	27	�	�	PROPN
iajs-2946	117	28	̂	̂	VERB
iajs-2946	117	29	�	�	NOUN
iajs-2946	117	30	𝜹,	𝜹,	NOUN
iajs-2946	117	31	�	�	PROPN
iajs-2946	117	32	̂	̂	NOUN
iajs-2946	117	33	�	�	NOUN
iajs-2946	117	34	𝜹	𝜹	NOUN
iajs-2946	117	35	)	)	PUNCT
iajs-2946	117	36	}	}	PUNCT
iajs-2946	117	37	]	]	PUNCT
iajs-2946	117	38	.	.	PUNCT
iajs-2946	118	1	(	(	PUNCT
iajs-2946	118	2	12	12	NUM
iajs-2946	118	3	)	)	PUNCT
iajs-2946	118	4	3.4	3.4	NUM
iajs-2946	118	5	bayes	bayes	PROPN
iajs-2946	118	6	estimator	estimator	NOUN
iajs-2946	118	7	under	under	ADP
iajs-2946	118	8	precautionary	precautionary	ADJ
iajs-2946	118	9	loss	loss	NOUN
iajs-2946	118	10	function	function	NOUN
iajs-2946	118	11	norstrom	norstrom	ADP
iajs-2946	118	12	(	(	PUNCT
iajs-2946	118	13	1996	1996	NUM
iajs-2946	118	14	)	)	PUNCT
iajs-2946	118	15	introduced	introduce	VERB
iajs-2946	118	16	asymmetric	asymmetric	ADJ
iajs-2946	118	17	surrogate	surrogate	ADJ
iajs-2946	118	18	precautionary	precautionary	ADJ
iajs-2946	118	19	loss	loss	NOUN
iajs-2946	118	20	functions	function	NOUN
iajs-2946	118	21	and	and	CCONJ
iajs-2946	118	22	also	also	ADV
iajs-2946	118	23	introduced	introduce	VERB
iajs-2946	118	24	a	a	DET
iajs-2946	118	25	general	general	ADJ
iajs-2946	118	26	class	class	NOUN
iajs-2946	118	27	of	of	ADP
iajs-2946	118	28	precautionary	precautionary	ADJ
iajs-2946	118	29	loss	loss	NOUN
iajs-2946	118	30	functions	function	NOUN
iajs-2946	118	31	as	as	ADP
iajs-2946	118	32	a	a	DET
iajs-2946	118	33	special	special	ADJ
iajs-2946	118	34	case	case	NOUN
iajs-2946	118	35	.	.	PUNCT
iajs-2946	119	1	these	these	DET
iajs-2946	119	2	loss	loss	NOUN
iajs-2946	119	3	functions	function	NOUN
iajs-2946	119	4	get	get	VERB
iajs-2946	119	5	infinitely	infinitely	ADV
iajs-2946	119	6	close	close	ADJ
iajs-2946	119	7	to	to	ADP
iajs-2946	119	8	the	the	DET
iajs-2946	119	9	origin	origin	NOUN
iajs-2946	119	10	to	to	PART
iajs-2946	119	11	prevent	prevent	VERB
iajs-2946	119	12	underestimation	underestimation	NOUN
iajs-2946	119	13	,	,	PUNCT
iajs-2946	119	14	thus	thus	ADV
iajs-2946	119	15	giving	give	VERB
iajs-2946	119	16	conservative	conservative	ADJ
iajs-2946	119	17	estimates	estimate	NOUN
iajs-2946	119	18	,	,	PUNCT
iajs-2946	119	19	especially	especially	ADV
iajs-2946	119	20	when	when	SCONJ
iajs-2946	119	21	estimating	estimate	VERB
iajs-2946	119	22	low	low	ADJ
iajs-2946	119	23	failure	failure	NOUN
iajs-2946	119	24	rates	rate	NOUN
iajs-2946	119	25	.	.	PUNCT
iajs-2946	120	1	these	these	DET
iajs-2946	120	2	capabilities	capability	NOUN
iajs-2946	120	3	are	be	AUX
iajs-2946	120	4	very	very	ADV
iajs-2946	120	5	useful	useful	ADJ
iajs-2946	120	6	,	,	PUNCT
iajs-2946	120	7	but	but	CCONJ
iajs-2946	120	8	underestimating	underestimate	VERB
iajs-2946	120	9	them	they	PRON
iajs-2946	120	10	can	can	AUX
iajs-2946	120	11	have	have	VERB
iajs-2946	120	12	disastrous	disastrous	ADJ
iajs-2946	120	13	consequences	consequence	NOUN
iajs-2946	120	14	.	.	PUNCT
iajs-2946	121	1	a	a	DET
iajs-2946	121	2	very	very	ADV
iajs-2946	121	3	useful	useful	ADJ
iajs-2946	121	4	and	and	CCONJ
iajs-2946	121	5	simple	simple	ADJ
iajs-2946	121	6	asymmetric	asymmetric	ADJ
iajs-2946	121	7	spare	spare	ADJ
iajs-2946	121	8	-	-	PUNCT
iajs-2946	121	9	loss	loss	NOUN
iajs-2946	121	10	function	function	NOUN
iajs-2946	121	11	is	be	AUX
iajs-2946	121	12	[	[	X
iajs-2946	121	13	6	6	NUM
iajs-2946	121	14	]	]	X
iajs-2946	121	15	:	:	PUNCT
iajs-2946	121	16	l(θ̂	l(θ̂	PROPN
iajs-2946	121	17	,	,	PUNCT
iajs-2946	121	18	θ	θ	PROPN
iajs-2946	121	19	)	)	PUNCT
iajs-2946	121	20	=	=	SYM
iajs-2946	121	21	(	(	PUNCT
iajs-2946	121	22	θ−θ̂	θ−θ̂	X
iajs-2946	121	23	)	)	PUNCT
iajs-2946	121	24	2	2	NUM
iajs-2946	121	25	θ̂	θ̂	NUM
iajs-2946	121	26	.	.	PUNCT
iajs-2946	122	1	based	base	VERB
iajs-2946	122	2	on	on	ADP
iajs-2946	122	3	the	the	DET
iajs-2946	122	4	precautionary	precautionary	ADJ
iajs-2946	122	5	loss	loss	NOUN
iajs-2946	122	6	function	function	NOUN
iajs-2946	122	7	,	,	PUNCT
iajs-2946	122	8	the	the	DET
iajs-2946	122	9	risk	risk	NOUN
iajs-2946	122	10	function	function	NOUN
iajs-2946	122	11	rp(γ̂	rp(γ̂	NOUN
iajs-2946	122	12	,	,	PUNCT
iajs-2946	122	13	γ	γ	NOUN
iajs-2946	122	14	)	)	PUNCT
iajs-2946	122	15	can	can	AUX
iajs-2946	122	16	be	be	AUX
iajs-2946	122	17	derived	derive	VERB
iajs-2946	122	18	as	as	SCONJ
iajs-2946	122	19	follows	follow	VERB
iajs-2946	122	20	:	:	PUNCT
iajs-2946	122	21	rp(γ̂	rp(γ̂	NOUN
iajs-2946	122	22	,	,	PUNCT
iajs-2946	122	23	γ	γ	NOUN
iajs-2946	122	24	)	)	PUNCT
iajs-2946	122	25	=	=	SYM
iajs-2946	122	26	e[l(γ̂	e[l(γ̂	NOUN
iajs-2946	122	27	,	,	PUNCT
iajs-2946	122	28	γ	γ	NOUN
iajs-2946	122	29	)	)	PUNCT
iajs-2946	122	30	]	]	PUNCT
iajs-2946	123	1	=	=	SYM
iajs-2946	123	2	∫	∫	PROPN
iajs-2946	123	3	l(γ̂	l(γ̂	PROPN
iajs-2946	123	4	,	,	PUNCT
iajs-2946	123	5	γ	γ	NOUN
iajs-2946	123	6	)	)	PUNCT
iajs-2946	123	7	h(γ|x)dγ	h(γ|x)dγ	NOUN
iajs-2946	123	8	∞	∞	PROPN
iajs-2946	123	9	0	0	NUM
iajs-2946	123	10	rp(γ̂	rp(γ̂	NOUN
iajs-2946	123	11	,	,	PUNCT
iajs-2946	123	12	γ	γ	NOUN
iajs-2946	123	13	)	)	PUNCT
iajs-2946	123	14	=	=	SYM
iajs-2946	123	15	∫	∫	PROPN
iajs-2946	123	16	(	(	PUNCT
iajs-2946	123	17	γ	γ	PROPN
iajs-2946	123	18	−	−	PROPN
iajs-2946	123	19	γ̂)2	γ̂)2	PROPN
iajs-2946	123	20	γ̂	γ̂	VERB
iajs-2946	124	1	∞	∞	NUM
iajs-2946	124	2	0	0	NUM
iajs-2946	124	3	h(γ|x)dγ	h(γ|x)dγ	NOUN
iajs-2946	124	4	=	=	SYM
iajs-2946	124	5	∫	∫	PROPN
iajs-2946	124	6	(	(	PUNCT
iajs-2946	124	7	γ2γ̂−1	γ2γ̂−1	NOUN
iajs-2946	124	8	)	)	PUNCT
iajs-2946	124	9	h(γ|x)dγ	h(γ|x)dγ	NOUN
iajs-2946	124	10	−	−	PROPN
iajs-2946	124	11	∫	∫	PROPN
iajs-2946	124	12	2γ	2γ	VERB
iajs-2946	124	13	h(γ|x)dγ	h(γ|x)dγ	NOUN
iajs-2946	124	14	∞	∞	PROPN
iajs-2946	124	15	0	0	NUM
iajs-2946	125	1	+	+	CCONJ
iajs-2946	125	2	∫	∫	PROPN
iajs-2946	125	3	γ̂	γ̂	NUM
iajs-2946	126	1	∞	∞	NUM
iajs-2946	126	2	0	0	NUM
iajs-2946	127	1	∞	∞	NUM
iajs-2946	127	2	0	0	NUM
iajs-2946	127	3	h(γ|x)dγ	h(γ|x)dγ	PROPN
iajs-2946	127	4	rp(γ̂	rp(γ̂	NOUN
iajs-2946	127	5	,	,	PUNCT
iajs-2946	127	6	γ	γ	NOUN
iajs-2946	127	7	)	)	PUNCT
iajs-2946	127	8	=	=	SYM
iajs-2946	127	9	e(γ2|x)γ̂−1	e(γ2|x)γ̂−1	NOUN
iajs-2946	127	10	−	−	ADP
iajs-2946	127	11	2e(γ|x	2e(γ|x	NUM
iajs-2946	127	12	)	)	PUNCT
iajs-2946	128	1	+	+	NUM
iajs-2946	128	2	γ̂.	γ̂.	NOUN
iajs-2946	128	3	taking	take	VERB
iajs-2946	128	4	the	the	DET
iajs-2946	128	5	partial	partial	ADJ
iajs-2946	128	6	derivative	derivative	NOUN
iajs-2946	128	7	for	for	ADP
iajs-2946	128	8	rp(γ̂	rp(γ̂	NOUN
iajs-2946	128	9	,	,	PUNCT
iajs-2946	128	10	γ	γ	NOUN
iajs-2946	128	11	)	)	PUNCT
iajs-2946	128	12	with	with	ADP
iajs-2946	128	13	respect	respect	NOUN
iajs-2946	128	14	to	to	ADP
iajs-2946	128	15	γ̂	γ̂	PUNCT
iajs-2946	128	16	and	and	CCONJ
iajs-2946	128	17	setting	set	VERB
iajs-2946	128	18	it	it	PRON
iajs-2946	128	19	equal	equal	ADJ
iajs-2946	128	20	to	to	ADP
iajs-2946	128	21	zero	zero	NUM
iajs-2946	128	22	yields	yield	NOUN
iajs-2946	128	23	:	:	PUNCT
iajs-2946	129	1	−e(γ2|x)γ̂−2	−e(γ2|x)γ̂−2	NOUN
iajs-2946	129	2	+	+	CCONJ
iajs-2946	129	3	1	1	NUM
iajs-2946	129	4	=	=	SYM
iajs-2946	129	5	0	0	NUM
iajs-2946	129	6	.	.	PUNCT
iajs-2946	130	1	thus	thus	ADV
iajs-2946	130	2	,	,	PUNCT
iajs-2946	130	3	γ̂p	γ̂p	SYM
iajs-2946	130	4	2	2	NUM
iajs-2946	130	5	=	=	SYM
iajs-2946	130	6	e(γ2|x	e(γ2|x	NOUN
iajs-2946	130	7	)	)	PUNCT
iajs-2946	130	8	,	,	PUNCT
iajs-2946	130	9	hence	hence	ADV
iajs-2946	130	10	,	,	PUNCT
iajs-2946	130	11	the	the	DET
iajs-2946	130	12	bayesian	bayesian	NOUN
iajs-2946	130	13	estimator	estimator	NOUN
iajs-2946	130	14	for	for	ADP
iajs-2946	130	15	γ	γ	NOUN
iajs-2946	130	16	relative	relative	ADJ
iajs-2946	130	17	to	to	ADP
iajs-2946	130	18	the	the	DET
iajs-2946	130	19	precautionary	precautionary	ADJ
iajs-2946	130	20	loss	loss	NOUN
iajs-2946	130	21	function	function	NOUN
iajs-2946	130	22	is	be	AUX
iajs-2946	130	23	denoted	denote	VERB
iajs-2946	130	24	by	by	ADP
iajs-2946	130	25	γ̂p	γ̂p	X
iajs-2946	130	26	is	be	AUX
iajs-2946	130	27	given	give	VERB
iajs-2946	130	28	by	by	ADP
iajs-2946	130	29	:	:	PUNCT
iajs-2946	130	30	γ̂p	γ̂p	PROPN
iajs-2946	130	31	=	=	SYM
iajs-2946	130	32	√e(γ2|x	√e(γ2|x	PROPN
iajs-2946	130	33	)	)	PUNCT
iajs-2946	130	34	.	.	PUNCT
iajs-2946	131	1	i	i	PRON
iajs-2946	131	2	)	)	PUNCT
iajs-2946	131	3	bayesian	bayesian	NOUN
iajs-2946	131	4	estimation	estimation	NOUN
iajs-2946	131	5	for	for	ADP
iajs-2946	131	6	γ	γ	NOUN
iajs-2946	131	7	under	under	ADP
iajs-2946	131	8	precautionary	precautionary	ADJ
iajs-2946	131	9	loss	loss	NOUN
iajs-2946	131	10	function	function	NOUN
iajs-2946	131	11	obtaining	obtain	VERB
iajs-2946	131	12	bayesian	bayesian	NOUN
iajs-2946	131	13	estimation	estimation	NOUN
iajs-2946	131	14	for	for	ADP
iajs-2946	131	15	𝛾	𝛾	PROPN
iajs-2946	131	16	under	under	ADP
iajs-2946	131	17	plf	plf	NOUN
iajs-2946	131	18	assumes	assume	VERB
iajs-2946	131	19	that	that	SCONJ
iajs-2946	131	20	:	:	PUNCT
iajs-2946	131	21	u(γ	u(γ	PROPN
iajs-2946	131	22	,	,	PUNCT
iajs-2946	131	23	δ	δ	NOUN
iajs-2946	131	24	)	)	PUNCT
iajs-2946	131	25	=	=	PUNCT
iajs-2946	131	26	𝛾2	𝛾2	PROPN
iajs-2946	131	27	.	.	PUNCT
iajs-2946	132	1	and	and	CCONJ
iajs-2946	132	2	therefore	therefore	ADV
iajs-2946	132	3	,	,	PUNCT
iajs-2946	132	4	𝛿𝛿	𝛿𝛿	PROPN
iajs-2946	132	5	∗(𝛾	∗(𝛾	PROPN
iajs-2946	132	6	,	,	PUNCT
iajs-2946	132	7	𝛿	𝛿	ADJ
iajs-2946	132	8	)	)	PUNCT
iajs-2946	132	9	=	=	SYM
iajs-2946	132	10	δ(γ	δ(γ	NOUN
iajs-2946	132	11	,	,	PUNCT
iajs-2946	132	12	δ	δ	NOUN
iajs-2946	132	13	)	)	PUNCT
iajs-2946	133	1	+	+	CCONJ
iajs-2946	133	2	ln	ln	ADJ
iajs-2946	133	3	𝛾2	𝛾2	NOUN
iajs-2946	133	4	𝑛	𝑛	PROPN
iajs-2946	133	5	.	.	PUNCT
iajs-2946	134	1	in	in	ADP
iajs-2946	134	2	order	order	NOUN
iajs-2946	134	3	to	to	PART
iajs-2946	134	4	compute	compute	VERB
iajs-2946	134	5	|∑𝛾𝑃𝐿	|∑𝛾𝑃𝐿	PROPN
iajs-2946	134	6	∗	∗	NOUN
iajs-2946	134	7	|	|	NOUN
iajs-2946	134	8	,	,	PUNCT
iajs-2946	134	9	we	we	PRON
iajs-2946	134	10	first	first	ADV
iajs-2946	134	11	get	get	VERB
iajs-2946	134	12	the	the	DET
iajs-2946	134	13	following	follow	VERB
iajs-2946	134	14	expressions	expression	NOUN
iajs-2946	134	15	:	:	PUNCT
iajs-2946	134	16	𝜕𝛿∗	𝜕𝛿∗	PROPN
iajs-2946	134	17	𝜕𝛾	𝜕𝛾	NOUN
iajs-2946	134	18	=	=	SYM
iajs-2946	134	19	1	1	NUM
iajs-2946	134	20	𝑛	𝑛	PROPN
iajs-2946	134	21	[	[	PUNCT
iajs-2946	134	22	−𝑛	−𝑛	NOUN
iajs-2946	134	23	𝛾	𝛾	ADP
iajs-2946	134	24	+	+	ADV
iajs-2946	134	25	∑	∑	PUNCT
iajs-2946	134	26	(	(	PUNCT
iajs-2946	134	27	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	134	28	𝑖=1	𝑖=1	PROPN
iajs-2946	134	29	𝛾2	𝛾2	VERB
iajs-2946	134	30	–	–	PUNCT
iajs-2946	134	31	𝑐]+	𝑐]+	PROPN
iajs-2946	134	32	2	2	NUM
iajs-2946	134	33	𝑛𝛾	𝑛𝛾	VERB
iajs-2946	134	34	,	,	PUNCT
iajs-2946	134	35	∂2𝛿∗	∂2𝛿∗	X
iajs-2946	134	36	∂γ2	∂γ2	PROPN
iajs-2946	134	37	=	=	SYM
iajs-2946	134	38	1	1	NUM
iajs-2946	134	39	𝑛	𝑛	PROPN
iajs-2946	134	40	[	[	PUNCT
iajs-2946	134	41	𝑛	𝑛	PROPN
iajs-2946	134	42	𝛾2	𝛾2	NOUN
iajs-2946	134	43	−	−	PROPN
iajs-2946	134	44	2	2	NUM
iajs-2946	134	45	∑	∑	PUNCT
iajs-2946	134	46	(	(	PUNCT
iajs-2946	134	47	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	134	48	𝑖=1	𝑖=1	PROPN
iajs-2946	134	49	𝛾3	𝛾3	PROPN
iajs-2946	134	50	]	]	PUNCT
iajs-2946	134	51	−	−	PROPN
iajs-2946	134	52	2	2	NUM
iajs-2946	134	53	𝑛𝛾2	𝑛𝛾2	NOUN
iajs-2946	134	54	,	,	PUNCT
iajs-2946	134	55	𝜕𝛿∗	𝜕𝛿∗	ADJ
iajs-2946	134	56	𝜕𝛿	𝜕𝛿	NOUN
iajs-2946	134	57	=	=	SYM
iajs-2946	134	58	1	1	NUM
iajs-2946	134	59	𝑛	𝑛	PROPN
iajs-2946	134	60	[	[	PUNCT
iajs-2946	134	61	𝑛	𝑛	PRON
iajs-2946	134	62	𝛾	𝛾	NOUN
iajs-2946	134	63	+	+	CCONJ
iajs-2946	134	64	(	(	PUNCT
iajs-2946	134	65	𝑎−1	𝑎−1	PROPN
iajs-2946	134	66	)	)	PUNCT
iajs-2946	134	67	𝛿	𝛿	ADJ
iajs-2946	134	68	−	−	PROPN
iajs-2946	134	69	𝑏	𝑏	NOUN
iajs-2946	134	70	]	]	PUNCT
iajs-2946	134	71	,	,	PUNCT
iajs-2946	134	72	∂2𝛿∗	∂2𝛿∗	X
iajs-2946	134	73	∂δ2	∂δ2	NOUN
iajs-2946	134	74	=	=	SYM
iajs-2946	134	75	(	(	PUNCT
iajs-2946	134	76	1−𝑎	1−𝑎	X
iajs-2946	134	77	)	)	PUNCT
iajs-2946	134	78	𝑛𝛿2	𝑛𝛿2	VERB
iajs-2946	134	79	,	,	PUNCT
iajs-2946	134	80	∂2𝛿∗	∂2𝛿∗	NUM
iajs-2946	134	81	∂γ	∂γ	PROPN
iajs-2946	135	1	∂δ	∂δ	PROPN
iajs-2946	136	1	=	=	SYM
iajs-2946	137	1	−1	−1	NOUN
iajs-2946	137	2	𝛾2	𝛾2	NOUN
iajs-2946	137	3	,	,	PUNCT
iajs-2946	137	4	ihjpas	ihjpa	NOUN
iajs-2946	137	5	.	.	PUNCT
iajs-2946	138	1	36(2)2023	36(2)2023	NUM
iajs-2946	138	2	295	295	NUM
iajs-2946	138	3	|∑𝛾𝑃𝐿	|∑𝛾𝑃𝐿	X
iajs-2946	138	4	∗	∗	NOUN
iajs-2946	138	5	|	|	NOUN
iajs-2946	139	1	=	=	PRON
iajs-2946	139	2	[	[	PUNCT
iajs-2946	139	3	1	1	NUM
iajs-2946	139	4	𝑛	𝑛	PROPN
iajs-2946	139	5	[	[	PUNCT
iajs-2946	139	6	𝑛	𝑛	PROPN
iajs-2946	139	7	𝛾2	𝛾2	NOUN
iajs-2946	139	8	−	−	PROPN
iajs-2946	139	9	2	2	NUM
iajs-2946	139	10	∑	∑	PUNCT
iajs-2946	139	11	(	(	PUNCT
iajs-2946	139	12	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	139	13	𝑖=1	𝑖=1	PROPN
iajs-2946	139	14	𝛾3	𝛾3	NOUN
iajs-2946	139	15	−	−	NOUN
iajs-2946	139	16	2	2	NUM
iajs-2946	139	17	𝛾2	𝛾2	NOUN
iajs-2946	139	18	]	]	PUNCT
iajs-2946	139	19	(	(	PUNCT
iajs-2946	139	20	1−𝑎	1−𝑎	X
iajs-2946	139	21	)	)	PUNCT
iajs-2946	139	22	𝑛𝛿2	𝑛𝛿2	VERB
iajs-2946	139	23	−	−	PROPN
iajs-2946	139	24	1	1	NUM
iajs-2946	139	25	𝛾4	𝛾4	NOUN
iajs-2946	139	26	]	]	PUNCT
iajs-2946	139	27	−1	−1	NOUN
iajs-2946	139	28	.	.	PUNCT
iajs-2946	140	1	hence	hence	ADV
iajs-2946	140	2	,	,	PUNCT
iajs-2946	140	3	𝛾𝑃	𝛾𝑃	PROPN
iajs-2946	140	4	=[	=[	NOUN
iajs-2946	140	5	√	√	ADP
iajs-2946	140	6	|∑𝛾𝑃𝐿	|∑𝛾𝑃𝐿	VERB
iajs-2946	140	7	∗	∗	NOUN
iajs-2946	140	8	|	|	ADV
iajs-2946	140	9	│	│	VERB
iajs-2946	140	10	∑	∑	PROPN
iajs-2946	140	11	│	│	X
iajs-2946	140	12	𝑒[𝑛{𝛿𝛾	𝑒[𝑛{𝛿𝛾	VERB
iajs-2946	140	13	∗	∗	NOUN
iajs-2946	140	14	(	(	PUNCT
iajs-2946	140	15	�	�	NOUN
iajs-2946	140	16	̂	̂	NOUN
iajs-2946	140	17	�	�	NOUN
iajs-2946	140	18	𝛿∗	𝛿∗	PROPN
iajs-2946	140	19	,	,	PUNCT
iajs-2946	140	20	�	�	PROPN
iajs-2946	140	21	̂	̂	NOUN
iajs-2946	140	22	�	�	NOUN
iajs-2946	140	23	𝛿∗)−	𝛿∗)−	PROPN
iajs-2946	140	24	δ(	δ(	PROPN
iajs-2946	140	25	�	�	PROPN
iajs-2946	140	26	̂	̂	NOUN
iajs-2946	140	27	�	�	NOUN
iajs-2946	140	28	𝛿,	𝛿,	NOUN
iajs-2946	140	29	�	�	PROPN
iajs-2946	140	30	̂	̂	NOUN
iajs-2946	140	31	�	�	NOUN
iajs-2946	140	32	𝛿	𝛿	NOUN
iajs-2946	140	33	)	)	PUNCT
iajs-2946	140	34	}	}	PUNCT
iajs-2946	140	35	]	]	PUNCT
iajs-2946	140	36	1	1	NUM
iajs-2946	140	37	2	2	NUM
iajs-2946	140	38	.	.	PUNCT
iajs-2946	140	39	(	(	PUNCT
iajs-2946	140	40	13	13	NUM
iajs-2946	140	41	)	)	SYM
iajs-2946	140	42	ii	ii	NOUN
iajs-2946	140	43	)	)	PUNCT
iajs-2946	140	44	bayesian	bayesian	NOUN
iajs-2946	140	45	estimation	estimation	NOUN
iajs-2946	140	46	for	for	ADP
iajs-2946	140	47	the	the	DET
iajs-2946	140	48	location	location	NOUN
iajs-2946	140	49	parameter	parameter	PROPN
iajs-2946	140	50	δ	δ	PROPN
iajs-2946	140	51	under	under	ADP
iajs-2946	140	52	precautionary	precautionary	ADJ
iajs-2946	140	53	loss	loss	NOUN
iajs-2946	140	54	function	function	NOUN
iajs-2946	140	55	similarly	similarly	ADV
iajs-2946	140	56	,	,	PUNCT
iajs-2946	140	57	𝛿	𝛿	PROPN
iajs-2946	140	58	can	can	AUX
iajs-2946	140	59	be	be	AUX
iajs-2946	140	60	estimated	estimate	VERB
iajs-2946	140	61	as	as	SCONJ
iajs-2946	140	62	follows	follow	VERB
iajs-2946	140	63	:	:	PUNCT
iajs-2946	140	64	assume	assume	VERB
iajs-2946	140	65	that	that	SCONJ
iajs-2946	140	66	,	,	PUNCT
iajs-2946	140	67	𝑢(𝛾	𝑢(𝛾	PRON
iajs-2946	140	68	,	,	PUNCT
iajs-2946	140	69	𝛿	𝛿	ADJ
iajs-2946	140	70	)	)	PUNCT
iajs-2946	140	71	=	=	SYM
iajs-2946	140	72	𝛿2	𝛿2	NOUN
iajs-2946	140	73	.	.	PUNCT
iajs-2946	141	1	and	and	CCONJ
iajs-2946	141	2	therefore	therefore	ADV
iajs-2946	141	3	,	,	PUNCT
iajs-2946	141	4	𝛿𝛿	𝛿𝛿	PROPN
iajs-2946	141	5	∗(𝛾	∗(𝛾	PROPN
iajs-2946	141	6	,	,	PUNCT
iajs-2946	141	7	𝛿	𝛿	ADJ
iajs-2946	141	8	)	)	PUNCT
iajs-2946	141	9	=	=	SYM
iajs-2946	141	10	δ(γ	δ(γ	NOUN
iajs-2946	141	11	,	,	PUNCT
iajs-2946	141	12	δ	δ	PROPN
iajs-2946	141	13	)	)	PUNCT
iajs-2946	142	1	+	+	CCONJ
iajs-2946	142	2	ln	ln	ADJ
iajs-2946	142	3	𝛿2	𝛿2	NOUN
iajs-2946	142	4	𝑛	𝑛	PROPN
iajs-2946	142	5	.	.	PUNCT
iajs-2946	143	1	in	in	ADP
iajs-2946	143	2	order	order	NOUN
iajs-2946	143	3	to	to	PART
iajs-2946	143	4	compute	compute	VERB
iajs-2946	143	5	|∑𝛿𝑃𝐿	|∑𝛿𝑃𝐿	PROPN
iajs-2946	143	6	∗	∗	VERB
iajs-2946	143	7	|	|	ADV
iajs-2946	143	8	,	,	PUNCT
iajs-2946	143	9	we	we	PRON
iajs-2946	143	10	first	first	ADV
iajs-2946	143	11	get	get	VERB
iajs-2946	143	12	the	the	DET
iajs-2946	143	13	following	follow	VERB
iajs-2946	143	14	expressions	expression	NOUN
iajs-2946	143	15	:	:	PUNCT
iajs-2946	143	16	𝜕𝛿∗	𝜕𝛿∗	PROPN
iajs-2946	143	17	𝜕𝛾	𝜕𝛾	NOUN
iajs-2946	143	18	=	=	SYM
iajs-2946	143	19	1	1	NUM
iajs-2946	143	20	𝑛	𝑛	PROPN
iajs-2946	143	21	[	[	PUNCT
iajs-2946	143	22	−𝑛	−𝑛	NOUN
iajs-2946	143	23	𝛾	𝛾	ADP
iajs-2946	143	24	+	+	ADV
iajs-2946	143	25	∑	∑	PUNCT
iajs-2946	143	26	(	(	PUNCT
iajs-2946	143	27	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	143	28	𝑖=1	𝑖=1	PROPN
iajs-2946	143	29	𝛾2	𝛾2	NOUN
iajs-2946	143	30	–	–	PUNCT
iajs-2946	143	31	𝑐	𝑐	NOUN
iajs-2946	143	32	]	]	X
iajs-2946	143	33	,	,	PUNCT
iajs-2946	143	34	∂2𝛿∗	∂2𝛿∗	X
iajs-2946	143	35	∂γ2	∂γ2	PROPN
iajs-2946	143	36	=	=	SYM
iajs-2946	143	37	1	1	NUM
iajs-2946	143	38	𝑛	𝑛	PROPN
iajs-2946	143	39	[	[	PUNCT
iajs-2946	143	40	𝑛	𝑛	PROPN
iajs-2946	143	41	𝛾2	𝛾2	NOUN
iajs-2946	143	42	−	−	PROPN
iajs-2946	143	43	2	2	NUM
iajs-2946	143	44	∑	∑	PUNCT
iajs-2946	143	45	(	(	PUNCT
iajs-2946	143	46	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	143	47	𝑖=1	𝑖=1	PROPN
iajs-2946	143	48	𝛾3	𝛾3	PROPN
iajs-2946	143	49	]	]	PUNCT
iajs-2946	143	50	,	,	PUNCT
iajs-2946	143	51	𝜕𝛿∗	𝜕𝛿∗	ADJ
iajs-2946	143	52	𝜕𝛿	𝜕𝛿	NOUN
iajs-2946	143	53	=	=	SYM
iajs-2946	143	54	1	1	NUM
iajs-2946	143	55	𝑛	𝑛	PROPN
iajs-2946	143	56	[	[	PUNCT
iajs-2946	143	57	𝑛	𝑛	PRON
iajs-2946	143	58	𝛾	𝛾	NOUN
iajs-2946	143	59	+	+	CCONJ
iajs-2946	143	60	(	(	PUNCT
iajs-2946	143	61	𝑎−1	𝑎−1	PROPN
iajs-2946	143	62	)	)	PUNCT
iajs-2946	143	63	𝛿	𝛿	ADJ
iajs-2946	143	64	−	−	PROPN
iajs-2946	143	65	𝑏	𝑏	NOUN
iajs-2946	143	66	]	]	X
iajs-2946	143	67	+	+	CCONJ
iajs-2946	143	68	2	2	NUM
iajs-2946	143	69	𝑛𝛿	𝑛𝛿	NOUN
iajs-2946	143	70	,	,	PUNCT
iajs-2946	143	71	∂2𝛿∗	∂2𝛿∗	X
iajs-2946	143	72	∂δ2	∂δ2	NOUN
iajs-2946	143	73	=	=	SYM
iajs-2946	143	74	(	(	PUNCT
iajs-2946	143	75	1−𝑎	1−𝑎	X
iajs-2946	143	76	)	)	PUNCT
iajs-2946	143	77	𝑛𝛿2	𝑛𝛿2	VERB
iajs-2946	143	78	−	−	NUM
iajs-2946	143	79	2	2	NUM
iajs-2946	143	80	𝑛𝛿2	𝑛𝛿2	NOUN
iajs-2946	143	81	,	,	PUNCT
iajs-2946	143	82	∂2𝛿∗	∂2𝛿∗	NUM
iajs-2946	144	1	∂γ	∂γ	PROPN
iajs-2946	145	1	∂δ	∂δ	PROPN
iajs-2946	146	1	=	=	SYM
iajs-2946	147	1	−1	−1	NOUN
iajs-2946	147	2	𝛾2	𝛾2	NOUN
iajs-2946	147	3	,	,	PUNCT
iajs-2946	147	4	|∑𝛿𝑃𝐿	|∑𝛿𝑃𝐿	PROPN
iajs-2946	147	5	∗	∗	VERB
iajs-2946	147	6	|	|	ADV
iajs-2946	148	1	=	=	PRON
iajs-2946	149	1	[	[	PUNCT
iajs-2946	149	2	1	1	NUM
iajs-2946	149	3	𝑛	𝑛	PROPN
iajs-2946	149	4	[	[	PUNCT
iajs-2946	149	5	𝑛	𝑛	PROPN
iajs-2946	149	6	𝛾2	𝛾2	NOUN
iajs-2946	149	7	−	−	PROPN
iajs-2946	149	8	2	2	NUM
iajs-2946	149	9	∑	∑	PUNCT
iajs-2946	149	10	(	(	PUNCT
iajs-2946	149	11	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	149	12	𝑖=1	𝑖=1	PROPN
iajs-2946	149	13	𝛾3	𝛾3	PROPN
iajs-2946	149	14	]	]	PUNCT
iajs-2946	149	15	(	(	PUNCT
iajs-2946	150	1	1−𝑎)−2	1−𝑎)−2	NUM
iajs-2946	150	2	𝑛𝛿2	𝑛𝛿2	VERB
iajs-2946	150	3	−	−	PROPN
iajs-2946	150	4	1	1	NUM
iajs-2946	150	5	𝛾4]−1	𝛾4]−1	NOUN
iajs-2946	150	6	.	.	PUNCT
iajs-2946	150	7	thus	thus	ADV
iajs-2946	150	8	,	,	PUNCT
iajs-2946	150	9	𝛿𝑃	𝛿𝑃	VERB
iajs-2946	150	10	=[	=[	NOUN
iajs-2946	150	11	√	√	ADP
iajs-2946	150	12	|∑𝛿𝑃𝐿	|∑𝛿𝑃𝐿	PROPN
iajs-2946	150	13	∗	∗	NOUN
iajs-2946	150	14	|	|	ADV
iajs-2946	150	15	│	│	VERB
iajs-2946	150	16	∑	∑	ADJ
iajs-2946	150	17	│	│	ADJ
iajs-2946	150	18	𝑒[𝑛{𝛿𝛿	𝑒[𝑛{𝛿𝛿	NOUN
iajs-2946	150	19	∗	∗	NOUN
iajs-2946	150	20	(	(	PUNCT
iajs-2946	150	21	�	�	NOUN
iajs-2946	150	22	̂	̂	NOUN
iajs-2946	150	23	�	�	NOUN
iajs-2946	150	24	𝛿∗	𝛿∗	PROPN
iajs-2946	150	25	,	,	PUNCT
iajs-2946	150	26	�	�	PROPN
iajs-2946	150	27	̂	̂	NOUN
iajs-2946	150	28	�	�	NOUN
iajs-2946	150	29	𝛿∗)−	𝛿∗)−	PROPN
iajs-2946	150	30	δ(	δ(	PROPN
iajs-2946	150	31	�	�	PROPN
iajs-2946	150	32	̂	̂	NOUN
iajs-2946	150	33	�	�	NOUN
iajs-2946	150	34	𝛿,	𝛿,	NOUN
iajs-2946	150	35	�	�	PROPN
iajs-2946	150	36	̂	̂	NOUN
iajs-2946	150	37	�	�	NOUN
iajs-2946	150	38	𝛿	𝛿	NOUN
iajs-2946	150	39	)	)	PUNCT
iajs-2946	150	40	}	}	PUNCT
iajs-2946	150	41	]	]	PUNCT
iajs-2946	150	42	1	1	NUM
iajs-2946	150	43	2	2	NUM
iajs-2946	150	44	.	.	PUNCT
iajs-2946	151	1	(	(	PUNCT
iajs-2946	151	2	14	14	NUM
iajs-2946	151	3	)	)	PUNCT
iajs-2946	151	4	3.3	3.3	NUM
iajs-2946	151	5	bayes	bayes	PROPN
iajs-2946	151	6	estimator	estimator	NOUN
iajs-2946	151	7	under	under	ADP
iajs-2946	151	8	entropy	entropy	PROPN
iajs-2946	151	9	loss	loss	NOUN
iajs-2946	151	10	function	function	NOUN
iajs-2946	151	11	the	the	DET
iajs-2946	151	12	entropy	entropy	NOUN
iajs-2946	151	13	loss	loss	NOUN
iajs-2946	151	14	function	function	NOUN
iajs-2946	151	15	was	be	AUX
iajs-2946	151	16	originally	originally	ADV
iajs-2946	151	17	proposed	propose	VERB
iajs-2946	151	18	by	by	ADP
iajs-2946	151	19	galabria	galabria	NOUN
iajs-2946	151	20	and	and	CCONJ
iajs-2946	151	21	pulcini	pulcini	PROPN
iajs-2946	151	22	(	(	PUNCT
iajs-2946	151	23	1994	1994	NUM
iajs-2946	151	24	)	)	PUNCT
iajs-2946	151	25	.	.	PUNCT
iajs-2946	152	1	it	it	PRON
iajs-2946	152	2	is	be	AUX
iajs-2946	152	3	derived	derive	VERB
iajs-2946	152	4	from	from	ADP
iajs-2946	152	5	the	the	DET
iajs-2946	152	6	linex	linex	ADJ
iajs-2946	152	7	loss	loss	NOUN
iajs-2946	152	8	function	function	NOUN
iajs-2946	152	9	and	and	CCONJ
iajs-2946	152	10	defined	define	VERB
iajs-2946	152	11	as	as	ADP
iajs-2946	152	12	[	[	X
iajs-2946	152	13	7	7	NUM
iajs-2946	152	14	]	]	X
iajs-2946	152	15	:	:	PUNCT
iajs-2946	152	16	l(θ̂	l(θ̂	PROPN
iajs-2946	152	17	,	,	PUNCT
iajs-2946	152	18	θ	θ	PROPN
iajs-2946	152	19	)	)	PUNCT
iajs-2946	152	20	∝	∝	PROPN
iajs-2946	152	21	(	(	PUNCT
iajs-2946	152	22	θ̂	θ̂	NUM
iajs-2946	152	23	θ	θ	PROPN
iajs-2946	152	24	)	)	PUNCT
iajs-2946	152	25	𝑝	𝑝	PROPN
iajs-2946	152	26	−	−	PROPN
iajs-2946	152	27	𝑝	𝑝	PROPN
iajs-2946	152	28	ln	ln	NOUN
iajs-2946	153	1	(	(	PUNCT
iajs-2946	153	2	θ̂	θ̂	NUM
iajs-2946	153	3	θ	θ	PROPN
iajs-2946	153	4	)	)	PUNCT
iajs-2946	154	1	−	−	PROPN
iajs-2946	155	1	1	1	X
iajs-2946	155	2	.	.	PUNCT
iajs-2946	156	1	we	we	PRON
iajs-2946	156	2	’ll	’ll	AUX
iajs-2946	156	3	assume	assume	VERB
iajs-2946	156	4	that	that	SCONJ
iajs-2946	156	5	𝑝	𝑝	X
iajs-2946	156	6	=	=	SYM
iajs-2946	156	7	1	1	NUM
iajs-2946	156	8	.	.	PUNCT
iajs-2946	156	9	based	base	VERB
iajs-2946	156	10	on	on	ADP
iajs-2946	156	11	entropy	entropy	PROPN
iajs-2946	156	12	loss	loss	NOUN
iajs-2946	156	13	function	function	NOUN
iajs-2946	156	14	,	,	PUNCT
iajs-2946	156	15	the	the	DET
iajs-2946	156	16	risk	risk	NOUN
iajs-2946	156	17	function	function	NOUN
iajs-2946	156	18	re(θ̂	re(θ̂	NOUN
iajs-2946	156	19	,	,	PUNCT
iajs-2946	156	20	θ	θ	NOUN
iajs-2946	156	21	)	)	PUNCT
iajs-2946	156	22	can	can	AUX
iajs-2946	156	23	be	be	AUX
iajs-2946	156	24	derived	derive	VERB
iajs-2946	156	25	as	as	SCONJ
iajs-2946	156	26	follows	follow	VERB
iajs-2946	156	27	:	:	PUNCT
iajs-2946	156	28	re(θ̂	re(θ̂	NUM
iajs-2946	156	29	,	,	PUNCT
iajs-2946	156	30	θ	θ	NOUN
iajs-2946	156	31	)	)	PUNCT
iajs-2946	156	32	=	=	SYM
iajs-2946	156	33	e[l(θ̂	e[l(θ̂	PROPN
iajs-2946	156	34	,	,	PUNCT
iajs-2946	156	35	θ	θ	PROPN
iajs-2946	156	36	)	)	PUNCT
iajs-2946	156	37	]	]	PUNCT
iajs-2946	157	1	=	=	SYM
iajs-2946	157	2	∫	∫	PROPN
iajs-2946	157	3	l(θ̂	l(θ̂	PROPN
iajs-2946	157	4	,	,	PUNCT
iajs-2946	157	5	θ	θ	PROPN
iajs-2946	157	6	)	)	PUNCT
iajs-2946	157	7	h(θ|x)dγ	h(θ|x)dγ	VERB
iajs-2946	157	8	∞	∞	PROPN
iajs-2946	157	9	0	0	NUM
iajs-2946	157	10	re(θ̂	re(θ̂	NUM
iajs-2946	157	11	,	,	PUNCT
iajs-2946	157	12	θ	θ	NOUN
iajs-2946	157	13	)	)	PUNCT
iajs-2946	157	14	=	=	SYM
iajs-2946	157	15	∫	∫	PROPN
iajs-2946	157	16	(	(	PUNCT
iajs-2946	157	17	(	(	PUNCT
iajs-2946	157	18	θ̂	θ̂	NUM
iajs-2946	157	19	θ	θ	PROPN
iajs-2946	157	20	)	)	PUNCT
iajs-2946	158	1	−	−	PROPN
iajs-2946	159	1	ln	ln	INTJ
iajs-2946	159	2	(	(	PUNCT
iajs-2946	159	3	θ̂	θ̂	NUM
iajs-2946	159	4	θ	θ	PROPN
iajs-2946	159	5	)	)	PUNCT
iajs-2946	160	1	−	−	ADP
iajs-2946	160	2	1	1	NUM
iajs-2946	160	3	)	)	PUNCT
iajs-2946	160	4	∞	∞	NOUN
iajs-2946	160	5	0	0	NUM
iajs-2946	161	1	h(θ|x)dθ	h(θ|x)dθ	NOUN
iajs-2946	161	2	.	.	PUNCT
iajs-2946	162	1	taking	take	VERB
iajs-2946	162	2	the	the	DET
iajs-2946	162	3	partial	partial	ADJ
iajs-2946	162	4	derivative	derivative	NOUN
iajs-2946	162	5	for	for	ADP
iajs-2946	162	6	re(θ̂	re(θ̂	NUM
iajs-2946	162	7	,	,	PUNCT
iajs-2946	162	8	θ	θ	NOUN
iajs-2946	162	9	)	)	PUNCT
iajs-2946	162	10	with	with	ADP
iajs-2946	162	11	respect	respect	NOUN
iajs-2946	162	12	to	to	ADP
iajs-2946	162	13	θ̂	θ̂	PROPN
iajs-2946	162	14	yields	yield	NOUN
iajs-2946	162	15	,	,	PUNCT
iajs-2946	162	16	∂re(θ̂,θ	∂re(θ̂,θ	NOUN
iajs-2946	162	17	)	)	PUNCT
iajs-2946	162	18	∂θ̂	∂θ̂	PUNCT
iajs-2946	163	1	=	=	PUNCT
iajs-2946	163	2	∫	∫	PROPN
iajs-2946	163	3	(	(	PUNCT
iajs-2946	163	4	1	1	NUM
iajs-2946	163	5	θ	θ	NOUN
iajs-2946	163	6	)	)	PUNCT
iajs-2946	163	7	h(θ|x)dγ	h(θ|x)dγ	PROPN
iajs-2946	163	8	−	−	PROPN
iajs-2946	163	9	∫	∫	PROPN
iajs-2946	163	10	1	1	NUM
iajs-2946	163	11	θ̂	θ̂	VERB
iajs-2946	163	12	∞	∞	PROPN
iajs-2946	163	13	0	0	NUM
iajs-2946	164	1	∞	∞	NUM
iajs-2946	164	2	0	0	NUM
iajs-2946	164	3	h(θ|x)dγ	h(θ|x)dγ	PROPN
iajs-2946	164	4	.	.	PUNCT
iajs-2946	165	1	let	let	VERB
iajs-2946	165	2	∂re(θ̂,θ	∂re(θ̂,θ	NOUN
iajs-2946	165	3	)	)	PUNCT
iajs-2946	165	4	∂θ̂	∂θ̂	NOUN
iajs-2946	166	1	=	=	PUNCT
iajs-2946	166	2	0	0	NUM
iajs-2946	166	3	,	,	PUNCT
iajs-2946	166	4	yields	yield	NOUN
iajs-2946	166	5	e	e	X
iajs-2946	166	6	(	(	PUNCT
iajs-2946	166	7	1	1	NUM
iajs-2946	166	8	θ	θ	PROPN
iajs-2946	166	9	|x	|x	NOUN
iajs-2946	166	10	)	)	PUNCT
iajs-2946	166	11	−	−	PROPN
iajs-2946	166	12	1	1	NUM
iajs-2946	166	13	θ̂	θ̂	VERB
iajs-2946	166	14	=	=	NOUN
iajs-2946	166	15	0	0	X
iajs-2946	166	16	.	.	PUNCT
iajs-2946	167	1	hence	hence	ADV
iajs-2946	167	2	,	,	PUNCT
iajs-2946	167	3	the	the	DET
iajs-2946	167	4	bayesian	bayesian	NOUN
iajs-2946	167	5	estimator	estimator	NOUN
iajs-2946	167	6	under	under	ADP
iajs-2946	167	7	entropy	entropy	PROPN
iajs-2946	167	8	loss	loss	NOUN
iajs-2946	167	9	function	function	NOUN
iajs-2946	167	10	will	will	AUX
iajs-2946	167	11	be	be	AUX
iajs-2946	167	12	as	as	SCONJ
iajs-2946	167	13	follows	follow	VERB
iajs-2946	167	14	:	:	PUNCT
iajs-2946	167	15	ihjpas	ihjpas	PROPN
iajs-2946	167	16	.	.	PUNCT
iajs-2946	168	1	36(2)2023	36(2)2023	NUM
iajs-2946	168	2	296	296	NUM
iajs-2946	168	3	θ̂e	θ̂e	NOUN
iajs-2946	168	4	=	=	PUNCT
iajs-2946	168	5	[	[	X
iajs-2946	168	6	e(θ−1|x)]−1	e(θ−1|x)]−1	X
iajs-2946	168	7	.	.	PUNCT
iajs-2946	169	1	i	i	NOUN
iajs-2946	169	2	)	)	PUNCT
iajs-2946	169	3	bayesian	bayesian	NOUN
iajs-2946	169	4	estimation	estimation	NOUN
iajs-2946	169	5	for	for	ADP
iajs-2946	169	6	γ	γ	NOUN
iajs-2946	169	7	under	under	ADP
iajs-2946	169	8	entropy	entropy	NOUN
iajs-2946	169	9	loss	loss	NOUN
iajs-2946	169	10	function	function	NOUN
iajs-2946	169	11	bayesian	bayesian	NOUN
iajs-2946	169	12	estimation	estimation	NOUN
iajs-2946	169	13	for	for	ADP
iajs-2946	169	14	γ	γ	NOUN
iajs-2946	169	15	under	under	ADP
iajs-2946	169	16	entropy	entropy	NOUN
iajs-2946	169	17	loss	loss	NOUN
iajs-2946	169	18	function	function	NOUN
iajs-2946	169	19	can	can	AUX
iajs-2946	169	20	be	be	AUX
iajs-2946	169	21	obtained	obtain	VERB
iajs-2946	169	22	as	as	ADP
iajs-2946	169	23	follows	follow	VERB
iajs-2946	169	24	:	:	PUNCT
iajs-2946	169	25	let	let	VERB
iajs-2946	169	26	𝑢(𝛾	𝑢(𝛾	PRON
iajs-2946	169	27	,	,	PUNCT
iajs-2946	169	28	𝛿	𝛿	ADJ
iajs-2946	169	29	)	)	PUNCT
iajs-2946	169	30	=	=	SYM
iajs-2946	169	31	1	1	NUM
iajs-2946	169	32	𝛾	𝛾	NOUN
iajs-2946	169	33	.	.	PUNCT
iajs-2946	170	1	and	and	CCONJ
iajs-2946	170	2	therefore	therefore	ADV
iajs-2946	170	3	,	,	PUNCT
iajs-2946	170	4	𝛿𝛾	𝛿𝛾	PROPN
iajs-2946	170	5	∗(𝛾	∗(𝛾	PROPN
iajs-2946	170	6	,	,	PUNCT
iajs-2946	170	7	𝛿	𝛿	ADJ
iajs-2946	170	8	)	)	PUNCT
iajs-2946	170	9	=	=	SYM
iajs-2946	170	10	δ(γ	δ(γ	NOUN
iajs-2946	170	11	,	,	PUNCT
iajs-2946	170	12	δ	δ	NOUN
iajs-2946	170	13	)	)	PUNCT
iajs-2946	171	1	+	+	CCONJ
iajs-2946	171	2	ln	ln	ADJ
iajs-2946	171	3	1	1	NUM
iajs-2946	171	4	𝛾	𝛾	NOUN
iajs-2946	171	5	𝑛	𝑛	PROPN
iajs-2946	171	6	.	.	PUNCT
iajs-2946	172	1	in	in	ADP
iajs-2946	172	2	order	order	NOUN
iajs-2946	172	3	to	to	PART
iajs-2946	172	4	compute	compute	VERB
iajs-2946	172	5	|∑𝛾𝐸𝐿	|∑𝛾𝐸𝐿	NOUN
iajs-2946	172	6	∗	∗	NOUN
iajs-2946	172	7	|	|	NOUN
iajs-2946	172	8	,	,	PUNCT
iajs-2946	172	9	we	we	PRON
iajs-2946	172	10	first	first	ADV
iajs-2946	172	11	get	get	VERB
iajs-2946	172	12	the	the	DET
iajs-2946	172	13	following	follow	VERB
iajs-2946	172	14	expressions	expression	NOUN
iajs-2946	172	15	:	:	PUNCT
iajs-2946	172	16	𝜕𝛿∗	𝜕𝛿∗	PROPN
iajs-2946	172	17	𝜕𝛾	𝜕𝛾	NOUN
iajs-2946	172	18	=	=	SYM
iajs-2946	172	19	1	1	NUM
iajs-2946	172	20	𝑛	𝑛	PROPN
iajs-2946	172	21	[	[	PUNCT
iajs-2946	172	22	−𝑛	−𝑛	NOUN
iajs-2946	172	23	𝛾	𝛾	ADP
iajs-2946	172	24	+	+	ADV
iajs-2946	172	25	∑	∑	PUNCT
iajs-2946	172	26	(	(	PUNCT
iajs-2946	172	27	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	172	28	𝑖=1	𝑖=1	PROPN
iajs-2946	172	29	𝛾2	𝛾2	VERB
iajs-2946	172	30	–	–	PUNCT
iajs-2946	172	31	𝑐	𝑐	NOUN
iajs-2946	172	32	]	]	PUNCT
iajs-2946	172	33	1	1	NUM
iajs-2946	172	34	𝑛𝛾	𝑛𝛾	ADJ
iajs-2946	172	35	,	,	PUNCT
iajs-2946	172	36	∂2𝛿∗	∂2𝛿∗	X
iajs-2946	172	37	∂γ2	∂γ2	PROPN
iajs-2946	172	38	=	=	SYM
iajs-2946	172	39	1	1	NUM
iajs-2946	172	40	𝑛	𝑛	PROPN
iajs-2946	172	41	[	[	PUNCT
iajs-2946	172	42	𝑛	𝑛	PROPN
iajs-2946	172	43	𝛾2	𝛾2	NOUN
iajs-2946	172	44	−	−	PROPN
iajs-2946	172	45	2	2	NUM
iajs-2946	172	46	∑	∑	PUNCT
iajs-2946	172	47	(	(	PUNCT
iajs-2946	172	48	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	172	49	𝑖=1	𝑖=1	PROPN
iajs-2946	172	50	𝛾3	𝛾3	NOUN
iajs-2946	172	51	]	]	PUNCT
iajs-2946	172	52	+	+	CCONJ
iajs-2946	172	53	1	1	NUM
iajs-2946	172	54	𝑛𝛾2	𝑛𝛾2	NOUN
iajs-2946	172	55	,	,	PUNCT
iajs-2946	172	56	𝜕𝛿∗	𝜕𝛿∗	ADJ
iajs-2946	172	57	𝜕𝛿	𝜕𝛿	NOUN
iajs-2946	172	58	=	=	SYM
iajs-2946	172	59	1	1	NUM
iajs-2946	172	60	𝑛	𝑛	PROPN
iajs-2946	172	61	[	[	PUNCT
iajs-2946	172	62	𝑛	𝑛	PRON
iajs-2946	172	63	𝛾	𝛾	NOUN
iajs-2946	172	64	+	+	CCONJ
iajs-2946	172	65	(	(	PUNCT
iajs-2946	172	66	𝑎−1	𝑎−1	PROPN
iajs-2946	172	67	)	)	PUNCT
iajs-2946	172	68	𝛿	𝛿	ADJ
iajs-2946	172	69	−	−	PROPN
iajs-2946	172	70	𝑏	𝑏	NOUN
iajs-2946	172	71	]	]	PUNCT
iajs-2946	172	72	,	,	PUNCT
iajs-2946	172	73	∂2𝛿∗	∂2𝛿∗	X
iajs-2946	172	74	∂δ2	∂δ2	NOUN
iajs-2946	173	1	=	=	SYM
iajs-2946	173	2	(	(	PUNCT
iajs-2946	173	3	1−𝑎	1−𝑎	X
iajs-2946	173	4	)	)	PUNCT
iajs-2946	173	5	𝑛𝛿2	𝑛𝛿2	VERB
iajs-2946	173	6	,	,	PUNCT
iajs-2946	173	7	∂2𝛿∗	∂2𝛿∗	NUM
iajs-2946	174	1	∂γ	∂γ	PROPN
iajs-2946	174	2	∂δ	∂δ	PROPN
iajs-2946	174	3	=	=	SYM
iajs-2946	174	4	−1	−1	NOUN
iajs-2946	174	5	𝛾2	𝛾2	VERB
iajs-2946	174	6	,	,	PUNCT
iajs-2946	174	7	|∑𝛾𝐸𝐿	|∑𝛾𝐸𝐿	NOUN
iajs-2946	174	8	∗	∗	NOUN
iajs-2946	174	9	|	|	NOUN
iajs-2946	175	1	=	=	PRON
iajs-2946	176	1	[	[	PUNCT
iajs-2946	176	2	1	1	NUM
iajs-2946	176	3	𝑛	𝑛	PROPN
iajs-2946	176	4	[	[	PUNCT
iajs-2946	176	5	𝑛	𝑛	PROPN
iajs-2946	176	6	𝛾2	𝛾2	NOUN
iajs-2946	176	7	−	−	PROPN
iajs-2946	176	8	2	2	NUM
iajs-2946	176	9	∑	∑	PUNCT
iajs-2946	176	10	(	(	PUNCT
iajs-2946	176	11	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	176	12	𝑖=1	𝑖=1	PROPN
iajs-2946	176	13	𝛾3	𝛾3	NOUN
iajs-2946	176	14	+	+	CCONJ
iajs-2946	176	15	1	1	NUM
iajs-2946	176	16	𝛾2	𝛾2	NOUN
iajs-2946	176	17	]	]	PUNCT
iajs-2946	176	18	(	(	PUNCT
iajs-2946	176	19	1−𝑎	1−𝑎	X
iajs-2946	176	20	)	)	PUNCT
iajs-2946	176	21	𝑛𝛿2	𝑛𝛿2	VERB
iajs-2946	176	22	−	−	PROPN
iajs-2946	176	23	1	1	NUM
iajs-2946	176	24	𝛾4]−1	𝛾4]−1	NOUN
iajs-2946	176	25	.	.	PUNCT
iajs-2946	177	1	then	then	ADV
iajs-2946	177	2	,	,	PUNCT
iajs-2946	177	3	𝛾𝐸=	𝛾𝐸=	PROPN
iajs-2946	178	1	[	[	X
iajs-2946	178	2	√	√	INTJ
iajs-2946	178	3	|∑𝛾𝐸𝐿	|∑𝛾𝐸𝐿	NOUN
iajs-2946	178	4	∗	∗	NOUN
iajs-2946	178	5	|	|	ADV
iajs-2946	178	6	│	│	VERB
iajs-2946	178	7	∑	∑	PROPN
iajs-2946	178	8	│	│	X
iajs-2946	178	9	𝑒[𝑛{𝛿𝛾	𝑒[𝑛{𝛿𝛾	VERB
iajs-2946	178	10	∗	∗	NOUN
iajs-2946	178	11	(	(	PUNCT
iajs-2946	178	12	�	�	NOUN
iajs-2946	178	13	̂	̂	NOUN
iajs-2946	178	14	�	�	NOUN
iajs-2946	178	15	𝛿∗	𝛿∗	PROPN
iajs-2946	178	16	,	,	PUNCT
iajs-2946	178	17	�	�	PROPN
iajs-2946	178	18	̂	̂	NOUN
iajs-2946	178	19	�	�	NOUN
iajs-2946	178	20	𝛿∗)−	𝛿∗)−	PROPN
iajs-2946	178	21	δ(	δ(	PROPN
iajs-2946	178	22	�	�	PROPN
iajs-2946	178	23	̂	̂	NOUN
iajs-2946	178	24	�	�	NOUN
iajs-2946	178	25	𝛿,	𝛿,	NOUN
iajs-2946	178	26	�	�	PROPN
iajs-2946	178	27	̂	̂	NOUN
iajs-2946	178	28	�	�	NOUN
iajs-2946	178	29	𝛿)}]]−1	𝛿)}]]−1	NOUN
iajs-2946	178	30	.	.	PUNCT
iajs-2946	179	1	(	(	PUNCT
iajs-2946	179	2	15	15	NUM
iajs-2946	179	3	)	)	PUNCT
iajs-2946	179	4	ii	ii	NOUN
iajs-2946	179	5	)	)	PUNCT
iajs-2946	179	6	bayesian	bayesian	NOUN
iajs-2946	179	7	estimation	estimation	NOUN
iajs-2946	179	8	for	for	ADP
iajs-2946	179	9	δ	δ	PROPN
iajs-2946	179	10	under	under	ADP
iajs-2946	179	11	entropy	entropy	NOUN
iajs-2946	179	12	loss	loss	NOUN
iajs-2946	179	13	function	function	NOUN
iajs-2946	179	14	bayesian	bayesian	NOUN
iajs-2946	179	15	estimation	estimation	NOUN
iajs-2946	179	16	for	for	ADP
iajs-2946	179	17	δ	δ	PROPN
iajs-2946	179	18	under	under	ADP
iajs-2946	179	19	entropy	entropy	NOUN
iajs-2946	179	20	loss	loss	NOUN
iajs-2946	179	21	function	function	NOUN
iajs-2946	179	22	can	can	AUX
iajs-2946	179	23	be	be	AUX
iajs-2946	179	24	obtained	obtain	VERB
iajs-2946	179	25	as	as	ADP
iajs-2946	179	26	follows	follow	VERB
iajs-2946	179	27	:	:	PUNCT
iajs-2946	179	28	let	let	VERB
iajs-2946	179	29	𝑢(𝛾	𝑢(𝛾	PRON
iajs-2946	179	30	,	,	PUNCT
iajs-2946	179	31	𝛿	𝛿	ADJ
iajs-2946	179	32	)	)	PUNCT
iajs-2946	179	33	=	=	SYM
iajs-2946	179	34	1	1	NUM
iajs-2946	179	35	𝛿	𝛿	NOUN
iajs-2946	179	36	.	.	PUNCT
iajs-2946	180	1	therefore	therefore	ADV
iajs-2946	180	2	,	,	PUNCT
iajs-2946	180	3	𝛿𝛿	𝛿𝛿	PROPN
iajs-2946	180	4	∗(𝛾	∗(𝛾	PROPN
iajs-2946	180	5	,	,	PUNCT
iajs-2946	180	6	𝛿	𝛿	ADJ
iajs-2946	180	7	)	)	PUNCT
iajs-2946	180	8	=	=	SYM
iajs-2946	180	9	δ(γ	δ(γ	NOUN
iajs-2946	180	10	,	,	PUNCT
iajs-2946	180	11	δ	δ	NOUN
iajs-2946	180	12	)	)	PUNCT
iajs-2946	181	1	+	+	X
iajs-2946	181	2	ln	ln	ADJ
iajs-2946	181	3	(	(	PUNCT
iajs-2946	181	4	1	1	NUM
iajs-2946	181	5	𝛿	𝛿	NOUN
iajs-2946	181	6	)	)	PUNCT
iajs-2946	181	7	𝑛	𝑛	NOUN
iajs-2946	181	8	.	.	PUNCT
iajs-2946	182	1	in	in	ADP
iajs-2946	182	2	order	order	NOUN
iajs-2946	182	3	to	to	PART
iajs-2946	182	4	compute	compute	VERB
iajs-2946	182	5	|∑𝛿𝐸𝐿	|∑𝛿𝐸𝐿	PROPN
iajs-2946	182	6	∗	∗	NOUN
iajs-2946	182	7	|	|	ADV
iajs-2946	182	8	,	,	PUNCT
iajs-2946	182	9	we	we	PRON
iajs-2946	182	10	first	first	ADV
iajs-2946	182	11	get	get	VERB
iajs-2946	182	12	the	the	DET
iajs-2946	182	13	following	follow	VERB
iajs-2946	182	14	expressions	expression	NOUN
iajs-2946	182	15	:	:	PUNCT
iajs-2946	182	16	𝜕𝛿∗	𝜕𝛿∗	PROPN
iajs-2946	182	17	𝜕𝛾	𝜕𝛾	NOUN
iajs-2946	182	18	=	=	SYM
iajs-2946	182	19	1	1	NUM
iajs-2946	182	20	𝑛	𝑛	PROPN
iajs-2946	182	21	[	[	PUNCT
iajs-2946	182	22	−𝑛	−𝑛	NOUN
iajs-2946	182	23	𝛾	𝛾	ADP
iajs-2946	182	24	+	+	ADV
iajs-2946	182	25	∑	∑	PUNCT
iajs-2946	182	26	(	(	PUNCT
iajs-2946	182	27	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	182	28	𝑖=1	𝑖=1	PROPN
iajs-2946	182	29	𝛾2	𝛾2	NOUN
iajs-2946	182	30	–	–	PUNCT
iajs-2946	182	31	𝑐	𝑐	NOUN
iajs-2946	182	32	]	]	X
iajs-2946	182	33	,	,	PUNCT
iajs-2946	182	34	∂2𝛿∗	∂2𝛿∗	X
iajs-2946	182	35	∂γ2	∂γ2	PROPN
iajs-2946	182	36	=	=	SYM
iajs-2946	182	37	1	1	NUM
iajs-2946	182	38	𝑛	𝑛	PROPN
iajs-2946	182	39	[	[	PUNCT
iajs-2946	182	40	𝑛	𝑛	PROPN
iajs-2946	182	41	𝛾2	𝛾2	NOUN
iajs-2946	182	42	−	−	PROPN
iajs-2946	182	43	2	2	NUM
iajs-2946	182	44	∑	∑	PUNCT
iajs-2946	182	45	(	(	PUNCT
iajs-2946	182	46	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	182	47	𝑖=1	𝑖=1	PROPN
iajs-2946	182	48	𝛾3	𝛾3	PROPN
iajs-2946	182	49	]	]	PUNCT
iajs-2946	182	50	,	,	PUNCT
iajs-2946	182	51	𝜕𝛿∗	𝜕𝛿∗	ADJ
iajs-2946	182	52	𝜕𝛿	𝜕𝛿	NOUN
iajs-2946	182	53	=	=	SYM
iajs-2946	182	54	1	1	NUM
iajs-2946	182	55	𝑛	𝑛	PROPN
iajs-2946	182	56	[	[	PUNCT
iajs-2946	182	57	𝑛	𝑛	PRON
iajs-2946	182	58	𝛾	𝛾	NOUN
iajs-2946	182	59	+	+	CCONJ
iajs-2946	182	60	(	(	PUNCT
iajs-2946	182	61	𝑎−1	𝑎−1	PROPN
iajs-2946	182	62	)	)	PUNCT
iajs-2946	182	63	𝛿	𝛿	ADJ
iajs-2946	182	64	−	−	PROPN
iajs-2946	182	65	𝑏	𝑏	NOUN
iajs-2946	182	66	]	]	SYM
iajs-2946	182	67	1	1	NUM
iajs-2946	182	68	𝑛𝛾	𝑛𝛾	ADJ
iajs-2946	182	69	,	,	PUNCT
iajs-2946	182	70	∂2𝛿∗	∂2𝛿∗	ADV
iajs-2946	182	71	∂δ2	∂δ2	NOUN
iajs-2946	183	1	=	=	SYM
iajs-2946	184	1	(	(	PUNCT
iajs-2946	184	2	1−𝑎	1−𝑎	X
iajs-2946	184	3	)	)	PUNCT
iajs-2946	184	4	𝑛𝛿2	𝑛𝛿2	VERB
iajs-2946	184	5	+	+	SYM
iajs-2946	184	6	1	1	NUM
iajs-2946	184	7	𝑛δ2	𝑛δ2	NOUN
iajs-2946	184	8	,	,	PUNCT
iajs-2946	184	9	∂2𝛿∗	∂2𝛿∗	NUM
iajs-2946	185	1	∂γ	∂γ	PROPN
iajs-2946	185	2	∂δ	∂δ	PROPN
iajs-2946	186	1	=	=	SYM
iajs-2946	186	2	−1	−1	NOUN
iajs-2946	186	3	𝛾2	𝛾2	NOUN
iajs-2946	186	4	,	,	PUNCT
iajs-2946	186	5	|∑𝛿𝐸𝐿	|∑𝛿𝐸𝐿	PROPN
iajs-2946	186	6	∗	∗	NOUN
iajs-2946	186	7	|	|	NOUN
iajs-2946	187	1	=	=	PRON
iajs-2946	188	1	[	[	PUNCT
iajs-2946	188	2	1	1	NUM
iajs-2946	188	3	𝑛	𝑛	PROPN
iajs-2946	188	4	[	[	PUNCT
iajs-2946	188	5	𝑛	𝑛	PROPN
iajs-2946	188	6	𝛾2	𝛾2	NOUN
iajs-2946	188	7	−	−	PROPN
iajs-2946	188	8	2	2	NUM
iajs-2946	188	9	∑	∑	PUNCT
iajs-2946	188	10	(	(	PUNCT
iajs-2946	188	11	𝑥𝑖−𝛿)𝑛	𝑥𝑖−𝛿)𝑛	NUM
iajs-2946	188	12	𝑖=1	𝑖=1	PROPN
iajs-2946	188	13	𝛾3	𝛾3	PROPN
iajs-2946	188	14	]	]	PUNCT
iajs-2946	188	15	(	(	PUNCT
iajs-2946	188	16	1−𝑎)+1	1−𝑎)+1	NUM
iajs-2946	188	17	𝑛𝛿2	𝑛𝛿2	VERB
iajs-2946	188	18	−	−	PROPN
iajs-2946	188	19	1	1	NUM
iajs-2946	188	20	𝛾4	𝛾4	NOUN
iajs-2946	188	21	]	]	PUNCT
iajs-2946	188	22	−1	−1	NOUN
iajs-2946	188	23	.	.	PUNCT
iajs-2946	189	1	then	then	ADV
iajs-2946	189	2	,	,	PUNCT
iajs-2946	189	3	δ̂𝐸=	δ̂𝐸=	NOUN
iajs-2946	189	4	[	[	X
iajs-2946	189	5	√	√	X
iajs-2946	189	6	|∑𝛿𝐸𝐿	|∑𝛿𝐸𝐿	PROPN
iajs-2946	189	7	∗	∗	NOUN
iajs-2946	189	8	|	|	ADV
iajs-2946	189	9	│	│	VERB
iajs-2946	189	10	∑	∑	ADJ
iajs-2946	189	11	│	│	ADJ
iajs-2946	189	12	𝑒[𝑛{𝛿𝛿	𝑒[𝑛{𝛿𝛿	NOUN
iajs-2946	189	13	∗	∗	NOUN
iajs-2946	189	14	(	(	PUNCT
iajs-2946	189	15	�	�	NOUN
iajs-2946	189	16	̂	̂	NOUN
iajs-2946	189	17	�	�	NOUN
iajs-2946	189	18	𝛿∗	𝛿∗	PROPN
iajs-2946	189	19	,	,	PUNCT
iajs-2946	189	20	�	�	PROPN
iajs-2946	189	21	̂	̂	NOUN
iajs-2946	189	22	�	�	NOUN
iajs-2946	189	23	𝛿∗)−	𝛿∗)−	PROPN
iajs-2946	189	24	δ(	δ(	PROPN
iajs-2946	189	25	�	�	PROPN
iajs-2946	189	26	̂	̂	NOUN
iajs-2946	189	27	�	�	NOUN
iajs-2946	189	28	𝛿,	𝛿,	NOUN
iajs-2946	189	29	�	�	PROPN
iajs-2946	189	30	̂	̂	NOUN
iajs-2946	189	31	�	�	NOUN
iajs-2946	189	32	𝛿)}]]−1	𝛿)}]]−1	NOUN
iajs-2946	189	33	.	.	PUNCT
iajs-2946	190	1	(	(	PUNCT
iajs-2946	190	2	16	16	NUM
iajs-2946	190	3	)	)	PUNCT
iajs-2946	190	4	ihjpas	ihjpa	NOUN
iajs-2946	190	5	.	.	PUNCT
iajs-2946	191	1	36(2)2023	36(2)2023	NUM
iajs-2946	191	2	297	297	NUM
iajs-2946	191	3	simulation	simulation	NOUN
iajs-2946	191	4	study	study	NOUN
iajs-2946	191	5	in	in	ADP
iajs-2946	191	6	this	this	DET
iajs-2946	191	7	section	section	NOUN
iajs-2946	191	8	,	,	PUNCT
iajs-2946	191	9	monte	monte	PROPN
iajs-2946	191	10	-	-	PUNCT
iajs-2946	191	11	carlo	carlo	PROPN
iajs-2946	191	12	simulation	simulation	NOUN
iajs-2946	191	13	is	be	AUX
iajs-2946	191	14	employed	employ	VERB
iajs-2946	191	15	to	to	PART
iajs-2946	191	16	compare	compare	VERB
iajs-2946	191	17	the	the	DET
iajs-2946	191	18	performance	performance	NOUN
iajs-2946	191	19	of	of	ADP
iajs-2946	191	20	five	five	NUM
iajs-2946	191	21	different	different	ADJ
iajs-2946	191	22	estimates	estimate	NOUN
iajs-2946	191	23	(	(	PUNCT
iajs-2946	191	24	maximum	maximum	ADJ
iajs-2946	191	25	likelihood	likelihood	NOUN
iajs-2946	191	26	estimator	estimator	NOUN
iajs-2946	191	27	,	,	PUNCT
iajs-2946	191	28	bayes	bayes	PROPN
iajs-2946	191	29	estimator	estimator	NOUN
iajs-2946	191	30	under	under	ADP
iajs-2946	191	31	squared	square	VERB
iajs-2946	191	32	error	error	NOUN
iajs-2946	191	33	loss	loss	NOUN
iajs-2946	191	34	function	function	NOUN
iajs-2946	191	35	,	,	PUNCT
iajs-2946	191	36	bayes	bayes	PROPN
iajs-2946	191	37	estimator	estimator	NOUN
iajs-2946	191	38	under	under	ADP
iajs-2946	191	39	entropy	entropy	PROPN
iajs-2946	191	40	loss	loss	NOUN
iajs-2946	191	41	function	function	NOUN
iajs-2946	191	42	,	,	PUNCT
iajs-2946	191	43	bayes	bayes	PROPN
iajs-2946	191	44	estimator	estimator	NOUN
iajs-2946	191	45	under	under	ADP
iajs-2946	191	46	precautionary	precautionary	ADJ
iajs-2946	191	47	loss	loss	NOUN
iajs-2946	191	48	function	function	NOUN
iajs-2946	191	49	)	)	PUNCT
iajs-2946	191	50	for	for	ADP
iajs-2946	191	51	unknown	unknown	ADJ
iajs-2946	191	52	scale	scale	NOUN
iajs-2946	191	53	and	and	CCONJ
iajs-2946	191	54	location	location	NOUN
iajs-2946	191	55	parameters	parameter	NOUN
iajs-2946	191	56	.	.	PUNCT
iajs-2946	192	1	the	the	DET
iajs-2946	192	2	comparison	comparison	NOUN
iajs-2946	192	3	is	be	AUX
iajs-2946	192	4	made	make	VERB
iajs-2946	192	5	on	on	ADP
iajs-2946	192	6	the	the	DET
iajs-2946	192	7	basis	basis	NOUN
iajs-2946	192	8	of	of	ADP
iajs-2946	192	9	the	the	DET
iajs-2946	192	10	mean	mean	ADJ
iajs-2946	192	11	squared	square	VERB
iajs-2946	192	12	error	error	NOUN
iajs-2946	192	13	(	(	PUNCT
iajs-2946	192	14	mse	mse	PROPN
iajs-2946	192	15	’s	’s	PART
iajs-2946	192	16	)	)	PUNCT
iajs-2946	192	17	,	,	PUNCT
iajs-2946	192	18	which	which	PRON
iajs-2946	192	19	is	be	AUX
iajs-2946	192	20	defined	define	VERB
iajs-2946	192	21	as	as	SCONJ
iajs-2946	192	22	follows	follow	VERB
iajs-2946	192	23	:	:	PUNCT
iajs-2946	192	24	mse(𝜃	mse(𝜃	X
iajs-2946	192	25	)	)	PUNCT
iajs-2946	192	26	=	=	SYM
iajs-2946	192	27	∑	∑	PROPN
iajs-2946	192	28	(	(	PUNCT
iajs-2946	192	29	�	�	PROPN
iajs-2946	192	30	̂	̂	VERB
iajs-2946	192	31	�	�	PROPN
iajs-2946	192	32	𝑖−𝜃)2𝑅	𝑖−𝜃)2𝑅	NOUN
iajs-2946	192	33	𝑖=1	𝑖=1	PROPN
iajs-2946	192	34	𝑅	𝑅	PROPN
iajs-2946	192	35	.	.	PUNCT
iajs-2946	193	1	where	where	SCONJ
iajs-2946	193	2	r	r	NOUN
iajs-2946	193	3	is	be	AUX
iajs-2946	193	4	the	the	DET
iajs-2946	193	5	number	number	NOUN
iajs-2946	193	6	of	of	ADP
iajs-2946	193	7	replications	replication	NOUN
iajs-2946	193	8	(	(	PUNCT
iajs-2946	193	9	generated	generate	VERB
iajs-2946	193	10	samples	sample	NOUN
iajs-2946	193	11	)	)	PUNCT
iajs-2946	193	12	.	.	PUNCT
iajs-2946	194	1	in	in	ADP
iajs-2946	194	2	this	this	DET
iajs-2946	194	3	paper	paper	NOUN
iajs-2946	194	4	,	,	PUNCT
iajs-2946	194	5	r	r	NOUN
iajs-2946	194	6	=	=	SYM
iajs-2946	194	7	5000	5000	NUM
iajs-2946	194	8	sample	sample	NOUN
iajs-2946	194	9	of	of	ADP
iajs-2946	194	10	size	size	NOUN
iajs-2946	194	11	n	n	NOUN
iajs-2946	194	12	=	=	SYM
iajs-2946	194	13	10	10	NUM
iajs-2946	194	14	,	,	PUNCT
iajs-2946	194	15	30	30	NUM
iajs-2946	194	16	,	,	PUNCT
iajs-2946	194	17	50	50	NUM
iajs-2946	194	18	,	,	PUNCT
iajs-2946	194	19	and	and	CCONJ
iajs-2946	194	20	100	100	NUM
iajs-2946	194	21	is	be	AUX
iajs-2946	194	22	to	to	PART
iajs-2946	194	23	represent	represent	VERB
iajs-2946	194	24	small	small	ADJ
iajs-2946	194	25	,	,	PUNCT
iajs-2946	194	26	moderate	moderate	ADJ
iajs-2946	194	27	,	,	PUNCT
iajs-2946	194	28	and	and	CCONJ
iajs-2946	194	29	large	large	ADJ
iajs-2946	194	30	sample	sample	NOUN
iajs-2946	194	31	sizes	size	NOUN
iajs-2946	194	32	from	from	ADP
iajs-2946	194	33	an	an	DET
iajs-2946	194	34	exponential	exponential	ADJ
iajs-2946	194	35	distribution	distribution	NOUN
iajs-2946	194	36	with	with	ADP
iajs-2946	194	37	γ	γ	X
iajs-2946	194	38	=	=	SYM
iajs-2946	194	39	0.5	0.5	NUM
iajs-2946	194	40	,	,	PUNCT
iajs-2946	194	41	1.5	1.5	NUM
iajs-2946	194	42	and	and	CCONJ
iajs-2946	194	43	δ	δ	PROPN
iajs-2946	194	44	=	=	PUNCT
iajs-2946	194	45	0.8	0.8	NUM
iajs-2946	194	46	,	,	PUNCT
iajs-2946	194	47	2	2	NUM
iajs-2946	194	48	.	.	PUNCT
iajs-2946	195	1	the	the	DET
iajs-2946	195	2	parameter	parameter	NOUN
iajs-2946	195	3	for	for	ADP
iajs-2946	195	4	the	the	DET
iajs-2946	195	5	prior	prior	ADJ
iajs-2946	195	6	distribution	distribution	NOUN
iajs-2946	195	7	of	of	ADP
iajs-2946	195	8	γ	γ	PROPN
iajs-2946	195	9	is	be	AUX
iajs-2946	195	10	chosen	choose	VERB
iajs-2946	195	11	as	as	ADP
iajs-2946	195	12	c	c	NOUN
iajs-2946	195	13	=	=	SYM
iajs-2946	195	14	0.4	0.4	NUM
iajs-2946	195	15	and	and	CCONJ
iajs-2946	195	16	the	the	DET
iajs-2946	195	17	two	two	NUM
iajs-2946	195	18	parameters	parameter	NOUN
iajs-2946	195	19	of	of	ADP
iajs-2946	195	20	the	the	DET
iajs-2946	195	21	gamma	gamma	NOUN
iajs-2946	195	22	prior	prior	ADV
iajs-2946	195	23	of	of	ADP
iajs-2946	195	24	δ	δ	PROPN
iajs-2946	195	25	are	be	AUX
iajs-2946	195	26	assumed	assume	VERB
iajs-2946	195	27	as	as	ADP
iajs-2946	195	28	a	a	DET
iajs-2946	195	29	=	=	SYM
iajs-2946	195	30	0.3	0.3	NUM
iajs-2946	195	31	and	and	CCONJ
iajs-2946	195	32	b	b	X
iajs-2946	195	33	=	=	SYM
iajs-2946	195	34	0.6	0.6	NUM
iajs-2946	195	35	discussion	discussion	NOUN
iajs-2946	195	36	the	the	DET
iajs-2946	195	37	results	result	NOUN
iajs-2946	195	38	are	be	AUX
iajs-2946	195	39	summarized	summarize	VERB
iajs-2946	195	40	and	and	CCONJ
iajs-2946	195	41	tabulated	tabulate	VERB
iajs-2946	195	42	in	in	ADP
iajs-2946	195	43	tables	table	NOUN
iajs-2946	195	44	(	(	PUNCT
iajs-2946	195	45	1	1	NUM
iajs-2946	195	46	-	-	SYM
iajs-2946	195	47	8)	8)	NUM
iajs-2946	195	48	which	which	PRON
iajs-2946	195	49	contain	contain	VERB
iajs-2946	195	50	the	the	DET
iajs-2946	195	51	expected	expect	VERB
iajs-2946	195	52	values	value	NOUN
iajs-2946	195	53	and	and	CCONJ
iajs-2946	195	54	(	(	PUNCT
iajs-2946	195	55	mses	ms	NOUN
iajs-2946	195	56	)	)	PUNCT
iajs-2946	195	57	for	for	ADP
iajs-2946	195	58	estimating	estimate	VERB
iajs-2946	195	59	γ	γ	PROPN
iajs-2946	195	60	and	and	CCONJ
iajs-2946	195	61	δ	δ	PROPN
iajs-2946	195	62	,	,	PUNCT
iajs-2946	195	63	and	and	CCONJ
iajs-2946	195	64	we	we	PRON
iajs-2946	195	65	have	have	AUX
iajs-2946	195	66	observed	observe	VERB
iajs-2946	195	67	that	that	SCONJ
iajs-2946	195	68	:	:	PUNCT
iajs-2946	195	69	1	1	X
iajs-2946	195	70	.	.	X
iajs-2946	195	71	the	the	DET
iajs-2946	195	72	mse	mse	PROPN
iajs-2946	195	73	values	value	NOUN
iajs-2946	195	74	for	for	ADP
iajs-2946	195	75	different	different	ADJ
iajs-2946	195	76	estimation	estimation	NOUN
iajs-2946	195	77	methods	method	NOUN
iajs-2946	195	78	increase	increase	VERB
iajs-2946	195	79	with	with	ADP
iajs-2946	195	80	increasing	increase	VERB
iajs-2946	195	81	values	value	NOUN
iajs-2946	195	82	of	of	ADP
iajs-2946	195	83	γ	γ	NOUN
iajs-2946	195	84	or	or	CCONJ
iajs-2946	195	85	δ	δ	PROPN
iajs-2946	195	86	.	.	PROPN
iajs-2946	196	1	2	2	X
iajs-2946	196	2	.	.	X
iajs-2946	196	3	the	the	DET
iajs-2946	196	4	bayesian	bayesian	NOUN
iajs-2946	196	5	estimation	estimation	NOUN
iajs-2946	196	6	under	under	ADP
iajs-2946	196	7	entropy	entropy	NOUN
iajs-2946	196	8	loss	loss	NOUN
iajs-2946	196	9	function	function	NOUN
iajs-2946	196	10	with	with	ADP
iajs-2946	196	11	assuming	assume	VERB
iajs-2946	196	12	the	the	DET
iajs-2946	196	13	exponential	exponential	ADJ
iajs-2946	196	14	distribution	distribution	NOUN
iajs-2946	196	15	and	and	CCONJ
iajs-2946	196	16	gamma	gamma	NOUN
iajs-2946	196	17	distribution	distribution	NOUN
iajs-2946	196	18	priors	prior	NOUN
iajs-2946	196	19	of	of	ADP
iajs-2946	196	20	the	the	DET
iajs-2946	196	21	scale	scale	NOUN
iajs-2946	196	22	and	and	CCONJ
iajs-2946	196	23	the	the	DET
iajs-2946	196	24	location	location	NOUN
iajs-2946	196	25	parameters	parameter	NOUN
iajs-2946	196	26	,	,	PUNCT
iajs-2946	196	27	respectively	respectively	ADV
iajs-2946	196	28	,	,	PUNCT
iajs-2946	196	29	is	be	AUX
iajs-2946	196	30	the	the	DET
iajs-2946	196	31	best	good	ADJ
iajs-2946	196	32	estimator	estimator	NOUN
iajs-2946	196	33	for	for	ADP
iajs-2946	196	34	γ	γ	PROPN
iajs-2946	196	35	.	.	PROPN
iajs-2946	196	36	3	3	NUM
iajs-2946	196	37	.	.	X
iajs-2946	197	1	it	it	PRON
iajs-2946	197	2	is	be	AUX
iajs-2946	197	3	clear	clear	ADJ
iajs-2946	197	4	that	that	SCONJ
iajs-2946	197	5	the	the	DET
iajs-2946	197	6	best	good	ADJ
iajs-2946	197	7	estimation	estimation	NOUN
iajs-2946	197	8	method	method	NOUN
iajs-2946	197	9	for	for	ADP
iajs-2946	197	10	δ	δ	PROPN
iajs-2946	197	11	is	be	AUX
iajs-2946	197	12	the	the	DET
iajs-2946	197	13	bayesian	bayesian	NOUN
iajs-2946	197	14	estimation	estimation	NOUN
iajs-2946	197	15	under	under	ADP
iajs-2946	197	16	the	the	DET
iajs-2946	197	17	entropy	entropy	NOUN
iajs-2946	197	18	loss	loss	NOUN
iajs-2946	197	19	function	function	NOUN
iajs-2946	197	20	in	in	ADP
iajs-2946	197	21	the	the	DET
iajs-2946	197	22	case	case	NOUN
iajs-2946	197	23	of	of	ADP
iajs-2946	197	24	a	a	DET
iajs-2946	197	25	small	small	ADJ
iajs-2946	197	26	value	value	NOUN
iajs-2946	197	27	of	of	ADP
iajs-2946	197	28	γ	γ	X
iajs-2946	197	29	(	(	PUNCT
iajs-2946	197	30	say	say	VERB
iajs-2946	197	31	γ	γ	X
iajs-2946	197	32	<	<	X
iajs-2946	197	33	1	1	NUM
iajs-2946	197	34	)	)	PUNCT
iajs-2946	197	35	while	while	SCONJ
iajs-2946	197	36	bayesian	bayesian	NOUN
iajs-2946	197	37	estimation	estimation	NOUN
iajs-2946	197	38	under	under	ADP
iajs-2946	197	39	the	the	DET
iajs-2946	197	40	precautionary	precautionary	ADJ
iajs-2946	197	41	loss	loss	NOUN
iajs-2946	197	42	function	function	NOUN
iajs-2946	197	43	is	be	AUX
iajs-2946	197	44	the	the	DET
iajs-2946	197	45	best	good	ADJ
iajs-2946	197	46	in	in	ADP
iajs-2946	197	47	the	the	DET
iajs-2946	197	48	case	case	NOUN
iajs-2946	197	49	of	of	ADP
iajs-2946	197	50	a	a	DET
iajs-2946	197	51	relatively	relatively	ADV
iajs-2946	197	52	large	large	ADJ
iajs-2946	197	53	value	value	NOUN
iajs-2946	197	54	of	of	ADP
iajs-2946	197	55	γ	γ	X
iajs-2946	197	56	(	(	PUNCT
iajs-2946	197	57	say	say	VERB
iajs-2946	197	58	γ	γ	X
iajs-2946	197	59	>	>	X
iajs-2946	197	60	1	1	NUM
iajs-2946	197	61	)	)	PUNCT
iajs-2946	197	62	.	.	PUNCT
iajs-2946	198	1	4	4	X
iajs-2946	198	2	.	.	X
iajs-2946	198	3	generally	generally	ADV
iajs-2946	198	4	,	,	PUNCT
iajs-2946	198	5	the	the	DET
iajs-2946	198	6	bayes	bayes	NOUN
iajs-2946	198	7	estimate	estimate	VERB
iajs-2946	198	8	for	for	ADP
iajs-2946	198	9	each	each	PRON
iajs-2946	198	10	of	of	ADP
iajs-2946	198	11	γ	γ	PROPN
iajs-2946	198	12	and	and	CCONJ
iajs-2946	198	13	δ	δ	PROPN
iajs-2946	198	14	are	be	AUX
iajs-2946	198	15	better	well	ADJ
iajs-2946	198	16	than	than	ADP
iajs-2946	198	17	the	the	DET
iajs-2946	198	18	maximum	maximum	ADJ
iajs-2946	198	19	-	-	PUNCT
iajs-2946	198	20	likelihood	likelihood	NOUN
iajs-2946	198	21	estimates	estimate	NOUN
iajs-2946	198	22	.	.	PUNCT
iajs-2946	199	1	table	table	NOUN
iajs-2946	199	2	1	1	NUM
iajs-2946	199	3	:	:	PUNCT
iajs-2946	199	4	the	the	DET
iajs-2946	199	5	expected	expect	VERB
iajs-2946	199	6	values	value	NOUN
iajs-2946	199	7	of	of	ADP
iajs-2946	199	8	different	different	ADJ
iajs-2946	199	9	estimators	estimator	NOUN
iajs-2946	199	10	for	for	ADP
iajs-2946	199	11	scale	scale	NOUN
iajs-2946	199	12	parameter	parameter	NOUN
iajs-2946	199	13	γ	γ	NOUN
iajs-2946	199	14	of	of	ADP
iajs-2946	199	15	exponential	exponential	ADJ
iajs-2946	199	16	distribution	distribution	NOUN
iajs-2946	199	17	when	when	SCONJ
iajs-2946	199	18	γ	γ	X
iajs-2946	199	19	=	=	SYM
iajs-2946	199	20	0.5	0.5	NUM
iajs-2946	199	21	n	n	PRON
iajs-2946	199	22	method	method	NOUN
iajs-2946	199	23	δ	δ	PROPN
iajs-2946	199	24	10	10	NUM
iajs-2946	199	25	30	30	NUM
iajs-2946	199	26	50	50	NUM
iajs-2946	199	27	100	100	NUM
iajs-2946	199	28	γ̂ml	γ̂ml	NOUN
iajs-2946	199	29	0.8	0.8	NUM
iajs-2946	199	30	0.44891420	0.44891420	NUM
iajs-2946	199	31	0.48373730	0.48373730	NUM
iajs-2946	199	32	0.49016020	0.49016020	NUM
iajs-2946	199	33	0.49513680	0.49513680	NUM
iajs-2946	199	34	γ̂se	γ̂se	PROPN
iajs-2946	199	35	0.44833940	0.44833940	NUM
iajs-2946	199	36	0.48366570	0.48366570	NUM
iajs-2946	199	37	0.49013460	0.49013460	NUM
iajs-2946	199	38	0.49513010	0.49513010	NUM
iajs-2946	199	39	γ̂e	γ̂e	NUM
iajs-2946	199	40	0.44833720	0.44833720	NUM
iajs-2946	199	41	0.48366560	0.48366560	NUM
iajs-2946	199	42	0.49013450	0.49013450	NUM
iajs-2946	199	43	0.49513010	0.49513010	NUM
iajs-2946	199	44	γ̂p	γ̂p	NUM
iajs-2946	199	45	0.44834030	0.44834030	NUM
iajs-2946	199	46	0.48366580	0.48366580	NUM
iajs-2946	199	47	0.49013470	0.49013470	NUM
iajs-2946	199	48	0.49513010	0.49513010	NUM
iajs-2946	199	49	γ̂ml	γ̂ml	NOUN
iajs-2946	199	50	2	2	NUM
iajs-2946	199	51	0.44891410	0.44891410	NUM
iajs-2946	199	52	0.48373720	0.48373720	NUM
iajs-2946	199	53	0.49016010	0.49016010	NUM
iajs-2946	199	54	0.49513680	0.49513680	NUM
iajs-2946	199	55	γ̂se	γ̂se	NOUN
iajs-2946	199	56	0.44881240	0.44881240	NUM
iajs-2946	200	1	0.48372580	0.48372580	NUM
iajs-2946	200	2	0.49015650	0.49015650	NUM
iajs-2946	200	3	0.49513560	0.49513560	NUM
iajs-2946	200	4	γ̂e	γ̂e	NUM
iajs-2946	200	5	0.44881220	0.44881220	NUM
iajs-2946	200	6	0.48372580	0.48372580	NUM
iajs-2946	200	7	0.49015660	0.49015660	NUM
iajs-2946	200	8	0.49513550	0.49513550	NUM
iajs-2946	200	9	γ̂p	γ̂p	PUNCT
iajs-2946	200	10	0.44881240	0.44881240	NUM
iajs-2946	200	11	0.48372580	0.48372580	NUM
iajs-2946	200	12	0.49015670	0.49015670	NUM
iajs-2946	200	13	0.49513570	0.49513570	NUM
iajs-2946	200	14	ihjpas	ihjpa	NOUN
iajs-2946	200	15	.	.	PUNCT
iajs-2946	201	1	36(2)2023	36(2)2023	NUM
iajs-2946	201	2	298	298	NUM
iajs-2946	201	3	table	table	NOUN
iajs-2946	201	4	2	2	NUM
iajs-2946	201	5	:	:	PUNCT
iajs-2946	201	6	the	the	DET
iajs-2946	201	7	mse	mse	NOUN
iajs-2946	201	8	values	value	NOUN
iajs-2946	201	9	of	of	ADP
iajs-2946	201	10	different	different	ADJ
iajs-2946	201	11	estimators	estimator	NOUN
iajs-2946	201	12	for	for	ADP
iajs-2946	201	13	scale	scale	NOUN
iajs-2946	201	14	parameter	parameter	NOUN
iajs-2946	201	15	γ	γ	NOUN
iajs-2946	201	16	of	of	ADP
iajs-2946	201	17	exponential	exponential	ADJ
iajs-2946	201	18	distribution	distribution	NOUN
iajs-2946	201	19	when	when	SCONJ
iajs-2946	201	20	γ	γ	X
iajs-2946	201	21	=	=	SYM
iajs-2946	201	22	0.5	0.5	NUM
iajs-2946	201	23	n	n	PRON
iajs-2946	201	24	method	method	NOUN
iajs-2946	201	25	δ	δ	PROPN
iajs-2946	201	26	10	10	NUM
iajs-2946	201	27	30	30	NUM
iajs-2946	201	28	50	50	NUM
iajs-2946	201	29	100	100	NUM
iajs-2946	201	30	γ̂ml	γ̂ml	NOUN
iajs-2946	201	31	0.8	0.8	NUM
iajs-2946	201	32	0.02490506	0.02490506	NUM
iajs-2946	201	33	0.00825872	0.00825872	NUM
iajs-2946	202	1	0.00499760	0.00499760	NUM
iajs-2946	202	2	0.00255322	0.00255322	NUM
iajs-2946	202	3	γ̂se	γ̂se	NOUN
iajs-2946	202	4	0.02480166	0.02480166	NUM
iajs-2946	202	5	0.00825400	0.00825400	NUM
iajs-2946	202	6	0.00499656	0.00499656	NUM
iajs-2946	202	7	0.00255308	0.00255308	NUM
iajs-2946	202	8	γ̂e	γ̂e	VERB
iajs-2946	202	9	0.02480095	0.02480095	NUM
iajs-2946	202	10	0.00825400	0.00825400	NUM
iajs-2946	202	11	0.00499656	0.00499656	NUM
iajs-2946	202	12	0.00255308	0.00255308	NUM
iajs-2946	202	13	γ̂p	γ̂p	NUM
iajs-2946	202	14	0.02480199	0.02480199	NUM
iajs-2946	202	15	0.00825401	0.00825401	NUM
iajs-2946	202	16	0.00499655	0.00499655	NUM
iajs-2946	202	17	0.00255308	0.00255308	NUM
iajs-2946	202	18	γ̂ml	γ̂ml	NOUN
iajs-2946	202	19	2	2	NUM
iajs-2946	202	20	0.02490506	0.02490506	NUM
iajs-2946	202	21	0.00825872	0.00825872	NUM
iajs-2946	202	22	0.00499760	0.00499760	NUM
iajs-2946	202	23	0.00255323	0.00255323	NUM
iajs-2946	202	24	γ̂	γ̂	PUNCT
iajs-2946	202	25	se	se	PROPN
iajs-2946	202	26	0.02488599	0.02488599	NUM
iajs-2946	202	27	0.00825792	0.00825792	NUM
iajs-2946	202	28	0.00499743	0.00499743	NUM
iajs-2946	202	29	0.00255320	0.00255320	NUM
iajs-2946	202	30	γ̂e	γ̂e	NUM
iajs-2946	202	31	0.02488597	0.02488597	NUM
iajs-2946	202	32	0.00825792	0.00825792	NUM
iajs-2946	202	33	0.00499743	0.00499743	NUM
iajs-2946	202	34	0.00255320	0.00255320	NUM
iajs-2946	202	35	γ̂p	γ̂p	NUM
iajs-2946	202	36	0.02488600	0.02488600	NUM
iajs-2946	202	37	0.00825792	0.00825792	NUM
iajs-2946	202	38	0.00499743	0.00499743	NUM
iajs-2946	202	39	0.00255320	0.00255320	NUM
iajs-2946	202	40	table	table	NOUN
iajs-2946	202	41	3	3	NUM
iajs-2946	202	42	:	:	PUNCT
iajs-2946	202	43	the	the	DET
iajs-2946	202	44	expected	expect	VERB
iajs-2946	202	45	values	value	NOUN
iajs-2946	202	46	of	of	ADP
iajs-2946	202	47	different	different	ADJ
iajs-2946	202	48	estimators	estimator	NOUN
iajs-2946	202	49	for	for	ADP
iajs-2946	202	50	scale	scale	NOUN
iajs-2946	202	51	parameter	parameter	NOUN
iajs-2946	202	52	γ	γ	NOUN
iajs-2946	202	53	of	of	ADP
iajs-2946	202	54	exponential	exponential	ADJ
iajs-2946	202	55	distribution	distribution	NOUN
iajs-2946	202	56	when	when	SCONJ
iajs-2946	202	57	γ	γ	X
iajs-2946	202	58	=	=	SYM
iajs-2946	202	59	1.5	1.5	NUM
iajs-2946	202	60	n	n	PRON
iajs-2946	202	61	method	method	NOUN
iajs-2946	202	62	δ	δ	PROPN
iajs-2946	202	63	10	10	NUM
iajs-2946	202	64	30	30	NUM
iajs-2946	202	65	50	50	NUM
iajs-2946	202	66	100	100	NUM
iajs-2946	202	67	γ̂ml	γ̂ml	NOUN
iajs-2946	202	68	0.8	0.8	NUM
iajs-2946	202	69	1.34674300	1.34674300	NUM
iajs-2946	202	70	1.45121400	1.45121400	NUM
iajs-2946	202	71	1.47047900	1.47047900	NUM
iajs-2946	202	72	1.48540900	1.48540900	NUM
iajs-2946	202	73	γ̂se	γ̂se	PROPN
iajs-2946	202	74	1.33628700	1.33628700	NUM
iajs-2946	202	75	1.44952700	1.44952700	NUM
iajs-2946	202	76	1.46982700	1.46982700	NUM
iajs-2946	202	77	1.48523600	1.48523600	NUM
iajs-2946	202	78	γ̂e	γ̂e	NUM
iajs-2946	202	79	1.33607700	1.33607700	NUM
iajs-2946	202	80	1.44952300	1.44952300	NUM
iajs-2946	202	81	1.46982600	1.46982600	NUM
iajs-2946	202	82	1.48523600	1.48523600	NUM
iajs-2946	202	83	γ̂p	γ̂p	NUM
iajs-2946	202	84	1.33638800	1.33638800	NUM
iajs-2946	202	85	1.44952900	1.44952900	NUM
iajs-2946	202	86	1.46982700	1.46982700	NUM
iajs-2946	202	87	1.48523600	1.48523600	NUM
iajs-2946	202	88	γ̂ml	γ̂ml	NOUN
iajs-2946	202	89	2	2	NUM
iajs-2946	202	90	1.34674300	1.34674300	NUM
iajs-2946	202	91	1.45121400	1.45121400	NUM
iajs-2946	202	92	1.47047900	1.47047900	NUM
iajs-2946	202	93	1.48540900	1.48540900	NUM
iajs-2946	202	94	γ̂se	γ̂se	PROPN
iajs-2946	202	95	1.34434900	1.34434900	NUM
iajs-2946	202	96	1.45090400	1.45090400	NUM
iajs-2946	202	97	1.47036600	1.47036600	NUM
iajs-2946	202	98	1.48537900	1.48537900	NUM
iajs-2946	202	99	γ̂e	γ̂e	NUM
iajs-2946	202	100	1.34433600	1.34433600	NUM
iajs-2946	202	101	1.45090400	1.45090400	NUM
iajs-2946	202	102	1.47036600	1.47036600	NUM
iajs-2946	202	103	1.48537900	1.48537900	NUM
iajs-2946	202	104	γ̂p	γ̂p	NUM
iajs-2946	202	105	1.34435500	1.34435500	NUM
iajs-2946	202	106	1.45090500	1.45090500	NUM
iajs-2946	202	107	1.47036700	1.47036700	NUM
iajs-2946	202	108	1.48537900	1.48537900	NUM
iajs-2946	202	109	table	table	NOUN
iajs-2946	202	110	4	4	NUM
iajs-2946	202	111	:	:	PUNCT
iajs-2946	202	112	the	the	DET
iajs-2946	202	113	mse	mse	NOUN
iajs-2946	202	114	values	value	NOUN
iajs-2946	202	115	of	of	ADP
iajs-2946	202	116	different	different	ADJ
iajs-2946	202	117	estimators	estimator	NOUN
iajs-2946	202	118	for	for	ADP
iajs-2946	202	119	scale	scale	NOUN
iajs-2946	202	120	parameter	parameter	NOUN
iajs-2946	202	121	γ	γ	NOUN
iajs-2946	202	122	of	of	ADP
iajs-2946	202	123	exponential	exponential	ADJ
iajs-2946	202	124	distribution	distribution	NOUN
iajs-2946	202	125	when	when	SCONJ
iajs-2946	202	126	γ	γ	X
iajs-2946	202	127	=	=	SYM
iajs-2946	202	128	1.5	1.5	NUM
iajs-2946	202	129	n	n	PRON
iajs-2946	202	130	method	method	NOUN
iajs-2946	202	131	δ	δ	PROPN
iajs-2946	202	132	10	10	NUM
iajs-2946	202	133	30	30	NUM
iajs-2946	202	134	50	50	NUM
iajs-2946	202	135	100	100	NUM
iajs-2946	202	136	γ̂ml	γ̂ml	NOUN
iajs-2946	202	137	0.8	0.8	NUM
iajs-2946	202	138	0.22414510	0.22414510	NUM
iajs-2946	202	139	0.07432850	0.07432850	NUM
iajs-2946	202	140	0.04497841	0.04497841	NUM
iajs-2946	202	141	0.02297903	0.02297903	NUM
iajs-2946	202	142	γ̂se	γ̂se	NOUN
iajs-2946	202	143	0.21975310	0.21975310	NUM
iajs-2946	202	144	0.07402348	0.07402348	NUM
iajs-2946	202	145	0.04490448	0.04490448	NUM
iajs-2946	202	146	0.02296835	0.02296835	NUM
iajs-2946	202	147	γ̂e	γ̂e	NUM
iajs-2946	202	148	0.21958860	0.21958860	NUM
iajs-2946	202	149	0.07402191	0.07402191	NUM
iajs-2946	202	150	0.04490434	0.04490434	NUM
iajs-2946	202	151	0.02296834	0.02296834	NUM
iajs-2946	202	152	γ̂p	γ̂p	NUM
iajs-2946	202	153	0.21983030	0.21983030	NUM
iajs-2946	202	154	0.07402430	0.07402430	NUM
iajs-2946	202	155	0.04490453	0.04490453	NUM
iajs-2946	202	156	0.02296836	0.02296836	NUM
iajs-2946	202	157	γ̂ml	γ̂ml	NOUN
iajs-2946	202	158	2	2	NUM
iajs-2946	202	159	0.22414520	0.22414520	NUM
iajs-2946	202	160	0.07432850	0.07432850	NUM
iajs-2946	202	161	0.04497840	0.04497840	NUM
iajs-2946	202	162	0.02297903	0.02297903	NUM
iajs-2946	202	163	γ̂se	γ̂se	NOUN
iajs-2946	202	164	0.22287770	0.22287770	NUM
iajs-2946	202	165	0.07426836	0.07426836	NUM
iajs-2946	202	166	0.04496492	0.04496492	NUM
iajs-2946	202	167	0.02297720	0.02297720	NUM
iajs-2946	202	168	γ̂e	γ̂e	NUM
iajs-2946	202	169	0.22286580	0.22286580	NUM
iajs-2946	202	170	0.07426828	0.07426828	NUM
iajs-2946	202	171	0.04496492	0.04496492	NUM
iajs-2946	202	172	0.02297719	0.02297719	NUM
iajs-2946	202	173	γ̂p	γ̂p	NUM
iajs-2946	202	174	0.22288340	0.22288340	NUM
iajs-2946	202	175	0.07426836	0.07426836	NUM
iajs-2946	202	176	0.04496482	0.04496482	NUM
iajs-2946	202	177	0.02297721	0.02297721	NUM
iajs-2946	202	178	ihjpas	ihjpa	NOUN
iajs-2946	202	179	.	.	PUNCT
iajs-2946	203	1	36(2)2023	36(2)2023	NUM
iajs-2946	203	2	299	299	NUM
iajs-2946	203	3	table	table	NOUN
iajs-2946	203	4	5	5	NUM
iajs-2946	203	5	:	:	PUNCT
iajs-2946	203	6	the	the	DET
iajs-2946	203	7	expected	expect	VERB
iajs-2946	203	8	values	value	NOUN
iajs-2946	203	9	of	of	ADP
iajs-2946	203	10	different	different	ADJ
iajs-2946	203	11	estimators	estimator	NOUN
iajs-2946	203	12	for	for	ADP
iajs-2946	203	13	the	the	DET
iajs-2946	203	14	location	location	NOUN
iajs-2946	203	15	parameter	parameter	PROPN
iajs-2946	203	16	δ	δ	PROPN
iajs-2946	203	17	of	of	ADP
iajs-2946	203	18	exponential	exponential	ADJ
iajs-2946	203	19	distribution	distribution	NOUN
iajs-2946	203	20	when	when	SCONJ
iajs-2946	203	21	δ	δ	PROPN
iajs-2946	203	22	=	=	VERB
iajs-2946	203	23	0.8	0.8	NUM
iajs-2946	203	24	n	n	PRON
iajs-2946	203	25	method	method	VERB
iajs-2946	203	26	γ	γ	X
iajs-2946	203	27	10	10	NUM
iajs-2946	203	28	30	30	NUM
iajs-2946	203	29	50	50	NUM
iajs-2946	203	30	100	100	NUM
iajs-2946	203	31	δ̂ml	δ̂ml	NOUN
iajs-2946	203	32	0.5	0.5	NUM
iajs-2946	203	33	0.84943810	0.84943810	NUM
iajs-2946	203	34	0.81654290	0.81654290	NUM
iajs-2946	203	35	0.80986330	0.80986330	NUM
iajs-2946	203	36	0.80493010	0.80493010	NUM
iajs-2946	203	37	δ̂se	δ̂se	ADP
iajs-2946	203	38	0.84540890	0.84540890	NUM
iajs-2946	203	39	0.81520250	0.81520250	NUM
iajs-2946	203	40	0.80906610	0.80906610	NUM
iajs-2946	203	41	0.80453480	0.80453480	NUM
iajs-2946	203	42	δ̂e	δ̂e	NUM
iajs-2946	203	43	0.84528550	0.84528550	NUM
iajs-2946	203	44	0.81519470	0.81519470	NUM
iajs-2946	203	45	0.80906360	0.80906360	NUM
iajs-2946	203	46	0.80453440	0.80453440	NUM
iajs-2946	203	47	δ̂p	δ̂p	NOUN
iajs-2946	203	48	0.84546530	0.84546530	NUM
iajs-2946	203	49	0.81520490	0.81520490	NUM
iajs-2946	203	50	0.80906710	0.80906710	NUM
iajs-2946	203	51	0.80453500	0.80453500	NUM
iajs-2946	203	52	δ̂ml	δ̂ml	NOUN
iajs-2946	203	53	1.5	1.5	NUM
iajs-2946	203	54	0.94831380	0.94831380	NUM
iajs-2946	203	55	0.84963150	0.84963150	NUM
iajs-2946	203	56	0.82959090	0.82959090	NUM
iajs-2946	203	57	0.81479020	0.81479020	NUM
iajs-2946	203	58	δ̂se	δ̂se	ADP
iajs-2946	203	59	0.80684980	0.80684980	NUM
iajs-2946	203	60	0.77114510	0.77114510	NUM
iajs-2946	203	61	0.77653750	0.77653750	NUM
iajs-2946	203	62	0.78571520	0.78571520	NUM
iajs-2946	203	63	δ̂e	δ̂e	NUM
iajs-2946	203	64	0.77337370	0.77337370	NUM
iajs-2946	203	65	0.74146620	0.74146620	NUM
iajs-2946	203	66	0.76579320	0.76579320	NUM
iajs-2946	203	67	0.78308200	0.78308200	NUM
iajs-2946	203	68	δ̂p	δ̂p	NOUN
iajs-2946	203	69	0.82826040	0.82826040	NUM
iajs-2946	203	70	0.77865910	0.77865910	NUM
iajs-2946	203	71	0.78010240	0.78010240	NUM
iajs-2946	203	72	0.78680470	0.78680470	NUM
iajs-2946	203	73	table	table	NOUN
iajs-2946	203	74	6	6	NUM
iajs-2946	203	75	:	:	PUNCT
iajs-2946	203	76	the	the	DET
iajs-2946	203	77	mse	mse	NOUN
iajs-2946	203	78	values	value	NOUN
iajs-2946	203	79	of	of	ADP
iajs-2946	203	80	different	different	ADJ
iajs-2946	203	81	estimators	estimator	NOUN
iajs-2946	203	82	for	for	ADP
iajs-2946	203	83	the	the	DET
iajs-2946	203	84	location	location	NOUN
iajs-2946	203	85	parameter	parameter	PROPN
iajs-2946	203	86	δ	δ	PROPN
iajs-2946	203	87	of	of	ADP
iajs-2946	203	88	exponential	exponential	ADJ
iajs-2946	203	89	distribution	distribution	NOUN
iajs-2946	203	90	when	when	SCONJ
iajs-2946	203	91	δ	δ	PROPN
iajs-2946	203	92	=	=	VERB
iajs-2946	203	93	0.8	0.8	NUM
iajs-2946	203	94	n	n	PRON
iajs-2946	203	95	method	method	VERB
iajs-2946	203	96	γ	γ	X
iajs-2946	203	97	10	10	NUM
iajs-2946	203	98	30	30	NUM
iajs-2946	203	99	50	50	NUM
iajs-2946	203	100	100	100	NUM
iajs-2946	203	101	δ̂ml	δ̂ml	NOUN
iajs-2946	203	102	0.5	0.5	NUM
iajs-2946	203	103	0.00488748	0.00488748	NUM
iajs-2946	203	104	0.00055560	0.00055560	NUM
iajs-2946	203	105	0.00019943	0.00019943	NUM
iajs-2946	203	106	0.00004816	0.00004816	NUM
iajs-2946	203	107	δ̂se	δ̂se	VERB
iajs-2946	203	108	0.00453428	0.00453428	NUM
iajs-2946	203	109	0.00051516	0.00051516	NUM
iajs-2946	203	110	0.00018462	0.00018462	NUM
iajs-2946	203	111	0.00004448	0.00004448	NUM
iajs-2946	203	112	δ̂e	δ̂e	NUM
iajs-2946	203	113	0.00452783	0.00452783	NUM
iajs-2946	203	114	0.00051498	0.00051498	NUM
iajs-2946	203	115	0.00018458	0.00018458	NUM
iajs-2946	203	116	0.00004448	0.00004448	NUM
iajs-2946	203	117	δ̂p	δ̂p	NOUN
iajs-2946	203	118	0.00453743	0.00453743	NUM
iajs-2946	203	119	0.00051525	0.00051525	NUM
iajs-2946	203	120	0.00018464	0.00018464	NUM
iajs-2946	203	121	0.00004448	0.00004448	NUM
iajs-2946	203	122	δ̂ml	δ̂ml	NOUN
iajs-2946	203	123	1.5	1.5	NUM
iajs-2946	203	124	0.04398723	0.04398723	NUM
iajs-2946	203	125	0.00500045	0.00500045	NUM
iajs-2946	203	126	0.00179484	0.00179484	NUM
iajs-2946	203	127	0.00043346	0.00043346	NUM
iajs-2946	203	128	δ̂se	δ̂se	NUM
iajs-2946	203	129	0.03550759	0.03550759	NUM
iajs-2946	203	130	0.00582472	0.00582472	NUM
iajs-2946	203	131	0.00223016	0.00223016	NUM
iajs-2946	203	132	0.00055773	0.00055773	NUM
iajs-2946	203	133	δ̂e	δ̂e	NUM
iajs-2946	203	134	0.07198691	0.07198691	NUM
iajs-2946	203	135	0.01483009	0.01483009	NUM
iajs-2946	203	136	0.00375661	0.00375661	NUM
iajs-2946	203	137	0.00069869	0.00069869	NUM
iajs-2946	203	138	δ̂p	δ̂p	NOUN
iajs-2946	203	139	0.03065065	0.03065065	NUM
iajs-2946	203	140	0.00471544	0.00471544	NUM
iajs-2946	203	141	0.00189898	0.00189898	NUM
iajs-2946	203	142	0.00050857	0.00050857	NUM
iajs-2946	203	143	table	table	NOUN
iajs-2946	203	144	7	7	NUM
iajs-2946	203	145	:	:	PUNCT
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iajs-2946	203	147	expected	expect	VERB
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iajs-2946	203	151	estimators	estimator	NOUN
iajs-2946	203	152	for	for	ADP
iajs-2946	203	153	the	the	DET
iajs-2946	203	154	location	location	NOUN
iajs-2946	203	155	parameter	parameter	PROPN
iajs-2946	203	156	δ	δ	PROPN
iajs-2946	203	157	of	of	ADP
iajs-2946	203	158	exponential	exponential	ADJ
iajs-2946	203	159	distribution	distribution	NOUN
iajs-2946	203	160	when	when	SCONJ
iajs-2946	203	161	δ	δ	PROPN
iajs-2946	203	162	=	=	SYM
iajs-2946	203	163	2	2	NUM
iajs-2946	203	164	n	n	PRON
iajs-2946	203	165	method	method	VERB
iajs-2946	203	166	γ	γ	X
iajs-2946	203	167	10	10	NUM
iajs-2946	203	168	30	30	NUM
iajs-2946	203	169	50	50	NUM
iajs-2946	203	170	100	100	NUM
iajs-2946	203	171	δ̂ml	δ̂ml	NOUN
iajs-2946	203	172	0.5	0.5	NUM
iajs-2946	203	173	2.04943400	2.04943400	NUM
iajs-2946	203	174	2.01654200	2.01654200	NUM
iajs-2946	203	175	2.00986100	2.00986100	NUM
iajs-2946	203	176	2.00492500	2.00492500	NUM
iajs-2946	203	177	δ̂se	δ̂se	ADP
iajs-2946	203	178	2.04767900	2.04767900	NUM
iajs-2946	203	179	2.01599500	2.01599500	NUM
iajs-2946	203	180	2.00954100	2.00954100	NUM
iajs-2946	203	181	2.00476700	2.00476700	NUM
iajs-2946	203	182	δ̂e	δ̂e	NUM
iajs-2946	203	183	2.04766800	2.04766800	NUM
iajs-2946	203	184	2.01599400	2.01599400	NUM
iajs-2946	203	185	2.00954100	2.00954100	NUM
iajs-2946	203	186	2.00476700	2.00476700	NUM
iajs-2946	203	187	δ̂p	δ̂p	NOUN
iajs-2946	203	188	2.04768400	2.04768400	NUM
iajs-2946	203	189	2.01599500	2.01599500	NUM
iajs-2946	203	190	2.00954000	2.00954000	NUM
iajs-2946	203	191	2.00476800	2.00476800	NUM
iajs-2946	203	192	δ̂ml	δ̂ml	NOUN
iajs-2946	203	193	1.5	1.5	NUM
iajs-2946	203	194	2.14831400	2.14831400	NUM
iajs-2946	203	195	2.04962900	2.04962900	NUM
iajs-2946	203	196	2.02959000	2.02959000	NUM
iajs-2946	203	197	2.01479300	2.01479300	NUM
iajs-2946	203	198	δ̂se	δ̂se	ADP
iajs-2946	203	199	2.04289200	2.04289200	NUM
iajs-2946	203	200	2.00840900	2.00840900	NUM
iajs-2946	203	201	2.00449300	2.00449300	NUM
iajs-2946	203	202	2.00213900	2.00213900	NUM
iajs-2946	203	203	δ̂e	δ̂e	NUM
iajs-2946	203	204	2.00838700	2.00838700	NUM
iajs-2946	203	205	2.00557600	2.00557600	NUM
iajs-2946	203	206	2.00363300	2.00363300	NUM
iajs-2946	203	207	2.00195300	2.00195300	NUM
iajs-2946	203	208	δ̂p	δ̂p	NOUN
iajs-2946	203	209	2.05189000	2.05189000	NUM
iajs-2946	203	210	2.00958700	2.00958700	NUM
iajs-2946	203	211	2.00489100	2.00489100	NUM
iajs-2946	203	212	2.00222900	2.00222900	NUM
iajs-2946	203	213	ihjpas	ihjpa	NOUN
iajs-2946	203	214	.	.	PUNCT
iajs-2946	204	1	36(2)2023	36(2)2023	NUM
iajs-2946	204	2	300	300	NUM
iajs-2946	204	3	table	table	NOUN
iajs-2946	204	4	8	8	NUM
iajs-2946	204	5	:	:	PUNCT
iajs-2946	204	6	the	the	DET
iajs-2946	204	7	mse	mse	NOUN
iajs-2946	204	8	values	value	NOUN
iajs-2946	204	9	of	of	ADP
iajs-2946	204	10	different	different	ADJ
iajs-2946	204	11	estimators	estimator	NOUN
iajs-2946	204	12	for	for	ADP
iajs-2946	204	13	the	the	DET
iajs-2946	204	14	location	location	NOUN
iajs-2946	204	15	parameter	parameter	PROPN
iajs-2946	204	16	δ	δ	PROPN
iajs-2946	204	17	of	of	ADP
iajs-2946	204	18	exponential	exponential	ADJ
iajs-2946	204	19	distribution	distribution	NOUN
iajs-2946	204	20	when	when	SCONJ
iajs-2946	204	21	δ	δ	PROPN
iajs-2946	204	22	=	=	SYM
iajs-2946	204	23	2	2	NUM
iajs-2946	204	24	n	n	PRON
iajs-2946	204	25	method	method	VERB
iajs-2946	204	26	γ	γ	X
iajs-2946	204	27	10	10	NUM
iajs-2946	204	28	30	30	NUM
iajs-2946	204	29	50	50	NUM
iajs-2946	204	30	100	100	NUM
iajs-2946	204	31	δ̂ml	δ̂ml	NOUN
iajs-2946	204	32	0.5	0.5	NUM
iajs-2946	204	33	0.00488748	0.00488748	NUM
iajs-2946	204	34	0.00055560	0.00055560	NUM
iajs-2946	204	35	0.00019943	0.00019943	NUM
iajs-2946	204	36	0.00004816	0.00004816	NUM
iajs-2946	204	37	δ̂se	δ̂se	ADP
iajs-2946	204	38	0.00471630	0.00471630	NUM
iajs-2946	204	39	0.00053813	0.00053813	NUM
iajs-2946	204	40	0.00019317	0.00019317	NUM
iajs-2946	204	41	0.00004663	0.00004663	NUM
iajs-2946	204	42	δ̂e	δ̂e	NUM
iajs-2946	204	43	0.00471540	0.00471540	NUM
iajs-2946	204	44	0.00053812	0.00053812	NUM
iajs-2946	204	45	0.00019316	0.00019316	NUM
iajs-2946	204	46	0.00004663	0.00004663	NUM
iajs-2946	204	47	δ̂p	δ̂p	NOUN
iajs-2946	204	48	0.00471674	0.00471674	NUM
iajs-2946	204	49	0.00053814	0.00053814	NUM
iajs-2946	204	50	0.00019317	0.00019317	NUM
iajs-2946	204	51	0.00004663	0.00004663	NUM
iajs-2946	204	52	δ̂ml	δ̂ml	NOUN
iajs-2946	204	53	1.5	1.5	NUM
iajs-2946	204	54	0.04398722	0.04398722	NUM
iajs-2946	204	55	0.00500045	0.00500045	NUM
iajs-2946	204	56	0.00179484	0.00179484	NUM
iajs-2946	204	57	0.00043346	0.00043346	NUM
iajs-2946	204	58	δ̂se	δ̂se	NOUN
iajs-2946	204	59	0.03865999	0.03865999	NUM
iajs-2946	204	60	0.00363416	0.00363416	NUM
iajs-2946	204	61	0.00115354	0.00115354	NUM
iajs-2946	204	62	0.00024975	0.00024975	NUM
iajs-2946	204	63	δ̂e	δ̂e	NUM
iajs-2946	204	64	0.06743077	0.06743077	NUM
iajs-2946	204	65	0.00395757	0.00395757	NUM
iajs-2946	204	66	0.00118017	0.00118017	NUM
iajs-2946	204	67	0.00025086	0.00025086	NUM
iajs-2946	204	68	δ̂p	δ̂p	NOUN
iajs-2946	204	69	0.03536728	0.03536728	NUM
iajs-2946	204	70	0.00354006	0.00354006	NUM
iajs-2946	204	71	0.00114343	0.00114343	NUM
iajs-2946	204	72	0.00024927	0.00024927	NUM
iajs-2946	204	73	references	reference	NOUN
iajs-2946	204	74	1.ahmad	1.ahmad	NUM
iajs-2946	204	75	,	,	PUNCT
iajs-2946	204	76	s.	s.	PROPN
iajs-2946	204	77	p.	p.	PROPN
iajs-2946	204	78	;	;	PUNCT
iajs-2946	204	79	bhat	bhat	PROPN
iajs-2946	204	80	,	,	PUNCT
iajs-2946	204	81	b.	b.	PROPN
iajs-2946	204	82	a.	a.	PROPN
iajs-2946	204	83	,	,	PUNCT
iajs-2946	204	84	posterior	posterior	ADJ
iajs-2946	204	85	estimates	estimate	NOUN
iajs-2946	204	86	of	of	ADP
iajs-2946	204	87	two	two	NUM
iajs-2946	204	88	parameter	parameter	NOUN
iajs-2946	204	89	exponential	exponential	ADJ
iajs-2946	204	90	distribution	distribution	NOUN
iajs-2946	204	91	using	use	VERB
iajs-2946	204	92	s	s	NOUN
iajs-2946	204	93	-	-	PUNCT
iajs-2946	204	94	plus	plus	CCONJ
iajs-2946	204	95	software	software	NOUN
iajs-2946	204	96	,	,	PUNCT
iajs-2946	204	97	journal	journal	NOUN
iajs-2946	204	98	of	of	ADP
iajs-2946	204	99	reliability	reliability	NOUN
iajs-2946	204	100	and	and	CCONJ
iajs-2946	204	101	statistical	statistical	ADJ
iajs-2946	204	102	studies	study	NOUN
iajs-2946	204	103	,	,	PUNCT
iajs-2946	204	104	2010	2010	NUM
iajs-2946	204	105	,	,	PUNCT
iajs-2946	204	106	3	3	NUM
iajs-2946	204	107	,	,	PUNCT
iajs-2946	204	108	2	2	NUM
iajs-2946	204	109	,	,	PUNCT
iajs-2946	204	110	27	27	NUM
iajs-2946	204	111	-	-	SYM
iajs-2946	204	112	34	34	NUM
iajs-2946	204	113	.	.	PUNCT
iajs-2946	205	1	2.rashid	2.rashid	NUM
iajs-2946	205	2	m.	m.	NOUN
iajs-2946	205	3	z.	z.	PROPN
iajs-2946	205	4	;	;	PUNCT
iajs-2946	205	5	akhter	akhter	PROPN
iajs-2946	205	6	a.	a.	PROPN
iajs-2946	205	7	s.	s.	PROPN
iajs-2946	205	8	estimation	estimation	PROPN
iajs-2946	205	9	accuracy	accuracy	NOUN
iajs-2946	205	10	of	of	ADP
iajs-2946	205	11	exponential	exponential	ADJ
iajs-2946	205	12	distribution	distribution	NOUN
iajs-2946	205	13	parameters	parameter	NOUN
iajs-2946	205	14	,	,	PUNCT
iajs-2946	205	15	pakistan	pakistan	PROPN
iajs-2946	205	16	journal	journal	PROPN
iajs-2946	205	17	of	of	ADP
iajs-2946	205	18	statistics	statistic	NOUN
iajs-2946	205	19	and	and	CCONJ
iajs-2946	205	20	operation	operation	NOUN
iajs-2946	205	21	research	research	NOUN
iajs-2946	205	22	,	,	PUNCT
iajs-2946	205	23	2011	2011	NUM
iajs-2946	205	24	,	,	PUNCT
iajs-2946	205	25	7	7	NUM
iajs-2946	205	26	,	,	PUNCT
iajs-2946	205	27	2	2	NUM
iajs-2946	205	28	,	,	PUNCT
iajs-2946	205	29	217	217	NUM
iajs-2946	205	30	-	-	SYM
iajs-2946	205	31	232	232	NUM
iajs-2946	205	32	,	,	PUNCT
iajs-2946	205	33	.	.	PUNCT
iajs-2946	206	1	3	3	X
iajs-2946	206	2	.	.	X
iajs-2946	207	1	he	he	PRON
iajs-2946	207	2	h.	h.	PROPN
iajs-2946	207	3	,	,	PUNCT
iajs-2946	207	4	zhou	zhou	PROPN
iajs-2946	207	5	n.	n.	PROPN
iajs-2946	207	6	,	,	PUNCT
iajs-2946	207	7	zhang	zhang	PROPN
iajs-2946	207	8	r.	r.	PROPN
iajs-2946	207	9	,	,	PUNCT
iajs-2946	207	10	on	on	ADP
iajs-2946	207	11	estimation	estimation	NOUN
iajs-2946	207	12	for	for	ADP
iajs-2946	207	13	the	the	DET
iajs-2946	207	14	pareto	pareto	ADJ
iajs-2946	207	15	distribution	distribution	NOUN
iajs-2946	207	16	,	,	PUNCT
iajs-2946	207	17	statistical	statistical	ADJ
iajs-2946	207	18	methodology	methodology	NOUN
iajs-2946	207	19	,	,	PUNCT
iajs-2946	207	20	2014	2014	NUM
iajs-2946	207	21	,	,	PUNCT
iajs-2946	207	22	21	21	NUM
iajs-2946	207	23	,	,	PUNCT
iajs-2946	207	24	49–58	49–58	NUM
iajs-2946	207	25	.	.	PUNCT
iajs-2946	208	1	4	4	X
iajs-2946	208	2	.	.	X
iajs-2946	208	3	kumar	kumar	PROPN
iajs-2946	208	4	,	,	PUNCT
iajs-2946	208	5	d.	d.	PROPN
iajs-2946	208	6	;	;	PUNCT
iajs-2946	208	7	kumar	kumar	PROPN
iajs-2946	208	8	,	,	PUNCT
iajs-2946	208	9	p.	p.	PROPN
iajs-2946	208	10	singh	singh	PROPN
iajs-2946	208	11	,	,	PUNCT
iajs-2946	208	12	s.	s.	PROPN
iajs-2946	208	13	k.	k.	PROPN
iajs-2946	208	14	;	;	PUNCT
iajs-2946	208	15	singh	singh	PROPN
iajs-2946	208	16	,	,	PUNCT
iajs-2946	208	17	u.	u.	VERB
iajs-2946	208	18	a	a	DET
iajs-2946	208	19	new	new	ADJ
iajs-2946	208	20	asymmetric	asymmetric	ADJ
iajs-2946	208	21	loss	loss	NOUN
iajs-2946	208	22	function	function	NOUN
iajs-2946	208	23	:	:	PUNCT
iajs-2946	208	24	estimation	estimation	NOUN
iajs-2946	208	25	of	of	ADP
iajs-2946	208	26	parameter	parameter	NOUN
iajs-2946	208	27	of	of	ADP
iajs-2946	208	28	exponential	exponential	ADJ
iajs-2946	208	29	distribution	distribution	NOUN
iajs-2946	208	30	.	.	PUNCT
iajs-2946	209	1	journal	journal	PROPN
iajs-2946	209	2	of	of	ADP
iajs-2946	209	3	statistics	statistics	PROPN
iajs-2946	209	4	applications	application	NOUN
iajs-2946	209	5	&	&	CCONJ
iajs-2946	209	6	probability	probability	NOUN
iajs-2946	209	7	letters	letter	NOUN
iajs-2946	209	8	,	,	PUNCT
iajs-2946	209	9	2019	2019	NUM
iajs-2946	209	10	,	,	PUNCT
iajs-2946	209	11	6	6	NUM
iajs-2946	209	12	,	,	PUNCT
iajs-2946	209	13	1	1	NUM
iajs-2946	209	14	,	,	PUNCT
iajs-2946	209	15	37	37	NUM
iajs-2946	209	16	-	-	SYM
iajs-2946	209	17	50	50	NUM
iajs-2946	209	18	.	.	PUNCT
iajs-2946	210	1	issn	issn	PROPN
iajs-2946	210	2	2090	2090	NUM
iajs-2946	210	3	-	-	SYM
iajs-2946	210	4	8458	8458	NUM
iajs-2946	210	5	.	.	PUNCT
iajs-2946	211	1	5.li	5.li	NUM
iajs-2946	211	2	,	,	PUNCT
iajs-2946	211	3	j.	j.	PROPN
iajs-2946	211	4	;	;	PUNCT
iajs-2946	211	5	ren	ren	PROPN
iajs-2946	211	6	,	,	PUNCT
iajs-2946	211	7	h.	h.	PROPN
iajs-2946	211	8	,	,	PUNCT
iajs-2946	211	9	estimation	estimation	NOUN
iajs-2946	211	10	of	of	ADP
iajs-2946	211	11	one	one	NUM
iajs-2946	211	12	parameter	parameter	NOUN
iajs-2946	211	13	exponential	exponential	ADJ
iajs-2946	211	14	family	family	NOUN
iajs-2946	211	15	under	under	ADP
iajs-2946	211	16	a	a	DET
iajs-2946	211	17	precautionary	precautionary	ADJ
iajs-2946	211	18	loss	loss	NOUN
iajs-2946	211	19	function	function	NOUN
iajs-2946	211	20	based	base	VERB
iajs-2946	211	21	on	on	ADP
iajs-2946	211	22	record	record	NOUN
iajs-2946	211	23	values	value	NOUN
iajs-2946	211	24	,	,	PUNCT
iajs-2946	211	25	international	international	ADJ
iajs-2946	211	26	journal	journal	NOUN
iajs-2946	211	27	of	of	ADP
iajs-2946	211	28	engineering	engineering	NOUN
iajs-2946	211	29	and	and	CCONJ
iajs-2946	211	30	manufacturing	manufacturing	NOUN
iajs-2946	211	31	,	,	PUNCT
iajs-2946	211	32	2012	2012	NUM
iajs-2946	211	33	,	,	PUNCT
iajs-2946	211	34	2	2	NUM
iajs-2946	211	35	,	,	PUNCT
iajs-2946	211	36	3	3	NUM
iajs-2946	211	37	,	,	PUNCT
iajs-2946	211	38	75	75	NUM
iajs-2946	211	39	-	-	SYM
iajs-2946	211	40	81	81	NUM
iajs-2946	211	41	.	.	PUNCT
iajs-2946	212	1	6.naji	6.naji	NUM
iajs-2946	212	2	,	,	PUNCT
iajs-2946	212	3	l.	l.	PROPN
iajs-2946	212	4	f.	f.	PROPN
iajs-2946	212	5	;	;	PUNCT
iajs-2946	212	6	rasheed	rasheed	NOUN
iajs-2946	212	7	,	,	PUNCT
iajs-2946	212	8	h.	h.	PROPN
iajs-2946	212	9	a.bayesian	a.bayesian	ADJ
iajs-2946	212	10	estimation	estimation	NOUN
iajs-2946	212	11	for	for	ADP
iajs-2946	212	12	two	two	NUM
iajs-2946	212	13	parameters	parameter	NOUN
iajs-2946	212	14	of	of	ADP
iajs-2946	212	15	gamma	gamma	NOUN
iajs-2946	212	16	distribution	distribution	NOUN
iajs-2946	212	17	under	under	ADP
iajs-2946	212	18	precautionary	precautionary	ADJ
iajs-2946	212	19	loss	loss	NOUN
iajs-2946	212	20	function	function	NOUN
iajs-2946	212	21	,	,	PUNCT
iajs-2946	212	22	ibn	ibn	PROPN
iajs-2946	212	23	al	al	PROPN
iajs-2946	212	24	-	-	PUNCT
iajs-2946	212	25	haitham	haitham	PROPN
iajs-2946	212	26	journal	journal	PROPN
iajs-2946	212	27	for	for	ADP
iajs-2946	212	28	pure	pure	ADJ
iajs-2946	212	29	and	and	CCONJ
iajs-2946	212	30	applied	applied	ADJ
iajs-2946	212	31	sciences	science	NOUN
iajs-2946	212	32	,	,	PUNCT
iajs-2946	212	33	2019,32	2019,32	NUM
iajs-2946	212	34	,	,	PUNCT
iajs-2946	212	35	1	1	NUM
iajs-2946	212	36	,	,	PUNCT
iajs-2946	212	37	193	193	NUM
iajs-2946	212	38	-	-	SYM
iajs-2946	212	39	202	202	NUM
iajs-2946	212	40	,	,	PUNCT
iajs-2946	212	41	7.rashidi	7.rashidi	NUM
iajs-2946	212	42	,	,	PUNCT
iajs-2946	212	43	n.	n.	NOUN
iajs-2946	212	44	,	,	PUNCT
iajs-2946	212	45	sanjari	sanjari	PROPN
iajs-2946	212	46	farsipour	farsipour	PROPN
iajs-2946	212	47	,	,	PUNCT
iajs-2946	212	48	n.	n.	NOUN
iajs-2946	212	49	,	,	PUNCT
iajs-2946	212	50	bayesian	bayesian	NOUN
iajs-2946	212	51	estimation	estimation	NOUN
iajs-2946	212	52	of	of	ADP
iajs-2946	212	53	reliability	reliability	NOUN
iajs-2946	212	54	for	for	ADP
iajs-2946	212	55	rayleigh	rayleigh	ADJ
iajs-2946	212	56	distribution	distribution	NOUN
iajs-2946	212	57	under	under	ADP
iajs-2946	212	58	the	the	DET
iajs-2946	212	59	entropy	entropy	NOUN
iajs-2946	212	60	loss	loss	NOUN
iajs-2946	212	61	function	function	NOUN
iajs-2946	212	62	,	,	PUNCT
iajs-2946	212	63	journal	journal	NOUN
iajs-2946	212	64	of	of	ADP
iajs-2946	212	65	statistical	statistical	ADJ
iajs-2946	212	66	modelling	modelling	NOUN
iajs-2946	212	67	:	:	PUNCT
iajs-2946	212	68	theory	theory	NOUN
iajs-2946	212	69	and	and	CCONJ
iajs-2946	212	70	applications	application	NOUN
iajs-2946	212	71	,	,	PUNCT
iajs-2946	212	72	2022,3	2022,3	NUM
iajs-2946	212	73	,	,	PUNCT
iajs-2946	212	74	1	1	NUM
iajs-2946	212	75	,	,	PUNCT
iajs-2946	212	76	1	1	NUM
iajs-2946	212	77	-	-	SYM
iajs-2946	212	78	8	8	NUM
iajs-2946	212	79	.	.	PUNCT