id	sid	tid	token	lemma	pos
ejpam-6162	1	1	european	european	PROPN
ejpam-6162	1	2	journal	journal	PROPN
ejpam-6162	1	3	of	of	ADP
ejpam-6162	1	4	pure	pure	ADJ
ejpam-6162	1	5	and	and	CCONJ
ejpam-6162	1	6	applied	applied	ADJ
ejpam-6162	1	7	mathematics	mathematic	NOUN
ejpam-6162	1	8	2025	2025	NUM
ejpam-6162	1	9	,	,	PUNCT
ejpam-6162	1	10	vol	vol	NOUN
ejpam-6162	1	11	.	.	PROPN
ejpam-6162	1	12	18	18	NUM
ejpam-6162	1	13	,	,	PUNCT
ejpam-6162	1	14	issue	issue	NOUN
ejpam-6162	1	15	2	2	NUM
ejpam-6162	1	16	,	,	PUNCT
ejpam-6162	1	17	article	article	NOUN
ejpam-6162	1	18	number	number	NOUN
ejpam-6162	1	19	6162	6162	NUM
ejpam-6162	1	20	issn	issn	PROPN
ejpam-6162	1	21	1307	1307	NUM
ejpam-6162	1	22	-	-	SYM
ejpam-6162	1	23	5543	5543	NUM
ejpam-6162	1	24	–	–	PUNCT
ejpam-6162	1	25	ejpam.com	ejpam.com	X
ejpam-6162	1	26	published	publish	VERB
ejpam-6162	1	27	by	by	ADP
ejpam-6162	1	28	new	new	PROPN
ejpam-6162	1	29	york	york	PROPN
ejpam-6162	1	30	business	business	PROPN
ejpam-6162	1	31	global	global	PROPN
ejpam-6162	1	32	a	a	DET
ejpam-6162	1	33	simulation	simulation	NOUN
ejpam-6162	1	34	study	study	NOUN
ejpam-6162	1	35	of	of	ADP
ejpam-6162	1	36	some	some	DET
ejpam-6162	1	37	logistic	logistic	ADJ
ejpam-6162	1	38	,	,	PUNCT
ejpam-6162	1	39	poisson	poisson	NOUN
ejpam-6162	1	40	,	,	PUNCT
ejpam-6162	1	41	and	and	CCONJ
ejpam-6162	1	42	multiple	multiple	ADJ
ejpam-6162	1	43	ridge	ridge	NOUN
ejpam-6162	1	44	regression	regression	PROPN
ejpam-6162	1	45	estimators	estimator	NOUN
ejpam-6162	1	46	jerson	jerson	PROPN
ejpam-6162	1	47	s.	s.	PROPN
ejpam-6162	1	48	mohamad1	mohamad1	PROPN
ejpam-6162	1	49	,	,	PUNCT
ejpam-6162	1	50	angelyn	angelyn	PROPN
ejpam-6162	1	51	s.	s.	PROPN
ejpam-6162	1	52	delica1	delica1	PROPN
ejpam-6162	1	53	,	,	PUNCT
ejpam-6162	1	54	maydalyn	maydalyn	ADJ
ejpam-6162	1	55	h.	h.	PROPN
ejpam-6162	1	56	esperat1	esperat1	PROPN
ejpam-6162	1	57	,	,	PUNCT
ejpam-6162	1	58	aubrey	aubrey	PROPN
ejpam-6162	1	59	g.	g.	PROPN
ejpam-6162	1	60	labastilla1	labastilla1	PROPN
ejpam-6162	1	61	,	,	PUNCT
ejpam-6162	1	62	shiela	shiela	PROPN
ejpam-6162	1	63	may	may	AUX
ejpam-6162	1	64	m.	m.	PROPN
ejpam-6162	1	65	ledesma1	ledesma1	PROPN
ejpam-6162	1	66	,	,	PUNCT
ejpam-6162	1	67	doeyien	doeyien	PROPN
ejpam-6162	1	68	d.	d.	PROPN
ejpam-6162	1	69	misil1	misil1	PROPN
ejpam-6162	2	1	1department	1department	NUM
ejpam-6162	2	2	of	of	ADP
ejpam-6162	2	3	mathematics	mathematic	NOUN
ejpam-6162	2	4	and	and	CCONJ
ejpam-6162	2	5	statistics	statistic	NOUN
ejpam-6162	2	6	,	,	PUNCT
ejpam-6162	2	7	college	college	NOUN
ejpam-6162	2	8	of	of	ADP
ejpam-6162	2	9	science	science	NOUN
ejpam-6162	2	10	and	and	CCONJ
ejpam-6162	2	11	mathematics	mathematic	NOUN
ejpam-6162	2	12	,	,	PUNCT
ejpam-6162	2	13	western	western	ADJ
ejpam-6162	2	14	mindanao	mindanao	PROPN
ejpam-6162	2	15	state	state	PROPN
ejpam-6162	2	16	university	university	PROPN
ejpam-6162	2	17	,	,	PUNCT
ejpam-6162	2	18	7000	7000	NUM
ejpam-6162	2	19	,	,	PUNCT
ejpam-6162	2	20	zamboanga	zamboanga	PROPN
ejpam-6162	2	21	city	city	PROPN
ejpam-6162	2	22	,	,	PUNCT
ejpam-6162	2	23	philippines	philippine	NOUN
ejpam-6162	2	24	abstract	abstract	ADJ
ejpam-6162	2	25	.	.	PUNCT
ejpam-6162	3	1	this	this	DET
ejpam-6162	3	2	paper	paper	NOUN
ejpam-6162	3	3	is	be	AUX
ejpam-6162	3	4	a	a	DET
ejpam-6162	3	5	monte	monte	PROPN
ejpam-6162	3	6	carlo	carlo	PROPN
ejpam-6162	3	7	simulation	simulation	PROPN
ejpam-6162	3	8	study	study	NOUN
ejpam-6162	3	9	of	of	ADP
ejpam-6162	3	10	some	some	DET
ejpam-6162	3	11	logistic	logistic	ADJ
ejpam-6162	3	12	,	,	PUNCT
ejpam-6162	3	13	poisson	poisson	NOUN
ejpam-6162	3	14	,	,	PUNCT
ejpam-6162	3	15	and	and	CCONJ
ejpam-6162	3	16	multiple	multiple	ADJ
ejpam-6162	3	17	ridge	ridge	NOUN
ejpam-6162	3	18	regression	regression	NOUN
ejpam-6162	3	19	estimators	estimator	NOUN
ejpam-6162	3	20	.	.	PUNCT
ejpam-6162	4	1	this	this	DET
ejpam-6162	4	2	study	study	NOUN
ejpam-6162	4	3	proposes	propose	VERB
ejpam-6162	4	4	new	new	ADJ
ejpam-6162	4	5	ridge	ridge	NOUN
ejpam-6162	4	6	regression	regression	NOUN
ejpam-6162	4	7	estimators	estimator	NOUN
ejpam-6162	4	8	using	use	VERB
ejpam-6162	4	9	linear	linear	ADJ
ejpam-6162	4	10	combinations	combination	NOUN
ejpam-6162	4	11	of	of	ADP
ejpam-6162	4	12	known	know	VERB
ejpam-6162	4	13	ridge	ridge	NOUN
ejpam-6162	4	14	parameters	parameter	NOUN
ejpam-6162	4	15	,	,	PUNCT
ejpam-6162	4	16	developed	develop	VERB
ejpam-6162	4	17	through	through	ADP
ejpam-6162	4	18	grid	grid	NOUN
ejpam-6162	4	19	search	search	NOUN
ejpam-6162	4	20	and	and	CCONJ
ejpam-6162	4	21	methods	method	NOUN
ejpam-6162	4	22	that	that	PRON
ejpam-6162	4	23	leverage	leverage	NOUN
ejpam-6162	4	24	mean	mean	VERB
ejpam-6162	4	25	squared	square	VERB
ejpam-6162	4	26	error	error	NOUN
ejpam-6162	4	27	(	(	PUNCT
ejpam-6162	4	28	mse	mse	NOUN
ejpam-6162	4	29	)	)	PUNCT
ejpam-6162	4	30	values	value	NOUN
ejpam-6162	4	31	from	from	ADP
ejpam-6162	4	32	prior	prior	ADJ
ejpam-6162	4	33	simulations	simulation	NOUN
ejpam-6162	4	34	.	.	PUNCT
ejpam-6162	5	1	the	the	DET
ejpam-6162	5	2	performance	performance	NOUN
ejpam-6162	5	3	of	of	ADP
ejpam-6162	5	4	each	each	DET
ejpam-6162	5	5	known	know	VERB
ejpam-6162	5	6	and	and	CCONJ
ejpam-6162	5	7	proposed	propose	VERB
ejpam-6162	5	8	estimators	estimator	NOUN
ejpam-6162	5	9	are	be	AUX
ejpam-6162	5	10	then	then	ADV
ejpam-6162	5	11	compared	compare	VERB
ejpam-6162	5	12	using	use	VERB
ejpam-6162	5	13	mse	mse	NOUN
ejpam-6162	5	14	criterion	criterion	NOUN
ejpam-6162	5	15	.	.	PUNCT
ejpam-6162	6	1	results	result	NOUN
ejpam-6162	6	2	show	show	VERB
ejpam-6162	6	3	that	that	SCONJ
ejpam-6162	6	4	the	the	DET
ejpam-6162	6	5	proposed	propose	VERB
ejpam-6162	6	6	estimators	estimator	NOUN
ejpam-6162	6	7	performed	perform	VERB
ejpam-6162	6	8	better	well	ADV
ejpam-6162	6	9	on	on	ADP
ejpam-6162	6	10	many	many	ADJ
ejpam-6162	6	11	cases	case	NOUN
ejpam-6162	6	12	.	.	PUNCT
ejpam-6162	7	1	furthermore	furthermore	ADV
ejpam-6162	7	2	,	,	PUNCT
ejpam-6162	7	3	each	each	DET
ejpam-6162	7	4	estimator	estimator	NOUN
ejpam-6162	7	5	was	be	AUX
ejpam-6162	7	6	applied	apply	VERB
ejpam-6162	7	7	to	to	ADP
ejpam-6162	7	8	secondary	secondary	ADJ
ejpam-6162	7	9	data	datum	NOUN
ejpam-6162	7	10	and	and	CCONJ
ejpam-6162	7	11	was	be	AUX
ejpam-6162	7	12	compared	compare	VERB
ejpam-6162	7	13	based	base	VERB
ejpam-6162	7	14	on	on	ADP
ejpam-6162	7	15	their	their	PRON
ejpam-6162	7	16	respective	respective	ADJ
ejpam-6162	7	17	estimated	estimate	VERB
ejpam-6162	7	18	coefficients	coefficient	NOUN
ejpam-6162	7	19	.	.	PUNCT
ejpam-6162	8	1	2020	2020	NUM
ejpam-6162	8	2	mathematics	mathematic	NOUN
ejpam-6162	8	3	subject	subject	NOUN
ejpam-6162	8	4	classifications	classification	NOUN
ejpam-6162	8	5	:	:	PUNCT
ejpam-6162	8	6	62j07	62j07	NUM
ejpam-6162	8	7	,	,	PUNCT
ejpam-6162	8	8	62j12	62j12	NUM
ejpam-6162	8	9	,	,	PUNCT
ejpam-6162	8	10	65c05	65c05	NOUN
ejpam-6162	8	11	key	key	ADJ
ejpam-6162	8	12	words	word	NOUN
ejpam-6162	8	13	and	and	CCONJ
ejpam-6162	8	14	phrases	phrase	NOUN
ejpam-6162	8	15	:	:	PUNCT
ejpam-6162	8	16	ridge	ridge	NOUN
ejpam-6162	8	17	regression	regression	PROPN
ejpam-6162	8	18	,	,	PUNCT
ejpam-6162	8	19	ridge	ridge	NOUN
ejpam-6162	8	20	parameter	parameter	NOUN
ejpam-6162	8	21	,	,	PUNCT
ejpam-6162	8	22	logistic	logistic	ADJ
ejpam-6162	8	23	regression	regression	NOUN
ejpam-6162	8	24	,	,	PUNCT
ejpam-6162	8	25	poisson	poisson	NOUN
ejpam-6162	8	26	regression	regression	NOUN
ejpam-6162	8	27	,	,	PUNCT
ejpam-6162	8	28	multiple	multiple	ADJ
ejpam-6162	8	29	regression	regression	NOUN
ejpam-6162	8	30	,	,	PUNCT
ejpam-6162	8	31	monte	monte	PROPN
ejpam-6162	8	32	carlo	carlo	PROPN
ejpam-6162	8	33	simulation	simulation	PROPN
ejpam-6162	8	34	,	,	PUNCT
ejpam-6162	8	35	stats	stat	VERB
ejpam-6162	8	36	r	r	NOUN
ejpam-6162	8	37	package	package	NOUN
ejpam-6162	8	38	1	1	NUM
ejpam-6162	8	39	.	.	PUNCT
ejpam-6162	9	1	introduction	introduction	NOUN
ejpam-6162	9	2	regression	regression	NOUN
ejpam-6162	9	3	analysis	analysis	NOUN
ejpam-6162	9	4	is	be	AUX
ejpam-6162	9	5	a	a	DET
ejpam-6162	9	6	powerful	powerful	ADJ
ejpam-6162	9	7	tool	tool	NOUN
ejpam-6162	9	8	in	in	ADP
ejpam-6162	9	9	statistics	statistic	NOUN
ejpam-6162	9	10	,	,	PUNCT
ejpam-6162	9	11	widely	widely	ADV
ejpam-6162	9	12	used	use	VERB
ejpam-6162	9	13	to	to	PART
ejpam-6162	9	14	model	model	VERB
ejpam-6162	9	15	relationships	relationship	NOUN
ejpam-6162	9	16	between	between	ADP
ejpam-6162	9	17	variables	variable	NOUN
ejpam-6162	9	18	.	.	PUNCT
ejpam-6162	10	1	however	however	ADV
ejpam-6162	10	2	,	,	PUNCT
ejpam-6162	10	3	challenges	challenge	NOUN
ejpam-6162	10	4	such	such	ADJ
ejpam-6162	10	5	as	as	ADP
ejpam-6162	10	6	multicollinearity	multicollinearity	NOUN
ejpam-6162	10	7	and	and	CCONJ
ejpam-6162	10	8	data	data	NOUN
ejpam-6162	10	9	-	-	PUNCT
ejpam-6162	10	10	specific	specific	ADJ
ejpam-6162	10	11	requirements	requirement	NOUN
ejpam-6162	10	12	can	can	AUX
ejpam-6162	10	13	limit	limit	VERB
ejpam-6162	10	14	the	the	DET
ejpam-6162	10	15	effectiveness	effectiveness	NOUN
ejpam-6162	10	16	of	of	ADP
ejpam-6162	10	17	traditional	traditional	ADJ
ejpam-6162	10	18	regression	regression	NOUN
ejpam-6162	10	19	methods	method	NOUN
ejpam-6162	10	20	.	.	PUNCT
ejpam-6162	11	1	in	in	ADP
ejpam-6162	11	2	response	response	NOUN
ejpam-6162	11	3	to	to	ADP
ejpam-6162	11	4	these	these	DET
ejpam-6162	11	5	challenges	challenge	NOUN
ejpam-6162	11	6	,	,	PUNCT
ejpam-6162	11	7	ridge	ridge	NOUN
ejpam-6162	11	8	regression	regression	NOUN
ejpam-6162	11	9	techniques	technique	NOUN
ejpam-6162	11	10	have	have	AUX
ejpam-6162	11	11	been	be	AUX
ejpam-6162	11	12	developed	develop	VERB
ejpam-6162	11	13	to	to	PART
ejpam-6162	11	14	enhance	enhance	VERB
ejpam-6162	11	15	model	model	NOUN
ejpam-6162	11	16	stability	stability	NOUN
ejpam-6162	11	17	and	and	CCONJ
ejpam-6162	11	18	accuracy	accuracy	NOUN
ejpam-6162	12	1	[	[	X
ejpam-6162	12	2	1	1	NUM
ejpam-6162	12	3	,	,	PUNCT
ejpam-6162	12	4	2	2	NUM
ejpam-6162	12	5	]	]	PUNCT
ejpam-6162	12	6	.	.	PUNCT
ejpam-6162	13	1	the	the	DET
ejpam-6162	13	2	general	general	ADJ
ejpam-6162	13	3	form	form	NOUN
ejpam-6162	13	4	of	of	ADP
ejpam-6162	13	5	ridge	ridge	NOUN
ejpam-6162	13	6	regression	regression	PROPN
ejpam-6162	13	7	applies	apply	VERB
ejpam-6162	13	8	an	an	DET
ejpam-6162	13	9	l2	l2	NOUN
ejpam-6162	13	10	penalty	penalty	NOUN
ejpam-6162	13	11	to	to	ADP
ejpam-6162	13	12	the	the	DET
ejpam-6162	13	13	coefficient	coefficient	NOUN
ejpam-6162	13	14	estimates	estimate	NOUN
ejpam-6162	13	15	,	,	PUNCT
ejpam-6162	13	16	modifying	modify	VERB
ejpam-6162	13	17	the	the	DET
ejpam-6162	13	18	standard	standard	ADJ
ejpam-6162	13	19	maximum	maximum	ADJ
ejpam-6162	13	20	likelihood	likelihood	NOUN
ejpam-6162	13	21	(	(	PUNCT
ejpam-6162	13	22	ml	ml	NOUN
ejpam-6162	13	23	)	)	PUNCT
ejpam-6162	13	24	estimation	estimation	NOUN
ejpam-6162	13	25	to	to	PART
ejpam-6162	13	26	control	control	VERB
ejpam-6162	13	27	overfitting	overfitting	NOUN
ejpam-6162	13	28	.	.	PUNCT
ejpam-6162	14	1	this	this	DET
ejpam-6162	14	2	paper	paper	NOUN
ejpam-6162	14	3	focuses	focus	VERB
ejpam-6162	14	4	on	on	ADP
ejpam-6162	14	5	logistic	logistic	ADJ
ejpam-6162	14	6	ridge	ridge	NOUN
ejpam-6162	14	7	regression	regression	NOUN
ejpam-6162	14	8	,	,	PUNCT
ejpam-6162	14	9	poisson	poisson	PROPN
ejpam-6162	14	10	ridge	ridge	PROPN
ejpam-6162	14	11	regression	regression	PROPN
ejpam-6162	14	12	,	,	PUNCT
ejpam-6162	14	13	and	and	CCONJ
ejpam-6162	14	14	multiple	multiple	ADJ
ejpam-6162	14	15	ridge	ridge	NOUN
ejpam-6162	14	16	regression	regression	NOUN
ejpam-6162	14	17	.	.	PUNCT
ejpam-6162	15	1	related	related	ADJ
ejpam-6162	15	2	studies	study	NOUN
ejpam-6162	15	3	are	be	AUX
ejpam-6162	15	4	found	find	VERB
ejpam-6162	15	5	in	in	ADP
ejpam-6162	15	6	[	[	X
ejpam-6162	15	7	3–8	3–8	NUM
ejpam-6162	15	8	]	]	SYM
ejpam-6162	15	9	.	.	PUNCT
ejpam-6162	16	1	doi	doi	NOUN
ejpam-6162	16	2	:	:	PUNCT
ejpam-6162	16	3	https://doi.org/10.29020/nybg.ejpam.v18i2.6162	https://doi.org/10.29020/nybg.ejpam.v18i2.6162	NOUN
ejpam-6162	16	4	email	email	NOUN
ejpam-6162	16	5	addresses	address	VERB
ejpam-6162	16	6	:	:	PUNCT
ejpam-6162	16	7	mohamad.jerson@wmsu.edu.ph	mohamad.jerson@wmsu.edu.ph	PROPN
ejpam-6162	16	8	(	(	PUNCT
ejpam-6162	16	9	j.	j.	PROPN
ejpam-6162	16	10	mohamad	mohamad	PROPN
ejpam-6162	16	11	)	)	PUNCT
ejpam-6162	16	12	,	,	PUNCT
ejpam-6162	16	13	angelyn.sanchez@wmsu.edu.ph	angelyn.sanchez@wmsu.edu.ph	PROPN
ejpam-6162	16	14	(	(	PUNCT
ejpam-6162	16	15	a.	a.	PROPN
ejpam-6162	16	16	delica	delica	PROPN
ejpam-6162	16	17	)	)	PUNCT
ejpam-6162	16	18	,	,	PUNCT
ejpam-6162	16	19	esperat.maydalyn@wmsu.edu.ph	esperat.maydalyn@wmsu.edu.ph	PROPN
ejpam-6162	16	20	(	(	PUNCT
ejpam-6162	16	21	m.	m.	PROPN
ejpam-6162	16	22	esperat	esperat	PROPN
ejpam-6162	16	23	)	)	PUNCT
ejpam-6162	16	24	,	,	PUNCT
ejpam-6162	16	25	aubrey.guerrero@wmsu.edu.ph	aubrey.guerrero@wmsu.edu.ph	PROPN
ejpam-6162	16	26	(	(	PUNCT
ejpam-6162	16	27	a.	a.	NOUN
ejpam-6162	16	28	labastilla	labastilla	PROPN
ejpam-6162	16	29	)	)	PUNCT
ejpam-6162	16	30	,	,	PUNCT
ejpam-6162	16	31	micubo.shiela@wmsu.edu.ph	micubo.shiela@wmsu.edu.ph	PROPN
ejpam-6162	16	32	(	(	PUNCT
ejpam-6162	16	33	s.	s.	PROPN
ejpam-6162	16	34	ledesma	ledesma	PROPN
ejpam-6162	16	35	)	)	PUNCT
ejpam-6162	16	36	,	,	PUNCT
ejpam-6162	16	37	doeyien.misil@wmsu.edu.ph	doeyien.misil@wmsu.edu.ph	PROPN
ejpam-6162	16	38	(	(	PUNCT
ejpam-6162	16	39	d.	d.	PROPN
ejpam-6162	16	40	misil	misil	PROPN
ejpam-6162	16	41	)	)	PUNCT
ejpam-6162	16	42	https://www.ejpam.com	https://www.ejpam.com	NOUN
ejpam-6162	17	1	1	1	NUM
ejpam-6162	17	2	copyright	copyright	NOUN
ejpam-6162	17	3	:	:	PUNCT
ejpam-6162	17	4	©	©	PROPN
ejpam-6162	17	5	2025	2025	NUM
ejpam-6162	17	6	the	the	DET
ejpam-6162	17	7	author(s	author(s	NOUN
ejpam-6162	17	8	)	)	PUNCT
ejpam-6162	17	9	.	.	PUNCT
ejpam-6162	18	1	(	(	PUNCT
ejpam-6162	18	2	cc	cc	NOUN
ejpam-6162	18	3	by	by	ADP
ejpam-6162	18	4	-	-	PUNCT
ejpam-6162	18	5	nc	nc	PROPN
ejpam-6162	18	6	4.0	4.0	NUM
ejpam-6162	18	7	)	)	PUNCT
ejpam-6162	18	8	j.	j.	PROPN
ejpam-6162	18	9	mohamad	mohamad	PROPN
ejpam-6162	18	10	,	,	PUNCT
ejpam-6162	18	11	et	et	PROPN
ejpam-6162	18	12	.	.	PUNCT
ejpam-6162	19	1	al	al	PROPN
ejpam-6162	19	2	.	.	PUNCT
ejpam-6162	19	3	/	/	SYM
ejpam-6162	19	4	eur	eur	PROPN
ejpam-6162	19	5	.	.	PUNCT
ejpam-6162	20	1	j.	j.	PROPN
ejpam-6162	20	2	pure	pure	PROPN
ejpam-6162	20	3	appl	appl	PROPN
ejpam-6162	20	4	.	.	PROPN
ejpam-6162	20	5	math	math	PROPN
ejpam-6162	20	6	,	,	PUNCT
ejpam-6162	20	7	18	18	NUM
ejpam-6162	20	8	(	(	PUNCT
ejpam-6162	20	9	2	2	NUM
ejpam-6162	20	10	)	)	PUNCT
ejpam-6162	20	11	(	(	PUNCT
ejpam-6162	20	12	2025	2025	NUM
ejpam-6162	20	13	)	)	PUNCT
ejpam-6162	20	14	,	,	PUNCT
ejpam-6162	20	15	6162	6162	NUM
ejpam-6162	20	16	2	2	NUM
ejpam-6162	20	17	of	of	ADP
ejpam-6162	20	18	10	10	NUM
ejpam-6162	20	19	logistic	logistic	ADJ
ejpam-6162	20	20	ridge	ridge	NOUN
ejpam-6162	20	21	regression	regression	NOUN
ejpam-6162	20	22	is	be	AUX
ejpam-6162	20	23	applied	apply	VERB
ejpam-6162	20	24	in	in	ADP
ejpam-6162	20	25	binary	binary	ADJ
ejpam-6162	20	26	classification	classification	NOUN
ejpam-6162	20	27	problems	problem	NOUN
ejpam-6162	20	28	.	.	PUNCT
ejpam-6162	21	1	the	the	DET
ejpam-6162	21	2	likelihood	likelihood	NOUN
ejpam-6162	21	3	function	function	NOUN
ejpam-6162	21	4	is	be	AUX
ejpam-6162	21	5	pi	pi	NOUN
ejpam-6162	21	6	=	=	SYM
ejpam-6162	21	7	1/(1	1/(1	PROPN
ejpam-6162	21	8	+	+	CCONJ
ejpam-6162	21	9	e−xt	e−xt	X
ejpam-6162	21	10	i	i	PROPN
ejpam-6162	21	11	β	β	NOUN
ejpam-6162	21	12	)	)	PUNCT
ejpam-6162	21	13	and	and	CCONJ
ejpam-6162	21	14	the	the	DET
ejpam-6162	21	15	ridge	ridge	NOUN
ejpam-6162	21	16	-	-	PUNCT
ejpam-6162	21	17	regularized	regularize	VERB
ejpam-6162	21	18	log	log	NOUN
ejpam-6162	21	19	-	-	PUNCT
ejpam-6162	21	20	likelihood	likelihood	NOUN
ejpam-6162	21	21	function	function	NOUN
ejpam-6162	21	22	is	be	AUX
ejpam-6162	21	23	j(β	j(β	NOUN
ejpam-6162	21	24	)	)	PUNCT
ejpam-6162	21	25	=	=	PUNCT
ejpam-6162	22	1	−	−	PROPN
ejpam-6162	22	2	n∑	n∑	NOUN
ejpam-6162	22	3	i=1	i=1	X
ejpam-6162	23	1	[	[	X
ejpam-6162	23	2	yi	yi	NUM
ejpam-6162	23	3	log(pi	log(pi	NOUN
ejpam-6162	23	4	)	)	PUNCT
ejpam-6162	23	5	+	+	CCONJ
ejpam-6162	23	6	(	(	PUNCT
ejpam-6162	23	7	1−	1−	NUM
ejpam-6162	23	8	yi	yi	NOUN
ejpam-6162	23	9	)	)	PUNCT
ejpam-6162	23	10	log(1−	log(1−	PROPN
ejpam-6162	23	11	pi	pi	PROPN
ejpam-6162	23	12	)	)	PUNCT
ejpam-6162	23	13	]	]	PUNCT
ejpam-6162	24	1	+	+	CCONJ
ejpam-6162	24	2	k	k	X
ejpam-6162	24	3	p∑	p∑	NOUN
ejpam-6162	24	4	j=1	j=1	PROPN
ejpam-6162	24	5	β2	β2	PROPN
ejpam-6162	24	6	j	j	PROPN
ejpam-6162	24	7	,	,	PUNCT
ejpam-6162	24	8	where	where	SCONJ
ejpam-6162	24	9	pi	pi	NOUN
ejpam-6162	24	10	represents	represent	VERB
ejpam-6162	24	11	the	the	DET
ejpam-6162	24	12	predicted	predict	VERB
ejpam-6162	24	13	probabilities	probability	NOUN
ejpam-6162	24	14	for	for	ADP
ejpam-6162	24	15	the	the	DET
ejpam-6162	24	16	outcome	outcome	NOUN
ejpam-6162	24	17	y	y	PROPN
ejpam-6162	24	18	,	,	PUNCT
ejpam-6162	24	19	n	n	PROPN
ejpam-6162	24	20	is	be	AUX
ejpam-6162	24	21	the	the	DET
ejpam-6162	24	22	number	number	NOUN
ejpam-6162	24	23	of	of	ADP
ejpam-6162	24	24	observations	observation	NOUN
ejpam-6162	24	25	,	,	PUNCT
ejpam-6162	24	26	p	p	PROPN
ejpam-6162	24	27	is	be	AUX
ejpam-6162	24	28	the	the	DET
ejpam-6162	24	29	number	number	NOUN
ejpam-6162	24	30	of	of	ADP
ejpam-6162	24	31	independent	independent	ADJ
ejpam-6162	24	32	variables	variable	NOUN
ejpam-6162	24	33	,	,	PUNCT
ejpam-6162	24	34	y	y	PROPN
ejpam-6162	24	35	is	be	AUX
ejpam-6162	24	36	the	the	DET
ejpam-6162	24	37	dependent	dependent	ADJ
ejpam-6162	24	38	n×	n×	PROPN
ejpam-6162	24	39	1	1	NUM
ejpam-6162	24	40	vector	vector	NOUN
ejpam-6162	24	41	,	,	PUNCT
ejpam-6162	24	42	x	x	X
ejpam-6162	24	43	is	be	AUX
ejpam-6162	24	44	the	the	DET
ejpam-6162	24	45	independent	independent	ADJ
ejpam-6162	24	46	n	n	NUM
ejpam-6162	24	47	×	×	NOUN
ejpam-6162	24	48	p	p	NOUN
ejpam-6162	24	49	matrix	matrix	NOUN
ejpam-6162	24	50	,	,	PUNCT
ejpam-6162	24	51	β	β	X
ejpam-6162	24	52	is	be	AUX
ejpam-6162	24	53	the	the	DET
ejpam-6162	24	54	p	p	ADJ
ejpam-6162	24	55	×	×	NOUN
ejpam-6162	24	56	1	1	NUM
ejpam-6162	24	57	coefficient	coefficient	NOUN
ejpam-6162	24	58	vector	vector	NOUN
ejpam-6162	24	59	,	,	PUNCT
ejpam-6162	24	60	and	and	CCONJ
ejpam-6162	24	61	k	k	PROPN
ejpam-6162	24	62	is	be	AUX
ejpam-6162	24	63	the	the	DET
ejpam-6162	24	64	ridge	ridge	NOUN
ejpam-6162	24	65	parameter	parameter	NOUN
ejpam-6162	24	66	.	.	PUNCT
ejpam-6162	25	1	poisson	poisson	PROPN
ejpam-6162	25	2	ridge	ridge	PROPN
ejpam-6162	25	3	regression	regression	PROPN
ejpam-6162	25	4	is	be	AUX
ejpam-6162	25	5	used	use	VERB
ejpam-6162	25	6	to	to	PART
ejpam-6162	25	7	model	model	VERB
ejpam-6162	25	8	count	count	NOUN
ejpam-6162	25	9	data	datum	NOUN
ejpam-6162	25	10	.	.	PUNCT
ejpam-6162	26	1	the	the	DET
ejpam-6162	26	2	likelihood	likelihood	NOUN
ejpam-6162	26	3	function	function	NOUN
ejpam-6162	26	4	is	be	AUX
ejpam-6162	26	5	l(β	l(β	PROPN
ejpam-6162	26	6	)	)	PUNCT
ejpam-6162	27	1	=	=	PUNCT
ejpam-6162	27	2	n∏	n∏	PROPN
ejpam-6162	27	3	i=1	i=1	PART
ejpam-6162	28	1	ex	ex	X
ejpam-6162	28	2	t	t	NOUN
ejpam-6162	29	1	i	i	PRON
ejpam-6162	29	2	βyi	βyi	PUNCT
ejpam-6162	29	3	yi	yi	PROPN
ejpam-6162	29	4	!	!	PUNCT
ejpam-6162	29	5	,	,	PUNCT
ejpam-6162	29	6	and	and	CCONJ
ejpam-6162	29	7	the	the	DET
ejpam-6162	29	8	ridge	ridge	NOUN
ejpam-6162	29	9	-	-	PUNCT
ejpam-6162	29	10	regularized	regularize	VERB
ejpam-6162	29	11	log	log	NOUN
ejpam-6162	29	12	-	-	PUNCT
ejpam-6162	29	13	likelihood	likelihood	NOUN
ejpam-6162	29	14	function	function	NOUN
ejpam-6162	29	15	is	be	AUX
ejpam-6162	29	16	j(β	j(β	NOUN
ejpam-6162	29	17	)	)	PUNCT
ejpam-6162	29	18	=	=	PUNCT
ejpam-6162	30	1	−	−	PROPN
ejpam-6162	30	2	n∑	n∑	NOUN
ejpam-6162	30	3	i=1	i=1	X
ejpam-6162	31	1	[	[	PUNCT
ejpam-6162	31	2	yi	yi	X
ejpam-6162	31	3	x	x	SYM
ejpam-6162	31	4	t	t	NOUN
ejpam-6162	31	5	i	i	INTJ
ejpam-6162	31	6	β	β	PROPN
ejpam-6162	32	1	−	−	X
ejpam-6162	32	2	ex	ex	X
ejpam-6162	33	1	t	t	NOUN
ejpam-6162	33	2	i	i	PRON
ejpam-6162	33	3	β	β	X
ejpam-6162	33	4	]	]	PUNCT
ejpam-6162	34	1	+	+	CCONJ
ejpam-6162	34	2	k	k	X
ejpam-6162	34	3	p∑	p∑	NOUN
ejpam-6162	35	1	j=1	j=1	PROPN
ejpam-6162	35	2	β2	β2	PROPN
ejpam-6162	35	3	j	j	PROPN
ejpam-6162	35	4	.	.	PUNCT
ejpam-6162	36	1	the	the	DET
ejpam-6162	36	2	coefficients	coefficient	NOUN
ejpam-6162	36	3	are	be	AUX
ejpam-6162	36	4	estimated	estimate	VERB
ejpam-6162	36	5	by	by	ADP
ejpam-6162	36	6	solving	solve	VERB
ejpam-6162	36	7	β̂ridge	β̂ridge	PUNCT
ejpam-6162	36	8	=	=	SYM
ejpam-6162	36	9	argmin	argmin	PROPN
ejpam-6162	36	10	β	β	X
ejpam-6162	36	11	j(β	j(β	PROPN
ejpam-6162	36	12	)	)	PUNCT
ejpam-6162	36	13	.	.	PUNCT
ejpam-6162	37	1	multiple	multiple	PROPN
ejpam-6162	37	2	ridge	ridge	PROPN
ejpam-6162	37	3	regression	regression	PROPN
ejpam-6162	37	4	applies	apply	VERB
ejpam-6162	37	5	the	the	DET
ejpam-6162	37	6	ridge	ridge	NOUN
ejpam-6162	37	7	penalty	penalty	NOUN
ejpam-6162	37	8	to	to	ADP
ejpam-6162	37	9	multiple	multiple	ADJ
ejpam-6162	37	10	linear	linear	ADJ
ejpam-6162	37	11	regression	regression	NOUN
ejpam-6162	37	12	,	,	PUNCT
ejpam-6162	37	13	which	which	PRON
ejpam-6162	37	14	models	model	VERB
ejpam-6162	37	15	the	the	DET
ejpam-6162	37	16	relationship	relationship	NOUN
ejpam-6162	37	17	between	between	ADP
ejpam-6162	37	18	a	a	DET
ejpam-6162	37	19	continuous	continuous	ADJ
ejpam-6162	37	20	dependent	dependent	ADJ
ejpam-6162	37	21	variable	variable	NOUN
ejpam-6162	37	22	and	and	CCONJ
ejpam-6162	37	23	multiple	multiple	ADJ
ejpam-6162	37	24	predictors	predictor	NOUN
ejpam-6162	37	25	.	.	PUNCT
ejpam-6162	38	1	the	the	DET
ejpam-6162	38	2	ridge	ridge	NOUN
ejpam-6162	38	3	estimator	estimator	NOUN
ejpam-6162	38	4	modifies	modify	VERB
ejpam-6162	38	5	the	the	DET
ejpam-6162	38	6	ordinary	ordinary	ADJ
ejpam-6162	38	7	least	least	ADJ
ejpam-6162	38	8	squares	square	NOUN
ejpam-6162	38	9	(	(	PUNCT
ejpam-6162	38	10	ols	ol	NOUN
ejpam-6162	38	11	)	)	PUNCT
ejpam-6162	38	12	estimator	estimator	NOUN
ejpam-6162	38	13	:	:	PUNCT
ejpam-6162	38	14	β̂ridge	β̂ridge	X
ejpam-6162	39	1	=	=	SYM
ejpam-6162	39	2	(	(	PUNCT
ejpam-6162	39	3	xtx	xtx	PROPN
ejpam-6162	39	4	+	+	PROPN
ejpam-6162	39	5	ki)−1xty	ki)−1xty	PROPN
ejpam-6162	39	6	2	2	NUM
ejpam-6162	39	7	.	.	PUNCT
ejpam-6162	39	8	methodology	methodology	NOUN
ejpam-6162	39	9	this	this	DET
ejpam-6162	39	10	study	study	NOUN
ejpam-6162	39	11	investigates	investigate	VERB
ejpam-6162	39	12	the	the	DET
ejpam-6162	39	13	performance	performance	NOUN
ejpam-6162	39	14	of	of	ADP
ejpam-6162	39	15	ridge	ridge	NOUN
ejpam-6162	39	16	-	-	PUNCT
ejpam-6162	39	17	regularized	regularize	VERB
ejpam-6162	39	18	estimators	estimator	NOUN
ejpam-6162	39	19	applied	apply	VERB
ejpam-6162	39	20	to	to	ADP
ejpam-6162	39	21	logistic	logistic	ADJ
ejpam-6162	39	22	regression	regression	NOUN
ejpam-6162	39	23	,	,	PUNCT
ejpam-6162	39	24	poisson	poisson	NOUN
ejpam-6162	39	25	regression	regression	NOUN
ejpam-6162	39	26	,	,	PUNCT
ejpam-6162	39	27	and	and	CCONJ
ejpam-6162	39	28	multiple	multiple	ADJ
ejpam-6162	39	29	linear	linear	ADJ
ejpam-6162	39	30	regression	regression	NOUN
ejpam-6162	39	31	models	model	NOUN
ejpam-6162	39	32	in	in	ADP
ejpam-6162	39	33	the	the	DET
ejpam-6162	39	34	presence	presence	NOUN
ejpam-6162	39	35	of	of	ADP
ejpam-6162	39	36	multicollinearity	multicollinearity	NOUN
ejpam-6162	39	37	.	.	PUNCT
ejpam-6162	40	1	the	the	DET
ejpam-6162	40	2	objective	objective	NOUN
ejpam-6162	40	3	is	be	AUX
ejpam-6162	40	4	to	to	PART
ejpam-6162	40	5	compare	compare	VERB
ejpam-6162	40	6	several	several	ADJ
ejpam-6162	40	7	known	know	VERB
ejpam-6162	40	8	ridge	ridge	NOUN
ejpam-6162	40	9	parameter	parameter	NOUN
ejpam-6162	40	10	estimators	estimator	NOUN
ejpam-6162	40	11	and	and	CCONJ
ejpam-6162	40	12	newly	newly	ADV
ejpam-6162	40	13	proposed	propose	VERB
ejpam-6162	40	14	ones	one	NOUN
ejpam-6162	40	15	based	base	VERB
ejpam-6162	40	16	on	on	ADP
ejpam-6162	40	17	their	their	PRON
ejpam-6162	40	18	ability	ability	NOUN
ejpam-6162	40	19	to	to	PART
ejpam-6162	40	20	minimize	minimize	VERB
ejpam-6162	40	21	the	the	DET
ejpam-6162	40	22	mean	mean	ADJ
ejpam-6162	40	23	squared	square	VERB
ejpam-6162	40	24	error	error	NOUN
ejpam-6162	40	25	(	(	PUNCT
ejpam-6162	40	26	mse	mse	NOUN
ejpam-6162	40	27	)	)	PUNCT
ejpam-6162	40	28	of	of	ADP
ejpam-6162	40	29	coefficient	coefficient	NOUN
ejpam-6162	40	30	estimates	estimate	NOUN
ejpam-6162	40	31	.	.	PUNCT
ejpam-6162	41	1	a	a	DET
ejpam-6162	41	2	monte	monte	PROPN
ejpam-6162	41	3	carlo	carlo	PROPN
ejpam-6162	41	4	simulation	simulation	NOUN
ejpam-6162	41	5	framework	framework	NOUN
ejpam-6162	41	6	is	be	AUX
ejpam-6162	41	7	employed	employ	VERB
ejpam-6162	41	8	for	for	ADP
ejpam-6162	41	9	the	the	DET
ejpam-6162	41	10	evaluation	evaluation	NOUN
ejpam-6162	41	11	.	.	PUNCT
ejpam-6162	42	1	2.1	2.1	NUM
ejpam-6162	42	2	.	.	PUNCT
ejpam-6162	42	3	theoretical	theoretical	ADJ
ejpam-6162	42	4	framework	framework	NOUN
ejpam-6162	42	5	for	for	ADP
ejpam-6162	42	6	ridge	ridge	NOUN
ejpam-6162	42	7	estimation	estimation	PROPN
ejpam-6162	42	8	the	the	DET
ejpam-6162	42	9	ridge	ridge	NOUN
ejpam-6162	42	10	estimator	estimator	NOUN
ejpam-6162	42	11	for	for	ADP
ejpam-6162	42	12	the	the	DET
ejpam-6162	42	13	regression	regression	NOUN
ejpam-6162	42	14	coefficients	coefficient	NOUN
ejpam-6162	42	15	β	β	X
ejpam-6162	42	16	is	be	AUX
ejpam-6162	42	17	β̂ridge	β̂ridge	PUNCT
ejpam-6162	43	1	=	=	SYM
ejpam-6162	43	2	(	(	PUNCT
ejpam-6162	43	3	xtx	xtx	PROPN
ejpam-6162	43	4	+	+	PROPN
ejpam-6162	43	5	ki)−1xty	ki)−1xty	PROPN
ejpam-6162	43	6	j.	j.	PROPN
ejpam-6162	43	7	mohamad	mohamad	PROPN
ejpam-6162	43	8	,	,	PUNCT
ejpam-6162	43	9	et	et	PROPN
ejpam-6162	43	10	.	.	PUNCT
ejpam-6162	44	1	al	al	PROPN
ejpam-6162	44	2	.	.	PUNCT
ejpam-6162	44	3	/	/	SYM
ejpam-6162	44	4	eur	eur	PROPN
ejpam-6162	44	5	.	.	PUNCT
ejpam-6162	45	1	j.	j.	PROPN
ejpam-6162	45	2	pure	pure	PROPN
ejpam-6162	45	3	appl	appl	PROPN
ejpam-6162	45	4	.	.	PROPN
ejpam-6162	45	5	math	math	PROPN
ejpam-6162	45	6	,	,	PUNCT
ejpam-6162	45	7	18	18	NUM
ejpam-6162	45	8	(	(	PUNCT
ejpam-6162	45	9	2	2	NUM
ejpam-6162	45	10	)	)	PUNCT
ejpam-6162	45	11	(	(	PUNCT
ejpam-6162	45	12	2025	2025	NUM
ejpam-6162	45	13	)	)	PUNCT
ejpam-6162	45	14	,	,	PUNCT
ejpam-6162	45	15	6162	6162	NUM
ejpam-6162	45	16	3	3	NUM
ejpam-6162	45	17	of	of	ADP
ejpam-6162	45	18	10	10	NUM
ejpam-6162	45	19	where	where	SCONJ
ejpam-6162	45	20	k	k	PROPN
ejpam-6162	45	21	>	>	X
ejpam-6162	45	22	0	0	NUM
ejpam-6162	45	23	is	be	AUX
ejpam-6162	45	24	the	the	DET
ejpam-6162	45	25	ridge	ridge	NOUN
ejpam-6162	45	26	parameter	parameter	NOUN
ejpam-6162	45	27	,	,	PUNCT
ejpam-6162	45	28	i	i	PRON
ejpam-6162	45	29	is	be	AUX
ejpam-6162	45	30	the	the	DET
ejpam-6162	45	31	p×	p×	PROPN
ejpam-6162	45	32	p	p	NOUN
ejpam-6162	45	33	identity	identity	NOUN
ejpam-6162	45	34	matrix	matrix	NOUN
ejpam-6162	45	35	,	,	PUNCT
ejpam-6162	45	36	and	and	CCONJ
ejpam-6162	45	37	x	x	X
ejpam-6162	45	38	is	be	AUX
ejpam-6162	45	39	the	the	DET
ejpam-6162	45	40	matrix	matrix	NOUN
ejpam-6162	45	41	of	of	ADP
ejpam-6162	45	42	predictors	predictor	NOUN
ejpam-6162	45	43	.	.	PUNCT
ejpam-6162	46	1	this	this	DET
ejpam-6162	46	2	estimator	estimator	NOUN
ejpam-6162	46	3	is	be	AUX
ejpam-6162	46	4	particularly	particularly	ADV
ejpam-6162	46	5	useful	useful	ADJ
ejpam-6162	46	6	in	in	ADP
ejpam-6162	46	7	the	the	DET
ejpam-6162	46	8	presence	presence	NOUN
ejpam-6162	46	9	of	of	ADP
ejpam-6162	46	10	multicollinearity	multicollinearity	NOUN
ejpam-6162	46	11	,	,	PUNCT
ejpam-6162	46	12	where	where	SCONJ
ejpam-6162	46	13	the	the	DET
ejpam-6162	46	14	ols	ol	NOUN
ejpam-6162	46	15	estimator	estimator	NOUN
ejpam-6162	46	16	becomes	become	VERB
ejpam-6162	46	17	unstable	unstable	ADJ
ejpam-6162	46	18	.	.	PUNCT
ejpam-6162	47	1	to	to	PART
ejpam-6162	47	2	analyze	analyze	VERB
ejpam-6162	47	3	the	the	DET
ejpam-6162	47	4	effect	effect	NOUN
ejpam-6162	47	5	of	of	ADP
ejpam-6162	47	6	ridge	ridge	NOUN
ejpam-6162	47	7	regularization	regularization	NOUN
ejpam-6162	47	8	,	,	PUNCT
ejpam-6162	47	9	we	we	PRON
ejpam-6162	47	10	express	express	VERB
ejpam-6162	47	11	the	the	DET
ejpam-6162	47	12	linear	linear	ADJ
ejpam-6162	47	13	model	model	NOUN
ejpam-6162	47	14	using	use	VERB
ejpam-6162	47	15	spectral	spectral	ADJ
ejpam-6162	47	16	decomposition	decomposition	NOUN
ejpam-6162	47	17	.	.	PUNCT
ejpam-6162	48	1	let	let	VERB
ejpam-6162	48	2	the	the	DET
ejpam-6162	48	3	matrix	matrix	NOUN
ejpam-6162	48	4	xtx	xtx	PROPN
ejpam-6162	48	5	have	have	VERB
ejpam-6162	48	6	eigen	eigen	NOUN
ejpam-6162	48	7	-	-	PUNCT
ejpam-6162	48	8	decomposition	decomposition	NOUN
ejpam-6162	48	9	:	:	PUNCT
ejpam-6162	49	1	xtx	xtx	X
ejpam-6162	49	2	=	=	PUNCT
ejpam-6162	50	1	dλdt	dλdt	INTJ
ejpam-6162	50	2	,	,	PUNCT
ejpam-6162	50	3	where	where	SCONJ
ejpam-6162	50	4	d	d	NOUN
ejpam-6162	50	5	is	be	AUX
ejpam-6162	50	6	an	an	DET
ejpam-6162	50	7	orthogonal	orthogonal	ADJ
ejpam-6162	50	8	matrix	matrix	NOUN
ejpam-6162	50	9	of	of	ADP
ejpam-6162	50	10	eigenvectors	eigenvector	NOUN
ejpam-6162	50	11	and	and	CCONJ
ejpam-6162	50	12	λ	λ	NOUN
ejpam-6162	50	13	=	=	SYM
ejpam-6162	50	14	diag(λ1	diag(λ1	NOUN
ejpam-6162	50	15	,	,	PUNCT
ejpam-6162	50	16	λ2	λ2	NOUN
ejpam-6162	50	17	,	,	PUNCT
ejpam-6162	50	18	.	.	PUNCT
ejpam-6162	50	19	.	.	PUNCT
ejpam-6162	51	1	.	.	PUNCT
ejpam-6162	52	1	,	,	PUNCT
ejpam-6162	52	2	λp	λp	X
ejpam-6162	52	3	)	)	PUNCT
ejpam-6162	52	4	contains	contain	VERB
ejpam-6162	52	5	the	the	DET
ejpam-6162	52	6	eigenvalues	eigenvalue	NOUN
ejpam-6162	52	7	of	of	ADP
ejpam-6162	52	8	xtx	xtx	PROPN
ejpam-6162	52	9	.	.	PUNCT
ejpam-6162	53	1	defining	define	VERB
ejpam-6162	53	2	z	z	PROPN
ejpam-6162	53	3	=	=	PUNCT
ejpam-6162	53	4	xd	xd	INTJ
ejpam-6162	53	5	and	and	CCONJ
ejpam-6162	53	6	α	α	NOUN
ejpam-6162	53	7	=	=	NOUN
ejpam-6162	53	8	dtβ	dtβ	NOUN
ejpam-6162	53	9	,	,	PUNCT
ejpam-6162	53	10	the	the	DET
ejpam-6162	53	11	model	model	NOUN
ejpam-6162	53	12	becomes	become	VERB
ejpam-6162	53	13	:	:	PUNCT
ejpam-6162	53	14	y	y	PROPN
ejpam-6162	53	15	=	=	SYM
ejpam-6162	53	16	zα+	zα+	PROPN
ejpam-6162	53	17	ε	ε	PROPN
ejpam-6162	53	18	.	.	PUNCT
ejpam-6162	54	1	the	the	DET
ejpam-6162	54	2	ridge	ridge	NOUN
ejpam-6162	54	3	estimator	estimator	NOUN
ejpam-6162	54	4	of	of	ADP
ejpam-6162	54	5	α	α	PROPN
ejpam-6162	54	6	is	be	AUX
ejpam-6162	54	7	:	:	PUNCT
ejpam-6162	54	8	α̂(k	α̂(k	NOUN
ejpam-6162	54	9	)	)	PUNCT
ejpam-6162	54	10	=	=	SYM
ejpam-6162	54	11	(	(	PUNCT
ejpam-6162	54	12	ztz	ztz	NOUN
ejpam-6162	54	13	+	+	X
ejpam-6162	54	14	ki)−1zty	ki)−1zty	PROPN
ejpam-6162	54	15	.	.	PUNCT
ejpam-6162	55	1	the	the	DET
ejpam-6162	55	2	mean	mean	ADJ
ejpam-6162	55	3	squared	square	VERB
ejpam-6162	55	4	error	error	NOUN
ejpam-6162	55	5	(	(	PUNCT
ejpam-6162	55	6	mse	mse	NOUN
ejpam-6162	55	7	)	)	PUNCT
ejpam-6162	55	8	of	of	ADP
ejpam-6162	55	9	α̂(k	α̂(k	NOUN
ejpam-6162	55	10	)	)	PUNCT
ejpam-6162	55	11	can	can	AUX
ejpam-6162	55	12	be	be	AUX
ejpam-6162	55	13	decomposed	decompose	VERB
ejpam-6162	55	14	into	into	ADP
ejpam-6162	55	15	variance	variance	NOUN
ejpam-6162	55	16	and	and	CCONJ
ejpam-6162	55	17	bias	bias	NOUN
ejpam-6162	55	18	components	component	NOUN
ejpam-6162	55	19	and	and	CCONJ
ejpam-6162	55	20	is	be	AUX
ejpam-6162	55	21	given	give	VERB
ejpam-6162	55	22	by	by	ADP
ejpam-6162	55	23	:	:	PUNCT
ejpam-6162	55	24	mse(α̂(k	mse(α̂(k	NOUN
ejpam-6162	55	25	)	)	PUNCT
ejpam-6162	55	26	)	)	PUNCT
ejpam-6162	56	1	=	=	SYM
ejpam-6162	56	2	σ2	σ2	PROPN
ejpam-6162	56	3	p∑	p∑	PROPN
ejpam-6162	57	1	i=1	i=1	PROPN
ejpam-6162	57	2	(	(	PUNCT
ejpam-6162	57	3	λi	λi	X
ejpam-6162	57	4	λi	λi	X
ejpam-6162	57	5	+	+	X
ejpam-6162	57	6	k	k	X
ejpam-6162	57	7	)	)	PUNCT
ejpam-6162	57	8	2	2	X
ejpam-6162	58	1	+	+	NUM
ejpam-6162	58	2	p∑	p∑	NOUN
ejpam-6162	58	3	i=1	i=1	PROPN
ejpam-6162	58	4	(	(	PUNCT
ejpam-6162	58	5	kα2	kα2	NOUN
ejpam-6162	59	1	i	i	PRON
ejpam-6162	59	2	λi	λi	VERB
ejpam-6162	59	3	+	+	X
ejpam-6162	59	4	k	k	X
ejpam-6162	59	5	)	)	PUNCT
ejpam-6162	59	6	2	2	NUM
ejpam-6162	59	7	,	,	PUNCT
ejpam-6162	59	8	where	where	SCONJ
ejpam-6162	59	9	σ2	σ2	PROPN
ejpam-6162	59	10	is	be	AUX
ejpam-6162	59	11	the	the	DET
ejpam-6162	59	12	error	error	NOUN
ejpam-6162	59	13	variance	variance	NOUN
ejpam-6162	59	14	,	,	PUNCT
ejpam-6162	59	15	and	and	CCONJ
ejpam-6162	59	16	αi	αi	VERB
ejpam-6162	59	17	is	be	AUX
ejpam-6162	59	18	the	the	DET
ejpam-6162	59	19	ith	ith	PROPN
ejpam-6162	59	20	element	element	NOUN
ejpam-6162	59	21	of	of	ADP
ejpam-6162	59	22	α	α	PROPN
ejpam-6162	59	23	.	.	PUNCT
ejpam-6162	60	1	in	in	ADP
ejpam-6162	60	2	practice	practice	NOUN
ejpam-6162	60	3	,	,	PUNCT
ejpam-6162	60	4	since	since	SCONJ
ejpam-6162	60	5	σ2	σ2	NOUN
ejpam-6162	60	6	and	and	CCONJ
ejpam-6162	60	7	α	α	NOUN
ejpam-6162	60	8	are	be	AUX
ejpam-6162	60	9	unknown	unknown	ADJ
ejpam-6162	60	10	,	,	PUNCT
ejpam-6162	60	11	the	the	DET
ejpam-6162	60	12	estimated	estimate	VERB
ejpam-6162	60	13	mse	mse	NOUN
ejpam-6162	60	14	used	use	VERB
ejpam-6162	60	15	for	for	ADP
ejpam-6162	60	16	comparison	comparison	NOUN
ejpam-6162	60	17	is	be	AUX
ejpam-6162	60	18	:	:	PUNCT
ejpam-6162	60	19	m̂se(α̂(k	m̂se(α̂(k	PROPN
ejpam-6162	60	20	)	)	PUNCT
ejpam-6162	60	21	)	)	PUNCT
ejpam-6162	61	1	=	=	PUNCT
ejpam-6162	61	2	σ̂2	σ̂2	NOUN
ejpam-6162	62	1	p∑	p∑	X
ejpam-6162	62	2	i=1	i=1	PROPN
ejpam-6162	63	1	(	(	PUNCT
ejpam-6162	63	2	λi	λi	X
ejpam-6162	63	3	λi	λi	X
ejpam-6162	63	4	+	+	X
ejpam-6162	63	5	k	k	X
ejpam-6162	63	6	)	)	PUNCT
ejpam-6162	63	7	2	2	X
ejpam-6162	64	1	+	+	NUM
ejpam-6162	64	2	p∑	p∑	NOUN
ejpam-6162	64	3	i=1	i=1	PROPN
ejpam-6162	65	1	(	(	PUNCT
ejpam-6162	65	2	kα̂2	kα̂2	NOUN
ejpam-6162	65	3	i	i	PRON
ejpam-6162	65	4	λi	λi	X
ejpam-6162	65	5	+	+	X
ejpam-6162	65	6	k	k	X
ejpam-6162	65	7	)	)	PUNCT
ejpam-6162	65	8	2	2	X
ejpam-6162	65	9	.	.	PUNCT
ejpam-6162	66	1	this	this	DET
ejpam-6162	66	2	framework	framework	NOUN
ejpam-6162	66	3	is	be	AUX
ejpam-6162	66	4	also	also	ADV
ejpam-6162	66	5	extended	extend	VERB
ejpam-6162	66	6	to	to	PART
ejpam-6162	66	7	logistic	logistic	VERB
ejpam-6162	66	8	and	and	CCONJ
ejpam-6162	66	9	poisson	poisson	NOUN
ejpam-6162	66	10	regression	regression	NOUN
ejpam-6162	66	11	models	model	NOUN
ejpam-6162	66	12	via	via	ADP
ejpam-6162	66	13	their	their	PRON
ejpam-6162	66	14	respective	respective	ADJ
ejpam-6162	66	15	iterative	iterative	NOUN
ejpam-6162	66	16	methods	method	NOUN
ejpam-6162	66	17	of	of	ADP
ejpam-6162	66	18	approximations	approximation	NOUN
ejpam-6162	66	19	.	.	PUNCT
ejpam-6162	67	1	for	for	ADP
ejpam-6162	67	2	these	these	DET
ejpam-6162	67	3	models	model	NOUN
ejpam-6162	67	4	,	,	PUNCT
ejpam-6162	67	5	the	the	DET
ejpam-6162	67	6	mse	mse	NOUN
ejpam-6162	67	7	is	be	AUX
ejpam-6162	67	8	computed	compute	VERB
ejpam-6162	67	9	based	base	VERB
ejpam-6162	67	10	on	on	ADP
ejpam-6162	67	11	the	the	DET
ejpam-6162	67	12	penalized	penalize	VERB
ejpam-6162	67	13	likelihood	likelihood	NOUN
ejpam-6162	67	14	estimates	estimate	NOUN
ejpam-6162	67	15	of	of	ADP
ejpam-6162	67	16	β̂.	β̂.	PROPN
ejpam-6162	67	17	2.2	2.2	NUM
ejpam-6162	67	18	.	.	PUNCT
ejpam-6162	67	19	ridge	ridge	NOUN
ejpam-6162	67	20	parameter	parameter	PROPN
ejpam-6162	67	21	estimators	estimator	VERB
ejpam-6162	67	22	the	the	DET
ejpam-6162	67	23	following	follow	VERB
ejpam-6162	67	24	are	be	AUX
ejpam-6162	67	25	the	the	DET
ejpam-6162	67	26	known	know	VERB
ejpam-6162	67	27	ridge	ridge	NOUN
ejpam-6162	67	28	parameters	parameter	NOUN
ejpam-6162	67	29	compared	compare	VERB
ejpam-6162	67	30	in	in	ADP
ejpam-6162	67	31	this	this	DET
ejpam-6162	67	32	simulation	simulation	NOUN
ejpam-6162	67	33	study	study	NOUN
ejpam-6162	67	34	:	:	PUNCT
ejpam-6162	67	35	hk	hk	PROPN
ejpam-6162	67	36	=	=	SYM
ejpam-6162	67	37	k1	k1	PROPN
ejpam-6162	67	38	=	=	SYM
ejpam-6162	67	39	k̂hk1	k̂hk1	PROPN
ejpam-6162	67	40	=	=	PROPN
ejpam-6162	67	41	σ2	σ2	PROPN
ejpam-6162	67	42	a2max	a2max	PROPN
ejpam-6162	67	43	,	,	PUNCT
ejpam-6162	67	44	where	where	SCONJ
ejpam-6162	67	45	σ2	σ2	NOUN
ejpam-6162	67	46	=	=	SYM
ejpam-6162	67	47	∑n	∑n	PROPN
ejpam-6162	67	48	i=1(yi	i=1(yi	PRON
ejpam-6162	67	49	−	−	NOUN
ejpam-6162	67	50	µ̂i	µ̂i	NUM
ejpam-6162	67	51	)	)	PUNCT
ejpam-6162	67	52	2	2	NUM
ejpam-6162	67	53	n−	n−	NOUN
ejpam-6162	67	54	p−	p−	NOUN
ejpam-6162	67	55	1	1	NUM
ejpam-6162	68	1	[	[	X
ejpam-6162	68	2	1	1	NUM
ejpam-6162	68	3	]	]	PUNCT
ejpam-6162	68	4	;	;	PUNCT
ejpam-6162	68	5	k2	k2	PROPN
ejpam-6162	68	6	=	=	PROPN
ejpam-6162	68	7	k̂hkm	k̂hkm	PROPN
ejpam-6162	68	8	=	=	NOUN
ejpam-6162	68	9	1	1	NUM
ejpam-6162	68	10	a2max	a2max	NOUN
ejpam-6162	68	11	[	[	X
ejpam-6162	68	12	2	2	NUM
ejpam-6162	68	13	]	]	PUNCT
ejpam-6162	68	14	;	;	PUNCT
ejpam-6162	68	15	k3	k3	PROPN
ejpam-6162	68	16	=	=	SYM
ejpam-6162	68	17	k̂gm	k̂gm	NOUN
ejpam-6162	68	18	=	=	PUNCT
ejpam-6162	68	19	σ2(∏p	σ2(∏p	VERB
ejpam-6162	68	20	i=1	i=1	PRON
ejpam-6162	68	21	a	a	DET
ejpam-6162	68	22	2	2	NUM
ejpam-6162	68	23	i	i	NOUN
ejpam-6162	68	24	)	)	PUNCT
ejpam-6162	68	25	1	1	X
ejpam-6162	68	26	/	/	SYM
ejpam-6162	68	27	p	p	X
ejpam-6162	69	1	[	[	X
ejpam-6162	69	2	9	9	NUM
ejpam-6162	69	3	]	]	PUNCT
ejpam-6162	69	4	;	;	PUNCT
ejpam-6162	69	5	k4	k4	NOUN
ejpam-6162	69	6	=	=	SYM
ejpam-6162	69	7	k̂med	k̂med	PROPN
ejpam-6162	69	8	=	=	PUNCT
ejpam-6162	69	9	median(m2	median(m2	NOUN
ejpam-6162	69	10	i	i	NOUN
ejpam-6162	69	11	)	)	PUNCT
ejpam-6162	69	12	,	,	PUNCT
ejpam-6162	69	13	where	where	SCONJ
ejpam-6162	69	14	mi	mi	PROPN
ejpam-6162	69	15	=	=	PROPN
ejpam-6162	69	16	σ2	σ2	PROPN
ejpam-6162	69	17	a2i	a2i	NOUN
ejpam-6162	69	18	[	[	X
ejpam-6162	69	19	10	10	NUM
ejpam-6162	69	20	]	]	PUNCT
ejpam-6162	69	21	;	;	PUNCT
ejpam-6162	69	22	j.	j.	PROPN
ejpam-6162	69	23	mohamad	mohamad	PROPN
ejpam-6162	69	24	,	,	PUNCT
ejpam-6162	69	25	et	et	PROPN
ejpam-6162	69	26	.	.	PUNCT
ejpam-6162	69	27	al	al	PROPN
ejpam-6162	69	28	.	.	PUNCT
ejpam-6162	69	29	/	/	SYM
ejpam-6162	69	30	eur	eur	PROPN
ejpam-6162	69	31	.	.	PUNCT
ejpam-6162	70	1	j.	j.	PROPN
ejpam-6162	70	2	pure	pure	PROPN
ejpam-6162	70	3	appl	appl	PROPN
ejpam-6162	70	4	.	.	PROPN
ejpam-6162	70	5	math	math	PROPN
ejpam-6162	70	6	,	,	PUNCT
ejpam-6162	70	7	18	18	NUM
ejpam-6162	70	8	(	(	PUNCT
ejpam-6162	70	9	2	2	NUM
ejpam-6162	70	10	)	)	PUNCT
ejpam-6162	70	11	(	(	PUNCT
ejpam-6162	70	12	2025	2025	NUM
ejpam-6162	70	13	)	)	PUNCT
ejpam-6162	70	14	,	,	PUNCT
ejpam-6162	70	15	6162	6162	NUM
ejpam-6162	70	16	4	4	NUM
ejpam-6162	70	17	of	of	ADP
ejpam-6162	70	18	10	10	NUM
ejpam-6162	70	19	k5	k5	NOUN
ejpam-6162	70	20	=	=	SYM
ejpam-6162	70	21	k̂ss	k̂ss	PROPN
ejpam-6162	71	1	=	=	PUNCT
ejpam-6162	71	2	max(si	max(si	PROPN
ejpam-6162	71	3	)	)	PUNCT
ejpam-6162	71	4	,	,	PUNCT
ejpam-6162	71	5	where	where	SCONJ
ejpam-6162	71	6	si	si	PROPN
ejpam-6162	71	7	=	=	PRON
ejpam-6162	71	8	tiσ	tiσ	PROPN
ejpam-6162	71	9	2	2	NUM
ejpam-6162	72	1	(	(	PUNCT
ejpam-6162	72	2	n−	n−	NOUN
ejpam-6162	72	3	p)σ2	p)σ2	VERB
ejpam-6162	72	4	+	+	CCONJ
ejpam-6162	72	5	tia2i	tia2i	X
ejpam-6162	73	1	[	[	X
ejpam-6162	73	2	10	10	NUM
ejpam-6162	73	3	]	]	X
ejpam-6162	73	4	;	;	PUNCT
ejpam-6162	73	5	k6	k6	PROPN
ejpam-6162	73	6	=	=	SYM
ejpam-6162	73	7	k̂km2	k̂km2	PROPN
ejpam-6162	73	8	=	=	PUNCT
ejpam-6162	73	9	max	max	PROPN
ejpam-6162	73	10	(	(	PUNCT
ejpam-6162	73	11	1	1	NUM
ejpam-6162	73	12	mi	mi	NOUN
ejpam-6162	73	13	)	)	PUNCT
ejpam-6162	74	1	[	[	X
ejpam-6162	74	2	11	11	NUM
ejpam-6162	74	3	]	]	PUNCT
ejpam-6162	74	4	;	;	PUNCT
ejpam-6162	75	1	k7	k7	PROPN
ejpam-6162	75	2	=	=	PUNCT
ejpam-6162	75	3	k̂km4	k̂km4	PROPN
ejpam-6162	75	4	=	=	PUNCT
ejpam-6162	75	5	(	(	PUNCT
ejpam-6162	75	6	p∏	p∏	PROPN
ejpam-6162	75	7	i=1	i=1	PROPN
ejpam-6162	75	8	1	1	NUM
ejpam-6162	75	9	mi	mi	PROPN
ejpam-6162	75	10	)	)	PUNCT
ejpam-6162	75	11	1	1	NUM
ejpam-6162	75	12	/	/	SYM
ejpam-6162	75	13	p	p	X
ejpam-6162	76	1	[	[	X
ejpam-6162	76	2	11	11	NUM
ejpam-6162	76	3	]	]	X
ejpam-6162	76	4	;	;	PUNCT
ejpam-6162	76	5	k8	k8	X
ejpam-6162	76	6	=	=	SYM
ejpam-6162	76	7	k̂km5	k̂km5	PROPN
ejpam-6162	76	8	=	=	SYM
ejpam-6162	76	9	median	median	NOUN
ejpam-6162	76	10	(	(	PUNCT
ejpam-6162	76	11	1	1	NUM
ejpam-6162	76	12	mi	mi	PROPN
ejpam-6162	76	13	)	)	PUNCT
ejpam-6162	77	1	[	[	X
ejpam-6162	77	2	11	11	NUM
ejpam-6162	77	3	]	]	PUNCT
ejpam-6162	77	4	.	.	PUNCT
ejpam-6162	78	1	2.3	2.3	NUM
ejpam-6162	78	2	.	.	PUNCT
ejpam-6162	78	3	proposed	propose	VERB
ejpam-6162	78	4	estimators	estimator	NOUN
ejpam-6162	78	5	for	for	ADP
ejpam-6162	78	6	logistic	logistic	ADJ
ejpam-6162	78	7	and	and	CCONJ
ejpam-6162	78	8	poisson	poisson	PROPN
ejpam-6162	78	9	regression	regression	PROPN
ejpam-6162	78	10	,	,	PUNCT
ejpam-6162	78	11	new	new	ADJ
ejpam-6162	78	12	ridge	ridge	NOUN
ejpam-6162	78	13	estimators	estimator	NOUN
ejpam-6162	78	14	k9l	k9l	X
ejpam-6162	78	15	and	and	CCONJ
ejpam-6162	78	16	k9p	k9p	PROPN
ejpam-6162	78	17	are	be	AUX
ejpam-6162	78	18	introduced	introduce	VERB
ejpam-6162	78	19	as	as	ADP
ejpam-6162	78	20	weighted	weight	VERB
ejpam-6162	78	21	linear	linear	PROPN
ejpam-6162	78	22	combinations	combination	NOUN
ejpam-6162	78	23	of	of	ADP
ejpam-6162	78	24	the	the	DET
ejpam-6162	78	25	above	above	ADJ
ejpam-6162	78	26	estimators	estimator	NOUN
ejpam-6162	78	27	.	.	PUNCT
ejpam-6162	79	1	the	the	DET
ejpam-6162	79	2	weights	weight	NOUN
ejpam-6162	79	3	are	be	AUX
ejpam-6162	79	4	computed	compute	VERB
ejpam-6162	79	5	based	base	VERB
ejpam-6162	79	6	on	on	ADP
ejpam-6162	79	7	the	the	DET
ejpam-6162	79	8	inverse	inverse	NOUN
ejpam-6162	79	9	of	of	ADP
ejpam-6162	79	10	the	the	DET
ejpam-6162	79	11	mean	mean	ADJ
ejpam-6162	79	12	mse	mse	NOUN
ejpam-6162	79	13	from	from	ADP
ejpam-6162	79	14	preliminary	preliminary	ADJ
ejpam-6162	79	15	simulations	simulation	NOUN
ejpam-6162	79	16	:	:	PUNCT
ejpam-6162	79	17	ci	ci	NOUN
ejpam-6162	79	18	=	=	SYM
ejpam-6162	79	19	1	1	NUM
ejpam-6162	79	20	mean	mean	NOUN
ejpam-6162	79	21	mse	mse	NOUN
ejpam-6162	79	22	of	of	ADP
ejpam-6162	79	23	ki∑	ki∑	PROPN
ejpam-6162	79	24	j	j	PROPN
ejpam-6162	79	25	1	1	NUM
ejpam-6162	79	26	mean	mean	NOUN
ejpam-6162	79	27	mse	mse	NOUN
ejpam-6162	79	28	of	of	ADP
ejpam-6162	79	29	kj	kj	PROPN
ejpam-6162	79	30	.	.	PUNCT
ejpam-6162	80	1	for	for	ADP
ejpam-6162	80	2	multiple	multiple	ADJ
ejpam-6162	80	3	linear	linear	PROPN
ejpam-6162	80	4	regression	regression	NOUN
ejpam-6162	80	5	,	,	PUNCT
ejpam-6162	80	6	the	the	DET
ejpam-6162	80	7	proposed	propose	VERB
ejpam-6162	80	8	estimator	estimator	NOUN
ejpam-6162	80	9	k9	k9	PROPN
ejpam-6162	80	10	m	m	PROPN
ejpam-6162	80	11	is	be	AUX
ejpam-6162	80	12	determined	determine	VERB
ejpam-6162	80	13	using	use	VERB
ejpam-6162	80	14	a	a	DET
ejpam-6162	80	15	grid	grid	NOUN
ejpam-6162	80	16	search	search	NOUN
ejpam-6162	80	17	method	method	NOUN
ejpam-6162	80	18	.	.	PUNCT
ejpam-6162	81	1	a	a	DET
ejpam-6162	81	2	sequence	sequence	NOUN
ejpam-6162	81	3	of	of	ADP
ejpam-6162	81	4	k	k	PROPN
ejpam-6162	81	5	values	value	NOUN
ejpam-6162	81	6	from	from	ADP
ejpam-6162	81	7	0.01	0.01	NUM
ejpam-6162	81	8	to	to	PART
ejpam-6162	81	9	10	10	NUM
ejpam-6162	81	10	is	be	AUX
ejpam-6162	81	11	tested	test	VERB
ejpam-6162	81	12	,	,	PUNCT
ejpam-6162	81	13	and	and	CCONJ
ejpam-6162	81	14	the	the	DET
ejpam-6162	81	15	value	value	NOUN
ejpam-6162	81	16	minimizing	minimize	VERB
ejpam-6162	81	17	the	the	DET
ejpam-6162	81	18	mse	mse	NOUN
ejpam-6162	81	19	is	be	AUX
ejpam-6162	81	20	selected	select	VERB
ejpam-6162	81	21	as	as	ADP
ejpam-6162	81	22	the	the	DET
ejpam-6162	81	23	optimal	optimal	ADJ
ejpam-6162	81	24	k	k	NOUN
ejpam-6162	81	25	,	,	PUNCT
ejpam-6162	81	26	denoted	denote	VERB
ejpam-6162	81	27	ksearch	ksearch	NOUN
ejpam-6162	81	28	.	.	PUNCT
ejpam-6162	82	1	regression	regression	NOUN
ejpam-6162	82	2	analysis	analysis	NOUN
ejpam-6162	82	3	is	be	AUX
ejpam-6162	82	4	then	then	ADV
ejpam-6162	82	5	performed	perform	VERB
ejpam-6162	82	6	on	on	ADP
ejpam-6162	82	7	ksearch	ksearch	ADJ
ejpam-6162	82	8	values	value	NOUN
ejpam-6162	82	9	using	use	VERB
ejpam-6162	82	10	the	the	DET
ejpam-6162	82	11	known	know	VERB
ejpam-6162	82	12	ridge	ridge	NOUN
ejpam-6162	82	13	parameters	parameter	NOUN
ejpam-6162	82	14	and	and	CCONJ
ejpam-6162	82	15	model	model	NOUN
ejpam-6162	82	16	dimensions	dimension	NOUN
ejpam-6162	82	17	(	(	PUNCT
ejpam-6162	82	18	n	n	NOUN
ejpam-6162	82	19	and	and	CCONJ
ejpam-6162	82	20	p	p	X
ejpam-6162	82	21	)	)	PUNCT
ejpam-6162	82	22	to	to	PART
ejpam-6162	82	23	generate	generate	VERB
ejpam-6162	82	24	a	a	DET
ejpam-6162	82	25	predictive	predictive	ADJ
ejpam-6162	82	26	formula	formula	NOUN
ejpam-6162	82	27	for	for	ADP
ejpam-6162	82	28	k9	k9	PROPN
ejpam-6162	82	29	m.	m.	PROPN
ejpam-6162	82	30	2.4	2.4	NUM
ejpam-6162	82	31	.	.	PUNCT
ejpam-6162	83	1	simulation	simulation	NOUN
ejpam-6162	83	2	procedure	procedure	NOUN
ejpam-6162	83	3	the	the	DET
ejpam-6162	83	4	simulation	simulation	NOUN
ejpam-6162	83	5	design	design	NOUN
ejpam-6162	83	6	consists	consist	VERB
ejpam-6162	83	7	of	of	ADP
ejpam-6162	83	8	the	the	DET
ejpam-6162	83	9	following	follow	VERB
ejpam-6162	83	10	steps	step	NOUN
ejpam-6162	83	11	:	:	PUNCT
ejpam-6162	83	12	1	1	X
ejpam-6162	83	13	.	.	PUNCT
ejpam-6162	83	14	parameter	parameter	NOUN
ejpam-6162	83	15	setup	setup	NOUN
ejpam-6162	83	16	.	.	PUNCT
ejpam-6162	84	1	the	the	DET
ejpam-6162	84	2	parameter	parameter	NOUN
ejpam-6162	84	3	ranges	range	NOUN
ejpam-6162	84	4	are	be	AUX
ejpam-6162	84	5	defined	define	VERB
ejpam-6162	84	6	as	as	SCONJ
ejpam-6162	84	7	follows	follow	VERB
ejpam-6162	84	8	:	:	PUNCT
ejpam-6162	84	9	the	the	DET
ejpam-6162	84	10	sample	sample	NOUN
ejpam-6162	84	11	size	size	NOUN
ejpam-6162	84	12	n	n	PRON
ejpam-6162	84	13	varies	vary	VERB
ejpam-6162	84	14	from	from	ADP
ejpam-6162	84	15	10	10	NUM
ejpam-6162	84	16	to	to	PART
ejpam-6162	84	17	250	250	NUM
ejpam-6162	84	18	;	;	PUNCT
ejpam-6162	84	19	the	the	DET
ejpam-6162	84	20	number	number	NOUN
ejpam-6162	84	21	of	of	ADP
ejpam-6162	84	22	predictors	predictor	NOUN
ejpam-6162	84	23	p	p	NOUN
ejpam-6162	84	24	ranges	range	VERB
ejpam-6162	84	25	from	from	ADP
ejpam-6162	84	26	2	2	NUM
ejpam-6162	84	27	to	to	ADP
ejpam-6162	84	28	12	12	NUM
ejpam-6162	84	29	;	;	PUNCT
ejpam-6162	84	30	the	the	DET
ejpam-6162	84	31	correlation	correlation	NOUN
ejpam-6162	84	32	level	level	NOUN
ejpam-6162	84	33	ρ	ρ	NOUN
ejpam-6162	84	34	is	be	AUX
ejpam-6162	84	35	between	between	ADP
ejpam-6162	84	36	0.70	0.70	NUM
ejpam-6162	84	37	and	and	CCONJ
ejpam-6162	84	38	0.99	0.99	NUM
ejpam-6162	84	39	inclusively	inclusively	NOUN
ejpam-6162	84	40	;	;	PUNCT
ejpam-6162	84	41	and	and	CCONJ
ejpam-6162	84	42	the	the	DET
ejpam-6162	84	43	intercept	intercept	NOUN
ejpam-6162	84	44	β0	β0	NOUN
ejpam-6162	84	45	is	be	AUX
ejpam-6162	84	46	set	set	VERB
ejpam-6162	84	47	to	to	ADP
ejpam-6162	84	48	either	either	PRON
ejpam-6162	84	49	0	0	NUM
ejpam-6162	84	50	or	or	CCONJ
ejpam-6162	84	51	1	1	NUM
ejpam-6162	84	52	.	.	PUNCT
ejpam-6162	85	1	these	these	DET
ejpam-6162	85	2	parameter	parameter	NOUN
ejpam-6162	85	3	values	value	NOUN
ejpam-6162	85	4	are	be	AUX
ejpam-6162	85	5	commonly	commonly	ADV
ejpam-6162	85	6	used	use	VERB
ejpam-6162	85	7	in	in	ADP
ejpam-6162	85	8	simulation	simulation	NOUN
ejpam-6162	85	9	studies	study	NOUN
ejpam-6162	85	10	[	[	X
ejpam-6162	85	11	3–5	3–5	NOUN
ejpam-6162	85	12	]	]	PUNCT
ejpam-6162	85	13	.	.	PUNCT
ejpam-6162	86	1	2	2	X
ejpam-6162	86	2	.	.	X
ejpam-6162	86	3	generate	generate	VERB
ejpam-6162	86	4	multicollinear	multicollinear	ADJ
ejpam-6162	86	5	predictors	predictor	NOUN
ejpam-6162	86	6	.	.	PUNCT
ejpam-6162	87	1	the	the	DET
ejpam-6162	87	2	matrix	matrix	NOUN
ejpam-6162	87	3	x	x	PUNCT
ejpam-6162	87	4	∈	∈	PROPN
ejpam-6162	87	5	rn×p	rn×p	PROPN
ejpam-6162	87	6	is	be	AUX
ejpam-6162	87	7	generated	generate	VERB
ejpam-6162	87	8	using	use	VERB
ejpam-6162	87	9	the	the	DET
ejpam-6162	87	10	method	method	NOUN
ejpam-6162	87	11	of	of	ADP
ejpam-6162	87	12	mcdonald	mcdonald	NOUN
ejpam-6162	87	13	and	and	CCONJ
ejpam-6162	87	14	galarneau	galarneau	NOUN
ejpam-6162	88	1	[	[	X
ejpam-6162	88	2	12	12	NUM
ejpam-6162	88	3	]	]	X
ejpam-6162	88	4	:	:	PUNCT
ejpam-6162	88	5	xij	xij	PROPN
ejpam-6162	88	6	=	=	PUNCT
ejpam-6162	88	7	√	√	PROPN
ejpam-6162	88	8	1−	1−	NUM
ejpam-6162	89	1	ρ2	ρ2	NOUN
ejpam-6162	89	2	·	·	PUNCT
ejpam-6162	89	3	zij	zij	PROPN
ejpam-6162	89	4	+	+	PROPN
ejpam-6162	89	5	ρ	ρ	PROPN
ejpam-6162	89	6	·	·	PUNCT
ejpam-6162	89	7	zi0	zi0	NUM
ejpam-6162	89	8	,	,	PUNCT
ejpam-6162	89	9	i	i	PRON
ejpam-6162	89	10	=	=	NOUN
ejpam-6162	89	11	1	1	NUM
ejpam-6162	89	12	,	,	PUNCT
ejpam-6162	89	13	.	.	PUNCT
ejpam-6162	89	14	.	.	PUNCT
ejpam-6162	90	1	.	.	PUNCT
ejpam-6162	91	1	,	,	PUNCT
ejpam-6162	91	2	n	n	CCONJ
ejpam-6162	91	3	,	,	PUNCT
ejpam-6162	91	4	j	j	PROPN
ejpam-6162	91	5	=	=	SYM
ejpam-6162	91	6	1	1	NUM
ejpam-6162	91	7	,	,	PUNCT
ejpam-6162	91	8	.	.	PUNCT
ejpam-6162	91	9	.	.	PUNCT
ejpam-6162	92	1	.	.	PUNCT
ejpam-6162	93	1	,	,	PUNCT
ejpam-6162	94	1	p	p	X
ejpam-6162	94	2	,	,	PUNCT
ejpam-6162	94	3	where	where	SCONJ
ejpam-6162	94	4	zij	zij	PROPN
ejpam-6162	94	5	∼	∼	NOUN
ejpam-6162	94	6	n	n	CCONJ
ejpam-6162	94	7	(	(	PUNCT
ejpam-6162	94	8	0	0	NUM
ejpam-6162	94	9	,	,	PUNCT
ejpam-6162	94	10	1	1	NUM
ejpam-6162	94	11	)	)	PUNCT
ejpam-6162	94	12	are	be	AUX
ejpam-6162	94	13	standard	standard	ADJ
ejpam-6162	94	14	normal	normal	ADJ
ejpam-6162	94	15	random	random	ADJ
ejpam-6162	94	16	variables	variable	NOUN
ejpam-6162	94	17	,	,	PUNCT
ejpam-6162	94	18	inducing	induce	VERB
ejpam-6162	94	19	correlation	correlation	NOUN
ejpam-6162	94	20	among	among	ADP
ejpam-6162	94	21	predictors	predictor	NOUN
ejpam-6162	94	22	.	.	PUNCT
ejpam-6162	95	1	3	3	X
ejpam-6162	95	2	.	.	X
ejpam-6162	95	3	generate	generate	VERB
ejpam-6162	95	4	response	response	NOUN
ejpam-6162	95	5	variable	variable	NOUN
ejpam-6162	95	6	.	.	PUNCT
ejpam-6162	96	1	set	set	VERB
ejpam-6162	96	2	the	the	DET
ejpam-6162	96	3	true	true	ADJ
ejpam-6162	96	4	coefficients	coefficient	NOUN
ejpam-6162	96	5	β	β	ADP
ejpam-6162	96	6	such	such	ADJ
ejpam-6162	96	7	that∑	that∑	NOUN
ejpam-6162	96	8	β2	β2	NOUN
ejpam-6162	96	9	i	i	NOUN
ejpam-6162	96	10	=	=	NOUN
ejpam-6162	96	11	1	1	X
ejpam-6162	96	12	.	.	PUNCT
ejpam-6162	96	13	generate	generate	VERB
ejpam-6162	96	14	the	the	DET
ejpam-6162	96	15	response	response	NOUN
ejpam-6162	96	16	vector	vector	NOUN
ejpam-6162	96	17	y	y	PROPN
ejpam-6162	96	18	appropriate	appropriate	ADJ
ejpam-6162	96	19	for	for	ADP
ejpam-6162	96	20	each	each	DET
ejpam-6162	96	21	regression	regression	NOUN
ejpam-6162	96	22	model	model	NOUN
ejpam-6162	96	23	(	(	PUNCT
ejpam-6162	96	24	logistic	logistic	ADJ
ejpam-6162	96	25	,	,	PUNCT
ejpam-6162	96	26	poisson	poisson	NOUN
ejpam-6162	96	27	,	,	PUNCT
ejpam-6162	96	28	or	or	CCONJ
ejpam-6162	96	29	linear	linear	NOUN
ejpam-6162	96	30	)	)	PUNCT
ejpam-6162	96	31	using	use	VERB
ejpam-6162	96	32	x	x	PUNCT
ejpam-6162	96	33	and	and	CCONJ
ejpam-6162	96	34	β	β	X
ejpam-6162	96	35	.	.	PUNCT
ejpam-6162	97	1	j.	j.	PROPN
ejpam-6162	97	2	mohamad	mohamad	PROPN
ejpam-6162	97	3	,	,	PUNCT
ejpam-6162	97	4	et	et	PROPN
ejpam-6162	97	5	.	.	PUNCT
ejpam-6162	98	1	al	al	PROPN
ejpam-6162	98	2	.	.	PUNCT
ejpam-6162	98	3	/	/	SYM
ejpam-6162	98	4	eur	eur	PROPN
ejpam-6162	98	5	.	.	PUNCT
ejpam-6162	99	1	j.	j.	PROPN
ejpam-6162	99	2	pure	pure	PROPN
ejpam-6162	99	3	appl	appl	PROPN
ejpam-6162	99	4	.	.	PROPN
ejpam-6162	99	5	math	math	PROPN
ejpam-6162	99	6	,	,	PUNCT
ejpam-6162	99	7	18	18	NUM
ejpam-6162	99	8	(	(	PUNCT
ejpam-6162	99	9	2	2	NUM
ejpam-6162	99	10	)	)	PUNCT
ejpam-6162	99	11	(	(	PUNCT
ejpam-6162	99	12	2025	2025	NUM
ejpam-6162	99	13	)	)	PUNCT
ejpam-6162	99	14	,	,	PUNCT
ejpam-6162	99	15	6162	6162	NUM
ejpam-6162	99	16	5	5	NUM
ejpam-6162	99	17	of	of	ADP
ejpam-6162	99	18	10	10	NUM
ejpam-6162	99	19	4	4	NUM
ejpam-6162	99	20	.	.	NOUN
ejpam-6162	99	21	estimate	estimate	NOUN
ejpam-6162	99	22	coefficients	coefficient	NOUN
ejpam-6162	99	23	and	and	CCONJ
ejpam-6162	99	24	compute	compute	PROPN
ejpam-6162	99	25	mse	mse	PROPN
ejpam-6162	99	26	.	.	PUNCT
ejpam-6162	100	1	for	for	ADP
ejpam-6162	100	2	each	each	DET
ejpam-6162	100	3	estimator	estimator	NOUN
ejpam-6162	100	4	,	,	PUNCT
ejpam-6162	100	5	the	the	DET
ejpam-6162	100	6	regression	regression	NOUN
ejpam-6162	100	7	method	method	NOUN
ejpam-6162	100	8	is	be	AUX
ejpam-6162	100	9	applied	apply	VERB
ejpam-6162	100	10	then	then	ADV
ejpam-6162	100	11	optimized	optimize	VERB
ejpam-6162	100	12	through	through	ADP
ejpam-6162	100	13	the	the	DET
ejpam-6162	100	14	optim	optim	ADJ
ejpam-6162	100	15	function	function	NOUN
ejpam-6162	100	16	in	in	ADP
ejpam-6162	100	17	r	r	NOUN
ejpam-6162	100	18	to	to	PART
ejpam-6162	100	19	compute	compute	VERB
ejpam-6162	100	20	β̂	β̂	PUNCT
ejpam-6162	100	21	and	and	CCONJ
ejpam-6162	100	22	evaluate	evaluate	VERB
ejpam-6162	100	23	the	the	DET
ejpam-6162	100	24	mse	mse	NOUN
ejpam-6162	100	25	:	:	PUNCT
ejpam-6162	100	26	mse	mse	PROPN
ejpam-6162	100	27	=	=	SYM
ejpam-6162	100	28	1	1	NUM
ejpam-6162	100	29	p	p	NOUN
ejpam-6162	100	30	(	(	PUNCT
ejpam-6162	100	31	β	β	NOUN
ejpam-6162	100	32	−	−	NOUN
ejpam-6162	100	33	β̂)t	β̂)t	NOUN
ejpam-6162	100	34	(	(	PUNCT
ejpam-6162	100	35	β	β	NOUN
ejpam-6162	100	36	−	−	PROPN
ejpam-6162	100	37	β̂	β̂	ADP
ejpam-6162	100	38	)	)	PUNCT
ejpam-6162	100	39	.	.	PUNCT
ejpam-6162	101	1	5	5	X
ejpam-6162	101	2	.	.	X
ejpam-6162	101	3	repetition	repetition	NOUN
ejpam-6162	101	4	and	and	CCONJ
ejpam-6162	101	5	averaging	average	VERB
ejpam-6162	101	6	.	.	PUNCT
ejpam-6162	102	1	perform	perform	VERB
ejpam-6162	102	2	steps	step	NOUN
ejpam-6162	102	3	2	2	NUM
ejpam-6162	102	4	to	to	ADP
ejpam-6162	102	5	4	4	NUM
ejpam-6162	102	6	for	for	ADP
ejpam-6162	102	7	a	a	DET
ejpam-6162	102	8	total	total	NOUN
ejpam-6162	102	9	of	of	ADP
ejpam-6162	102	10	1,000	1,000	NUM
ejpam-6162	102	11	times	time	NOUN
ejpam-6162	102	12	.	.	PUNCT
ejpam-6162	103	1	for	for	ADP
ejpam-6162	103	2	each	each	DET
ejpam-6162	103	3	estimator	estimator	NOUN
ejpam-6162	103	4	,	,	PUNCT
ejpam-6162	103	5	compute	compute	VERB
ejpam-6162	103	6	the	the	DET
ejpam-6162	103	7	average	average	ADJ
ejpam-6162	103	8	mse	mse	NOUN
ejpam-6162	103	9	across	across	ADP
ejpam-6162	103	10	the	the	DET
ejpam-6162	103	11	1,000	1,000	NUM
ejpam-6162	103	12	replications	replication	NOUN
ejpam-6162	103	13	.	.	PUNCT
ejpam-6162	104	1	the	the	DET
ejpam-6162	104	2	estimator	estimator	NOUN
ejpam-6162	104	3	with	with	ADP
ejpam-6162	104	4	the	the	DET
ejpam-6162	104	5	lowest	low	ADJ
ejpam-6162	104	6	average	average	ADJ
ejpam-6162	104	7	mse	mse	NOUN
ejpam-6162	104	8	is	be	AUX
ejpam-6162	104	9	considered	consider	VERB
ejpam-6162	104	10	the	the	DET
ejpam-6162	104	11	best	good	ADJ
ejpam-6162	104	12	estimator	estimator	NOUN
ejpam-6162	104	13	.	.	PUNCT
ejpam-6162	105	1	3	3	X
ejpam-6162	105	2	.	.	X
ejpam-6162	105	3	results	result	NOUN
ejpam-6162	105	4	in	in	ADP
ejpam-6162	105	5	developing	develop	VERB
ejpam-6162	105	6	new	new	ADJ
ejpam-6162	105	7	ridge	ridge	NOUN
ejpam-6162	105	8	estimators	estimator	NOUN
ejpam-6162	105	9	,	,	PUNCT
ejpam-6162	105	10	the	the	DET
ejpam-6162	105	11	following	follow	VERB
ejpam-6162	105	12	results	result	NOUN
ejpam-6162	105	13	were	be	AUX
ejpam-6162	105	14	determined	determine	VERB
ejpam-6162	105	15	and	and	CCONJ
ejpam-6162	105	16	are	be	AUX
ejpam-6162	105	17	proposed	propose	VERB
ejpam-6162	105	18	based	base	VERB
ejpam-6162	105	19	on	on	ADP
ejpam-6162	105	20	their	their	PRON
ejpam-6162	105	21	performance	performance	NOUN
ejpam-6162	105	22	in	in	ADP
ejpam-6162	105	23	their	their	PRON
ejpam-6162	105	24	respective	respective	ADJ
ejpam-6162	105	25	regression	regression	NOUN
ejpam-6162	105	26	models	model	NOUN
ejpam-6162	105	27	:	:	PUNCT
ejpam-6162	105	28	k9l	k9l	X
ejpam-6162	105	29	=	=	PUNCT
ejpam-6162	105	30	0.451	0.451	NUM
ejpam-6162	105	31	·	·	PUNCT
ejpam-6162	105	32	k6	k6	NOUN
ejpam-6162	105	33	+	+	CCONJ
ejpam-6162	105	34	0.269	0.269	NUM
ejpam-6162	105	35	·	·	PUNCT
ejpam-6162	106	1	k7	k7	NOUN
ejpam-6162	106	2	+	+	CCONJ
ejpam-6162	106	3	0.2797	0.2797	NUM
ejpam-6162	106	4	·	·	PUNCT
ejpam-6162	106	5	k8	k8	NOUN
ejpam-6162	106	6	for	for	ADP
ejpam-6162	106	7	logistic	logistic	ADJ
ejpam-6162	106	8	regression	regression	NOUN
ejpam-6162	106	9	,	,	PUNCT
ejpam-6162	106	10	k9p	k9p	PROPN
ejpam-6162	106	11	=	=	SYM
ejpam-6162	106	12	0.290	0.290	NUM
ejpam-6162	106	13	·	·	PUNCT
ejpam-6162	106	14	k2	k2	NOUN
ejpam-6162	106	15	+	+	CCONJ
ejpam-6162	106	16	0.169	0.169	NUM
ejpam-6162	106	17	·	·	SYM
ejpam-6162	106	18	k6	k6	NOUN
ejpam-6162	106	19	+	+	CCONJ
ejpam-6162	106	20	0.283	0.283	NUM
ejpam-6162	106	21	·	·	PUNCT
ejpam-6162	107	1	k7	k7	NOUN
ejpam-6162	107	2	+	+	CCONJ
ejpam-6162	107	3	0.253	0.253	NUM
ejpam-6162	107	4	·	·	PUNCT
ejpam-6162	107	5	k8	k8	NOUN
ejpam-6162	107	6	for	for	ADP
ejpam-6162	107	7	poisson	poisson	NOUN
ejpam-6162	107	8	regression	regression	NOUN
ejpam-6162	107	9	,	,	PUNCT
ejpam-6162	107	10	and	and	CCONJ
ejpam-6162	107	11	k9	k9	PROPN
ejpam-6162	107	12	m	m	PROPN
ejpam-6162	107	13	=	=	PROPN
ejpam-6162	107	14	k̂search	k̂search	X
ejpam-6162	107	15	=	=	PUNCT
ejpam-6162	107	16	0.329	0.329	NUM
ejpam-6162	107	17	·	·	PUNCT
ejpam-6162	107	18	n+	n+	ADP
ejpam-6162	107	19	0.464	0.464	NUM
ejpam-6162	107	20	·	·	PUNCT
ejpam-6162	107	21	p−	p−	NOUN
ejpam-6162	107	22	0.282	0.282	NUM
ejpam-6162	107	23	·	·	PUNCT
ejpam-6162	107	24	k2,−0.176	k2,−0.176	NOUN
ejpam-6162	107	25	·	·	PUNCT
ejpam-6162	107	26	k6	k6	NOUN
ejpam-6162	107	27	for	for	ADP
ejpam-6162	107	28	multiple	multiple	ADJ
ejpam-6162	107	29	regression	regression	NOUN
ejpam-6162	107	30	.	.	PUNCT
ejpam-6162	108	1	the	the	DET
ejpam-6162	108	2	following	follow	VERB
ejpam-6162	108	3	subsections	subsection	NOUN
ejpam-6162	108	4	discusses	discuss	VERB
ejpam-6162	108	5	the	the	DET
ejpam-6162	108	6	results	result	NOUN
ejpam-6162	108	7	in	in	ADP
ejpam-6162	108	8	tables	table	NOUN
ejpam-6162	108	9	for	for	ADP
ejpam-6162	108	10	each	each	DET
ejpam-6162	108	11	regression	regression	NOUN
ejpam-6162	108	12	model	model	NOUN
ejpam-6162	108	13	,	,	PUNCT
ejpam-6162	108	14	tables	table	NOUN
ejpam-6162	108	15	1	1	NUM
ejpam-6162	108	16	,	,	PUNCT
ejpam-6162	108	17	3	3	NUM
ejpam-6162	108	18	and	and	CCONJ
ejpam-6162	108	19	5	5	NUM
ejpam-6162	108	20	shows	show	VERB
ejpam-6162	108	21	the	the	DET
ejpam-6162	108	22	simulation	simulation	NOUN
ejpam-6162	108	23	results	result	VERB
ejpam-6162	108	24	where	where	SCONJ
ejpam-6162	108	25	the	the	DET
ejpam-6162	108	26	proposed	propose	VERB
ejpam-6162	108	27	estimator	estimator	NOUN
ejpam-6162	108	28	has	have	VERB
ejpam-6162	108	29	the	the	DET
ejpam-6162	108	30	least	least	ADV
ejpam-6162	108	31	estimated	estimate	VERB
ejpam-6162	108	32	mse	mse	PROPN
ejpam-6162	108	33	.	.	PUNCT
ejpam-6162	109	1	3.1	3.1	NUM
ejpam-6162	109	2	.	.	PUNCT
ejpam-6162	109	3	logistic	logistic	PROPN
ejpam-6162	109	4	ridge	ridge	PROPN
ejpam-6162	109	5	regression	regression	PROPN
ejpam-6162	109	6	simulation	simulation	NOUN
ejpam-6162	109	7	results	result	VERB
ejpam-6162	109	8	for	for	ADP
ejpam-6162	109	9	logistic	logistic	ADJ
ejpam-6162	109	10	ridge	ridge	NOUN
ejpam-6162	109	11	regression	regression	NOUN
ejpam-6162	109	12	,	,	PUNCT
ejpam-6162	109	13	the	the	DET
ejpam-6162	109	14	widely	widely	ADV
ejpam-6162	109	15	used	use	VERB
ejpam-6162	109	16	ml	ml	NOUN
ejpam-6162	109	17	estimator	estimator	NOUN
ejpam-6162	109	18	,	,	PUNCT
ejpam-6162	109	19	the	the	DET
ejpam-6162	109	20	known	known	ADJ
ejpam-6162	109	21	hk	hk	PROPN
ejpam-6162	109	22	,	,	PUNCT
ejpam-6162	109	23	k2	k2	PROPN
ejpam-6162	109	24	to	to	ADP
ejpam-6162	109	25	k8	k8	PROPN
ejpam-6162	109	26	estimators	estimator	NOUN
ejpam-6162	109	27	and	and	CCONJ
ejpam-6162	109	28	the	the	DET
ejpam-6162	109	29	proposed	propose	VERB
ejpam-6162	109	30	k9l	k9l	PROPN
ejpam-6162	109	31	estimator	estimator	NOUN
ejpam-6162	109	32	are	be	AUX
ejpam-6162	109	33	applied	apply	VERB
ejpam-6162	109	34	and	and	CCONJ
ejpam-6162	109	35	compared	compare	VERB
ejpam-6162	109	36	in	in	ADP
ejpam-6162	109	37	simulations	simulation	NOUN
ejpam-6162	109	38	.	.	PUNCT
ejpam-6162	110	1	table	table	NOUN
ejpam-6162	110	2	1	1	NUM
ejpam-6162	110	3	shows	show	VERB
ejpam-6162	110	4	some	some	PRON
ejpam-6162	110	5	of	of	ADP
ejpam-6162	110	6	the	the	DET
ejpam-6162	110	7	simulation	simulation	NOUN
ejpam-6162	110	8	results	result	VERB
ejpam-6162	110	9	where	where	SCONJ
ejpam-6162	110	10	the	the	DET
ejpam-6162	110	11	mse	mse	NOUN
ejpam-6162	110	12	values	value	NOUN
ejpam-6162	110	13	of	of	ADP
ejpam-6162	110	14	each	each	DET
ejpam-6162	110	15	estimator	estimator	NOUN
ejpam-6162	110	16	are	be	AUX
ejpam-6162	110	17	compared	compare	VERB
ejpam-6162	110	18	when	when	SCONJ
ejpam-6162	110	19	β0	β0	PROPN
ejpam-6162	110	20	=	=	PROPN
ejpam-6162	110	21	0	0	NUM
ejpam-6162	110	22	and	and	CCONJ
ejpam-6162	110	23	ρ	ρ	NUM
ejpam-6162	110	24	=	=	NOUN
ejpam-6162	110	25	0.99	0.99	NUM
ejpam-6162	110	26	for	for	ADP
ejpam-6162	110	27	p	p	NOUN
ejpam-6162	110	28	=	=	SYM
ejpam-6162	110	29	2	2	NUM
ejpam-6162	110	30	,	,	PUNCT
ejpam-6162	110	31	3	3	NUM
ejpam-6162	110	32	,	,	PUNCT
ejpam-6162	110	33	4	4	NUM
ejpam-6162	110	34	,	,	PUNCT
ejpam-6162	110	35	8	8	NUM
ejpam-6162	110	36	,	,	PUNCT
ejpam-6162	110	37	12	12	NUM
ejpam-6162	110	38	with	with	ADP
ejpam-6162	110	39	n	n	NOUN
ejpam-6162	110	40	=	=	SYM
ejpam-6162	110	41	20p+	20p+	NUM
ejpam-6162	110	42	10	10	NUM
ejpam-6162	110	43	,	,	PUNCT
ejpam-6162	110	44	30p	30p	NUM
ejpam-6162	110	45	,	,	PUNCT
ejpam-6162	110	46	40p	40p	NOUN
ejpam-6162	110	47	,	,	PUNCT
ejpam-6162	110	48	60p	60p	NOUN
ejpam-6162	110	49	,	,	PUNCT
ejpam-6162	110	50	and	and	CCONJ
ejpam-6162	110	51	100p	100p	NOUN
ejpam-6162	110	52	.	.	PUNCT
ejpam-6162	111	1	it	it	PRON
ejpam-6162	111	2	is	be	AUX
ejpam-6162	111	3	observed	observe	VERB
ejpam-6162	111	4	in	in	ADP
ejpam-6162	111	5	the	the	DET
ejpam-6162	111	6	simulation	simulation	NOUN
ejpam-6162	111	7	that	that	PRON
ejpam-6162	111	8	the	the	DET
ejpam-6162	111	9	new	new	ADJ
ejpam-6162	111	10	estimator	estimator	NOUN
ejpam-6162	111	11	k9l	k9l	PROPN
ejpam-6162	111	12	has	have	VERB
ejpam-6162	111	13	the	the	DET
ejpam-6162	111	14	least	least	ADJ
ejpam-6162	111	15	mse	mse	NOUN
ejpam-6162	111	16	in	in	ADP
ejpam-6162	111	17	some	some	DET
ejpam-6162	111	18	cases	case	NOUN
ejpam-6162	111	19	.	.	PUNCT
ejpam-6162	112	1	specifically	specifically	ADV
ejpam-6162	112	2	,	,	PUNCT
ejpam-6162	112	3	when	when	SCONJ
ejpam-6162	112	4	β0	β0	PROPN
ejpam-6162	112	5	=	=	SYM
ejpam-6162	112	6	0	0	PROPN
ejpam-6162	112	7	,	,	PUNCT
ejpam-6162	112	8	ρ	ρ	PROPN
ejpam-6162	112	9	=	=	SYM
ejpam-6162	112	10	0.99	0.99	NUM
ejpam-6162	112	11	,	,	PUNCT
ejpam-6162	112	12	p	p	X
ejpam-6162	112	13	=	=	NOUN
ejpam-6162	112	14	2	2	NUM
ejpam-6162	112	15	,	,	PUNCT
ejpam-6162	112	16	3	3	NUM
ejpam-6162	112	17	,	,	PUNCT
ejpam-6162	112	18	4	4	NUM
ejpam-6162	112	19	,	,	PUNCT
ejpam-6162	112	20	8	8	NUM
ejpam-6162	112	21	,	,	PUNCT
ejpam-6162	112	22	12	12	NUM
ejpam-6162	112	23	and	and	CCONJ
ejpam-6162	112	24	when	when	SCONJ
ejpam-6162	112	25	n	n	X
ejpam-6162	112	26	=	=	SYM
ejpam-6162	112	27	60	60	NUM
ejpam-6162	112	28	,	,	PUNCT
ejpam-6162	112	29	80	80	NUM
ejpam-6162	112	30	,	,	PUNCT
ejpam-6162	112	31	160	160	NUM
ejpam-6162	112	32	,	,	PUNCT
ejpam-6162	112	33	170	170	NUM
ejpam-6162	112	34	,	,	PUNCT
ejpam-6162	112	35	180	180	NUM
ejpam-6162	112	36	,	,	PUNCT
ejpam-6162	112	37	240	240	NUM
ejpam-6162	112	38	,	,	PUNCT
ejpam-6162	112	39	and	and	CCONJ
ejpam-6162	112	40	250	250	NUM
ejpam-6162	112	41	.	.	PUNCT
ejpam-6162	112	42	table	table	NOUN
ejpam-6162	112	43	1	1	NUM
ejpam-6162	112	44	:	:	PUNCT
ejpam-6162	112	45	estimated	estimate	VERB
ejpam-6162	112	46	mses	ms	NOUN
ejpam-6162	112	47	for	for	ADP
ejpam-6162	112	48	the	the	DET
ejpam-6162	112	49	logistic	logistic	PROPN
ejpam-6162	112	50	ridge	ridge	PROPN
ejpam-6162	112	51	regression	regression	PROPN
ejpam-6162	112	52	simulation	simulation	NOUN
ejpam-6162	112	53	with	with	ADP
ejpam-6162	112	54	β0	β0	PROPN
ejpam-6162	112	55	=	=	PROPN
ejpam-6162	112	56	0	0	NUM
ejpam-6162	112	57	and	and	CCONJ
ejpam-6162	112	58	ρ	ρ	NUM
ejpam-6162	112	59	=	=	NOUN
ejpam-6162	112	60	0.99	0.99	NUM
ejpam-6162	112	61	estimators	estimator	NOUN
ejpam-6162	112	62	p	p	NOUN
ejpam-6162	112	63	n	n	INTJ
ejpam-6162	112	64	ml	ml	ADP
ejpam-6162	112	65	hk	hk	PROPN
ejpam-6162	112	66	k2	k2	PROPN
ejpam-6162	112	67	k3	k3	VERB
ejpam-6162	112	68	k4	k4	PROPN
ejpam-6162	112	69	k5	k5	PROPN
ejpam-6162	112	70	k6	k6	PROPN
ejpam-6162	112	71	k7	k7	PROPN
ejpam-6162	112	72	k8	k8	PROPN
ejpam-6162	112	73	k9l	k9l	PROPN
ejpam-6162	112	74	2	2	NUM
ejpam-6162	112	75	60	60	NUM
ejpam-6162	112	76	0.658	0.658	NUM
ejpam-6162	112	77	0.569	0.569	NUM
ejpam-6162	112	78	0.370	0.370	NUM
ejpam-6162	112	79	0.533	0.533	NUM
ejpam-6162	112	80	0.416	0.416	NUM
ejpam-6162	112	81	0.517	0.517	NUM
ejpam-6162	112	82	0.217	0.217	NUM
ejpam-6162	112	83	0.219	0.219	NUM
ejpam-6162	112	84	0.214	0.214	NUM
ejpam-6162	112	85	0.213	0.213	NUM
ejpam-6162	112	86	2	2	NUM
ejpam-6162	112	87	80	80	NUM
ejpam-6162	112	88	0.452	0.452	NUM
ejpam-6162	112	89	0.403	0.403	NUM
ejpam-6162	112	90	0.277	0.277	NUM
ejpam-6162	112	91	0.386	0.386	NUM
ejpam-6162	112	92	0.316	0.316	NUM
ejpam-6162	112	93	0.380	0.380	NUM
ejpam-6162	112	94	0.161	0.161	NUM
ejpam-6162	112	95	0.166	0.166	NUM
ejpam-6162	112	96	0.161	0.161	NUM
ejpam-6162	112	97	0.159	0.159	NUM
ejpam-6162	112	98	3	3	NUM
ejpam-6162	112	99	180	180	NUM
ejpam-6162	112	100	6.817	6.817	NUM
ejpam-6162	112	101	5.097	5.097	NUM
ejpam-6162	112	102	2.355	2.355	NUM
ejpam-6162	112	103	2.601	2.601	NUM
ejpam-6162	112	104	0.812	0.812	NUM
ejpam-6162	112	105	1.747	1.747	NUM
ejpam-6162	112	106	0.076	0.076	NUM
ejpam-6162	112	107	0.078	0.078	NUM
ejpam-6162	112	108	0.073	0.073	NUM
ejpam-6162	112	109	0.070	0.070	NUM
ejpam-6162	112	110	4	4	NUM
ejpam-6162	112	111	160	160	NUM
ejpam-6162	112	112	13.74	13.74	NUM
ejpam-6162	112	113	10.81	10.81	NUM
ejpam-6162	112	114	5.144	5.144	NUM
ejpam-6162	112	115	4.518	4.518	NUM
ejpam-6162	112	116	1.244	1.244	NUM
ejpam-6162	112	117	3.088	3.088	NUM
ejpam-6162	112	118	0.099	0.099	NUM
ejpam-6162	112	119	0.096	0.096	NUM
ejpam-6162	112	120	0.087	0.087	NUM
ejpam-6162	112	121	0.086	0.086	NUM
ejpam-6162	112	122	8	8	NUM
ejpam-6162	112	123	170	170	NUM
ejpam-6162	112	124	42.43	42.43	NUM
ejpam-6162	112	125	35.62	35.62	NUM
ejpam-6162	112	126	17.41	17.41	NUM
ejpam-6162	112	127	10.89	10.89	NUM
ejpam-6162	112	128	3.43	3.43	NUM
ejpam-6162	112	129	9.19	9.19	NUM
ejpam-6162	112	130	0.129	0.129	NUM
ejpam-6162	112	131	0.129	0.129	NUM
ejpam-6162	112	132	0.113	0.113	NUM
ejpam-6162	112	133	0.103	0.103	NUM
ejpam-6162	112	134	8	8	NUM
ejpam-6162	112	135	240	240	NUM
ejpam-6162	112	136	27.98	27.98	NUM
ejpam-6162	112	137	23.67	23.67	NUM
ejpam-6162	112	138	11.98	11.98	NUM
ejpam-6162	112	139	7.215	7.215	NUM
ejpam-6162	112	140	2.87	2.87	NUM
ejpam-6162	112	141	7.63	7.63	NUM
ejpam-6162	112	142	0.088	0.088	NUM
ejpam-6162	112	143	0.157	0.157	NUM
ejpam-6162	112	144	0.127	0.127	NUM
ejpam-6162	112	145	0.082	0.082	NUM
ejpam-6162	112	146	12	12	NUM
ejpam-6162	112	147	250	250	NUM
ejpam-6162	112	148	53.22	53.22	NUM
ejpam-6162	112	149	46.255	46.255	NUM
ejpam-6162	112	150	23.671	23.671	NUM
ejpam-6162	112	151	13.07	13.07	NUM
ejpam-6162	112	152	5.048	5.048	NUM
ejpam-6162	112	153	14.199	14.199	NUM
ejpam-6162	112	154	0.105	0.105	NUM
ejpam-6162	112	155	0.180	0.180	NUM
ejpam-6162	112	156	0.140	0.140	NUM
ejpam-6162	112	157	0.090	0.090	NUM
ejpam-6162	112	158	j.	j.	PROPN
ejpam-6162	112	159	mohamad	mohamad	PROPN
ejpam-6162	112	160	,	,	PUNCT
ejpam-6162	112	161	et	et	PROPN
ejpam-6162	112	162	.	.	PUNCT
ejpam-6162	113	1	al	al	PROPN
ejpam-6162	113	2	.	.	PUNCT
ejpam-6162	113	3	/	/	SYM
ejpam-6162	113	4	eur	eur	PROPN
ejpam-6162	113	5	.	.	PUNCT
ejpam-6162	114	1	j.	j.	PROPN
ejpam-6162	114	2	pure	pure	PROPN
ejpam-6162	114	3	appl	appl	PROPN
ejpam-6162	114	4	.	.	PROPN
ejpam-6162	114	5	math	math	PROPN
ejpam-6162	114	6	,	,	PUNCT
ejpam-6162	114	7	18	18	NUM
ejpam-6162	114	8	(	(	PUNCT
ejpam-6162	114	9	2	2	NUM
ejpam-6162	114	10	)	)	PUNCT
ejpam-6162	114	11	(	(	PUNCT
ejpam-6162	114	12	2025	2025	NUM
ejpam-6162	114	13	)	)	PUNCT
ejpam-6162	114	14	,	,	PUNCT
ejpam-6162	114	15	6162	6162	NUM
ejpam-6162	114	16	6	6	NUM
ejpam-6162	114	17	of	of	ADP
ejpam-6162	114	18	10	10	NUM
ejpam-6162	114	19	to	to	PART
ejpam-6162	114	20	apply	apply	VERB
ejpam-6162	114	21	the	the	DET
ejpam-6162	114	22	logistic	logistic	ADJ
ejpam-6162	114	23	estimators	estimator	NOUN
ejpam-6162	114	24	to	to	ADP
ejpam-6162	114	25	secondary	secondary	ADJ
ejpam-6162	114	26	data	datum	NOUN
ejpam-6162	115	1	,	,	PUNCT
ejpam-6162	115	2	we	we	PRON
ejpam-6162	115	3	used	use	VERB
ejpam-6162	115	4	the	the	DET
ejpam-6162	115	5	breast	breast	NOUN
ejpam-6162	115	6	cancer	cancer	NOUN
ejpam-6162	115	7	data	datum	NOUN
ejpam-6162	115	8	obtained	obtain	VERB
ejpam-6162	115	9	from	from	ADP
ejpam-6162	115	10	taha	taha	PROPN
ejpam-6162	115	11	(	(	PUNCT
ejpam-6162	115	12	2022	2022	NUM
ejpam-6162	115	13	,	,	PUNCT
ejpam-6162	115	14	kaggle	kaggle	VERB
ejpam-6162	115	15	dataset	dataset	NOUN
ejpam-6162	115	16	)	)	PUNCT
ejpam-6162	115	17	.	.	PUNCT
ejpam-6162	116	1	we	we	PRON
ejpam-6162	116	2	set	set	VERB
ejpam-6162	116	3	the	the	DET
ejpam-6162	116	4	dependent	dependent	ADJ
ejpam-6162	116	5	variable	variable	NOUN
ejpam-6162	116	6	as	as	ADP
ejpam-6162	116	7	the	the	DET
ejpam-6162	116	8	type	type	NOUN
ejpam-6162	116	9	of	of	ADP
ejpam-6162	116	10	cancer	cancer	NOUN
ejpam-6162	116	11	diagnosis	diagnosis	NOUN
ejpam-6162	116	12	(	(	PUNCT
ejpam-6162	116	13	0	0	NUM
ejpam-6162	116	14	=	=	ADJ
ejpam-6162	116	15	benign	benign	ADJ
ejpam-6162	116	16	cancer	cancer	NOUN
ejpam-6162	116	17	,	,	PUNCT
ejpam-6162	116	18	1	1	NUM
ejpam-6162	116	19	=	=	SYM
ejpam-6162	116	20	malignant	malignant	ADJ
ejpam-6162	116	21	cancer	cancer	NOUN
ejpam-6162	116	22	)	)	PUNCT
ejpam-6162	116	23	with	with	ADP
ejpam-6162	116	24	n	n	NOUN
ejpam-6162	116	25	=	=	NUM
ejpam-6162	116	26	180	180	NUM
ejpam-6162	116	27	and	and	CCONJ
ejpam-6162	116	28	p	p	X
ejpam-6162	116	29	=	=	ADJ
ejpam-6162	116	30	3	3	X
ejpam-6162	116	31	.	.	PUNCT
ejpam-6162	116	32	three	three	NUM
ejpam-6162	116	33	explanatory	explanatory	ADJ
ejpam-6162	116	34	variables	variable	NOUN
ejpam-6162	116	35	are	be	AUX
ejpam-6162	116	36	included	include	VERB
ejpam-6162	116	37	:	:	PUNCT
ejpam-6162	116	38	radius	radius	NOUN
ejpam-6162	116	39	mean	mean	NOUN
ejpam-6162	116	40	(	(	PUNCT
ejpam-6162	116	41	r	r	NOUN
ejpam-6162	116	42	)	)	PUNCT
ejpam-6162	116	43	,	,	PUNCT
ejpam-6162	116	44	perimeter	perimeter	NOUN
ejpam-6162	116	45	mean	mean	VERB
ejpam-6162	116	46	(	(	PUNCT
ejpam-6162	116	47	p	p	NOUN
ejpam-6162	116	48	)	)	PUNCT
ejpam-6162	116	49	and	and	CCONJ
ejpam-6162	116	50	area	area	NOUN
ejpam-6162	116	51	mean	mean	VERB
ejpam-6162	116	52	(	(	PUNCT
ejpam-6162	116	53	a	a	X
ejpam-6162	116	54	)	)	PUNCT
ejpam-6162	116	55	,	,	PUNCT
ejpam-6162	116	56	which	which	PRON
ejpam-6162	116	57	represent	represent	VERB
ejpam-6162	116	58	specific	specific	ADJ
ejpam-6162	116	59	average	average	ADJ
ejpam-6162	116	60	values	value	NOUN
ejpam-6162	116	61	of	of	ADP
ejpam-6162	116	62	the	the	DET
ejpam-6162	116	63	cancer	cancer	NOUN
ejpam-6162	116	64	image	image	NOUN
ejpam-6162	116	65	features	feature	VERB
ejpam-6162	116	66	.	.	PUNCT
ejpam-6162	117	1	table	table	NOUN
ejpam-6162	117	2	2	2	NUM
ejpam-6162	117	3	shows	show	VERB
ejpam-6162	117	4	the	the	DET
ejpam-6162	117	5	coefficient	coefficient	NOUN
ejpam-6162	117	6	results	result	NOUN
ejpam-6162	117	7	of	of	ADP
ejpam-6162	117	8	the	the	DET
ejpam-6162	117	9	bivariate	bivariate	ADJ
ejpam-6162	117	10	correlation	correlation	NOUN
ejpam-6162	117	11	r	r	NOUN
ejpam-6162	117	12	to	to	AUX
ejpam-6162	117	13	diagnosis	diagnosis	VERB
ejpam-6162	117	14	and	and	CCONJ
ejpam-6162	117	15	the	the	DET
ejpam-6162	117	16	different	different	ADJ
ejpam-6162	117	17	logistic	logistic	ADJ
ejpam-6162	117	18	regression	regression	NOUN
ejpam-6162	117	19	estimator	estimator	NOUN
ejpam-6162	117	20	’s	’s	PART
ejpam-6162	117	21	coefficients	coefficient	NOUN
ejpam-6162	117	22	.	.	PUNCT
ejpam-6162	118	1	it	it	PRON
ejpam-6162	118	2	can	can	AUX
ejpam-6162	118	3	be	be	AUX
ejpam-6162	118	4	observed	observe	VERB
ejpam-6162	118	5	that	that	SCONJ
ejpam-6162	118	6	only	only	ADV
ejpam-6162	118	7	the	the	DET
ejpam-6162	118	8	estimated	estimate	VERB
ejpam-6162	118	9	coefficients	coefficient	NOUN
ejpam-6162	118	10	of	of	ADP
ejpam-6162	118	11	k6	k6	PROPN
ejpam-6162	118	12	,	,	PUNCT
ejpam-6162	118	13	k7	k7	PROPN
ejpam-6162	118	14	,	,	PUNCT
ejpam-6162	118	15	k8	k8	PROPN
ejpam-6162	118	16	,	,	PUNCT
ejpam-6162	118	17	and	and	CCONJ
ejpam-6162	118	18	the	the	DET
ejpam-6162	118	19	new	new	ADJ
ejpam-6162	118	20	estimator	estimator	NOUN
ejpam-6162	118	21	k9l	k9l	PROPN
ejpam-6162	118	22	has	have	VERB
ejpam-6162	118	23	the	the	DET
ejpam-6162	118	24	same	same	ADJ
ejpam-6162	118	25	sign	sign	NOUN
ejpam-6162	118	26	as	as	ADP
ejpam-6162	118	27	that	that	PRON
ejpam-6162	118	28	of	of	ADP
ejpam-6162	118	29	the	the	DET
ejpam-6162	118	30	correlation	correlation	NOUN
ejpam-6162	118	31	coefficients	coefficient	NOUN
ejpam-6162	118	32	of	of	ADP
ejpam-6162	118	33	the	the	DET
ejpam-6162	118	34	independent	independent	ADJ
ejpam-6162	118	35	variables	variable	NOUN
ejpam-6162	118	36	to	to	ADP
ejpam-6162	118	37	the	the	DET
ejpam-6162	118	38	dependent	dependent	NOUN
ejpam-6162	118	39	.	.	PUNCT
ejpam-6162	119	1	on	on	ADP
ejpam-6162	119	2	the	the	DET
ejpam-6162	119	3	other	other	ADJ
ejpam-6162	119	4	hand	hand	NOUN
ejpam-6162	119	5	,	,	PUNCT
ejpam-6162	119	6	the	the	DET
ejpam-6162	119	7	ml	ml	NOUN
ejpam-6162	119	8	and	and	CCONJ
ejpam-6162	119	9	hk	hk	PROPN
ejpam-6162	119	10	estimates	estimate	NOUN
ejpam-6162	119	11	do	do	AUX
ejpam-6162	119	12	not	not	PART
ejpam-6162	119	13	match	match	VERB
ejpam-6162	119	14	the	the	DET
ejpam-6162	119	15	signs	sign	NOUN
ejpam-6162	119	16	to	to	ADP
ejpam-6162	119	17	that	that	PRON
ejpam-6162	119	18	of	of	ADP
ejpam-6162	119	19	the	the	DET
ejpam-6162	119	20	correlation	correlation	NOUN
ejpam-6162	119	21	coefficients	coefficient	NOUN
ejpam-6162	119	22	,	,	PUNCT
ejpam-6162	119	23	a	a	DET
ejpam-6162	119	24	clear	clear	ADJ
ejpam-6162	119	25	indicator	indicator	NOUN
ejpam-6162	119	26	of	of	ADP
ejpam-6162	119	27	the	the	DET
ejpam-6162	119	28	negative	negative	ADJ
ejpam-6162	119	29	effect	effect	NOUN
ejpam-6162	119	30	of	of	ADP
ejpam-6162	119	31	multicollinearity	multicollinearity	NOUN
ejpam-6162	119	32	present	present	NOUN
ejpam-6162	119	33	in	in	ADP
ejpam-6162	119	34	the	the	DET
ejpam-6162	119	35	secondary	secondary	ADJ
ejpam-6162	119	36	data	datum	NOUN
ejpam-6162	119	37	.	.	PUNCT
ejpam-6162	120	1	table	table	NOUN
ejpam-6162	120	2	2	2	NUM
ejpam-6162	120	3	:	:	PUNCT
ejpam-6162	120	4	correlation	correlation	NOUN
ejpam-6162	120	5	coefficients	coefficient	NOUN
ejpam-6162	120	6	r	r	NOUN
ejpam-6162	120	7	and	and	CCONJ
ejpam-6162	120	8	estimated	estimate	VERB
ejpam-6162	120	9	logistic	logistic	ADJ
ejpam-6162	120	10	ridge	ridge	NOUN
ejpam-6162	120	11	coefficients	coefficient	NOUN
ejpam-6162	120	12	of	of	ADP
ejpam-6162	120	13	each	each	DET
ejpam-6162	120	14	estimator	estimator	NOUN
ejpam-6162	120	15	estimators	estimator	NOUN
ejpam-6162	120	16	var	var	NOUN
ejpam-6162	120	17	r	r	NOUN
ejpam-6162	120	18	ml	ml	PROPN
ejpam-6162	120	19	hk	hk	PROPN
ejpam-6162	120	20	k2	k2	PROPN
ejpam-6162	120	21	k3	k3	VERB
ejpam-6162	120	22	k4	k4	PROPN
ejpam-6162	120	23	k5	k5	PROPN
ejpam-6162	120	24	k6	k6	PROPN
ejpam-6162	120	25	k7	k7	PROPN
ejpam-6162	120	26	k8	k8	PROPN
ejpam-6162	120	27	k9l	k9l	ADP
ejpam-6162	120	28	r	r	NOUN
ejpam-6162	120	29	0.71	0.71	NUM
ejpam-6162	120	30	-43.9	-43.9	NUM
ejpam-6162	120	31	-43.8	-43.8	NUM
ejpam-6162	120	32	-42.4	-42.4	NUM
ejpam-6162	120	33	-40.7	-40.7	NOUN
ejpam-6162	121	1	-11.4	-11.4	NOUN
ejpam-6162	121	2	-28.1	-28.1	NUM
ejpam-6162	122	1	3.02	3.02	NUM
ejpam-6162	122	2	2.99	2.99	NUM
ejpam-6162	122	3	2.94	2.94	NUM
ejpam-6162	122	4	3.02	3.02	NUM
ejpam-6162	122	5	p	p	NOUN
ejpam-6162	122	6	0.73	0.73	NUM
ejpam-6162	122	7	38.03	38.03	NUM
ejpam-6162	122	8	37.9	37.9	NUM
ejpam-6162	122	9	36.7	36.7	NUM
ejpam-6162	122	10	35.1	35.1	NUM
ejpam-6162	122	11	9.7	9.7	NUM
ejpam-6162	122	12	24.6	24.6	NUM
ejpam-6162	122	13	0.004	0.004	NUM
ejpam-6162	122	14	0.024	0.024	NUM
ejpam-6162	122	15	0.048	0.048	NUM
ejpam-6162	122	16	0.007	0.007	NUM
ejpam-6162	122	17	a	a	DET
ejpam-6162	122	18	0.71	0.71	NUM
ejpam-6162	122	19	11.32	11.32	NUM
ejpam-6162	122	20	11.3	11.3	NUM
ejpam-6162	122	21	11.07	11.07	NUM
ejpam-6162	122	22	10.8	10.8	NUM
ejpam-6162	122	23	5.2	5.2	NUM
ejpam-6162	122	24	8.8	8.8	NUM
ejpam-6162	122	25	0.003	0.003	NUM
ejpam-6162	122	26	0.021	0.021	NUM
ejpam-6162	122	27	0.043	0.043	NUM
ejpam-6162	122	28	0.007	0.007	NUM
ejpam-6162	122	29	3.2	3.2	NUM
ejpam-6162	122	30	.	.	PUNCT
ejpam-6162	123	1	poisson	poisson	PROPN
ejpam-6162	123	2	ridge	ridge	PROPN
ejpam-6162	123	3	regression	regression	PROPN
ejpam-6162	123	4	simulation	simulation	NOUN
ejpam-6162	123	5	results	result	VERB
ejpam-6162	123	6	table	table	VERB
ejpam-6162	123	7	3	3	NUM
ejpam-6162	123	8	:	:	PUNCT
ejpam-6162	123	9	estimated	estimate	VERB
ejpam-6162	123	10	mses	ms	NOUN
ejpam-6162	123	11	for	for	ADP
ejpam-6162	123	12	the	the	DET
ejpam-6162	123	13	poisson	poisson	PROPN
ejpam-6162	123	14	ridge	ridge	PROPN
ejpam-6162	123	15	regression	regression	PROPN
ejpam-6162	123	16	simulation	simulation	NOUN
ejpam-6162	123	17	with	with	ADP
ejpam-6162	123	18	βo	βo	PROPN
ejpam-6162	123	19	=	=	SYM
ejpam-6162	123	20	0	0	NUM
ejpam-6162	123	21	and	and	CCONJ
ejpam-6162	123	22	p	p	NOUN
ejpam-6162	123	23	=	=	SYM
ejpam-6162	123	24	2	2	NUM
ejpam-6162	123	25	estimators	estimator	NOUN
ejpam-6162	123	26	p	p	NOUN
ejpam-6162	123	27	n	n	INTJ
ejpam-6162	123	28	ml	ml	ADP
ejpam-6162	123	29	hk	hk	PROPN
ejpam-6162	123	30	k2	k2	PROPN
ejpam-6162	123	31	k3	k3	VERB
ejpam-6162	123	32	k4	k4	PROPN
ejpam-6162	123	33	k5	k5	PROPN
ejpam-6162	123	34	k6	k6	PROPN
ejpam-6162	123	35	k7	k7	PROPN
ejpam-6162	123	36	k8	k8	PROPN
ejpam-6162	123	37	k9p	k9p	PROPN
ejpam-6162	123	38	0.85	0.85	NUM
ejpam-6162	123	39	15	15	NUM
ejpam-6162	123	40	0.102	0.102	NUM
ejpam-6162	123	41	0.077	0.077	NUM
ejpam-6162	123	42	0.032	0.032	NUM
ejpam-6162	123	43	0.074	0.074	NUM
ejpam-6162	123	44	0.072	0.072	NUM
ejpam-6162	123	45	0.070	0.070	NUM
ejpam-6162	123	46	0.054	0.054	NUM
ejpam-6162	123	47	0.034	0.034	NUM
ejpam-6162	123	48	0.034	0.034	NUM
ejpam-6162	123	49	0.032	0.032	NUM
ejpam-6162	123	50	0.85	0.85	NUM
ejpam-6162	123	51	20	20	NUM
ejpam-6162	123	52	0.064	0.064	NUM
ejpam-6162	123	53	0.054	0.054	NUM
ejpam-6162	123	54	0.023	0.023	NUM
ejpam-6162	123	55	0.045	0.045	NUM
ejpam-6162	123	56	0.040	0.040	NUM
ejpam-6162	123	57	0.050	0.050	NUM
ejpam-6162	123	58	0.028	0.028	NUM
ejpam-6162	123	59	0.022	0.022	NUM
ejpam-6162	123	60	0.020	0.020	NUM
ejpam-6162	123	61	0.020	0.020	NUM
ejpam-6162	123	62	0.90	0.90	NUM
ejpam-6162	123	63	15	15	NUM
ejpam-6162	123	64	0.142	0.142	NUM
ejpam-6162	123	65	0.091	0.091	NUM
ejpam-6162	123	66	0.031	0.031	NUM
ejpam-6162	123	67	0.065	0.065	NUM
ejpam-6162	123	68	0.062	0.062	NUM
ejpam-6162	123	69	0.087	0.087	NUM
ejpam-6162	123	70	0.054	0.054	NUM
ejpam-6162	123	71	0.035	0.035	NUM
ejpam-6162	123	72	0.033	0.033	NUM
ejpam-6162	123	73	0.031	0.031	NUM
ejpam-6162	123	74	0.90	0.90	NUM
ejpam-6162	123	75	20	20	NUM
ejpam-6162	123	76	0.076	0.076	NUM
ejpam-6162	123	77	0.061	0.061	NUM
ejpam-6162	123	78	0.025	0.025	NUM
ejpam-6162	123	79	0.044	0.044	NUM
ejpam-6162	123	80	0.041	0.041	NUM
ejpam-6162	123	81	0.060	0.060	NUM
ejpam-6162	123	82	0.030	0.030	NUM
ejpam-6162	123	83	0.026	0.026	NUM
ejpam-6162	123	84	0.022	0.022	NUM
ejpam-6162	123	85	0.022	0.022	NUM
ejpam-6162	123	86	0.95	0.95	NUM
ejpam-6162	123	87	10	10	NUM
ejpam-6162	123	88	2.392	2.392	NUM
ejpam-6162	123	89	0.714	0.714	NUM
ejpam-6162	123	90	0.107	0.107	NUM
ejpam-6162	123	91	0.484	0.484	NUM
ejpam-6162	123	92	0.129	0.129	NUM
ejpam-6162	123	93	0.352	0.352	NUM
ejpam-6162	123	94	0.122	0.122	NUM
ejpam-6162	123	95	0.067	0.067	NUM
ejpam-6162	123	96	0.076	0.076	NUM
ejpam-6162	123	97	0.064	0.064	NUM
ejpam-6162	123	98	0.96	0.96	NUM
ejpam-6162	123	99	10	10	NUM
ejpam-6162	123	100	4.892	4.892	NUM
ejpam-6162	123	101	0.474	0.474	NUM
ejpam-6162	123	102	0.084	0.084	NUM
ejpam-6162	123	103	0.282	0.282	NUM
ejpam-6162	123	104	0.113	0.113	NUM
ejpam-6162	123	105	0.241	0.241	NUM
ejpam-6162	123	106	0.134	0.134	NUM
ejpam-6162	123	107	0.075	0.075	NUM
ejpam-6162	123	108	0.087	0.087	NUM
ejpam-6162	123	109	0.073	0.073	NUM
ejpam-6162	123	110	0.96	0.96	NUM
ejpam-6162	123	111	20	20	NUM
ejpam-6162	123	112	0.123	0.123	NUM
ejpam-6162	123	113	0.080	0.080	NUM
ejpam-6162	123	114	0.025	0.025	NUM
ejpam-6162	123	115	0.077	0.077	NUM
ejpam-6162	123	116	0.074	0.074	NUM
ejpam-6162	123	117	0.081	0.081	NUM
ejpam-6162	123	118	0.030	0.030	NUM
ejpam-6162	123	119	0.024	0.024	NUM
ejpam-6162	123	120	0.021	0.021	NUM
ejpam-6162	123	121	0.021	0.021	NUM
ejpam-6162	123	122	0.97	0.97	NUM
ejpam-6162	123	123	10	10	NUM
ejpam-6162	123	124	2.256	2.256	NUM
ejpam-6162	123	125	0.594	0.594	NUM
ejpam-6162	123	126	0.114	0.114	NUM
ejpam-6162	123	127	0.413	0.413	NUM
ejpam-6162	123	128	0.147	0.147	NUM
ejpam-6162	123	129	0.336	0.336	NUM
ejpam-6162	123	130	0.129	0.129	NUM
ejpam-6162	123	131	0.075	0.075	NUM
ejpam-6162	123	132	0.085	0.085	NUM
ejpam-6162	123	133	0.072	0.072	NUM
ejpam-6162	123	134	0.98	0.98	NUM
ejpam-6162	123	135	10	10	NUM
ejpam-6162	123	136	2.785	2.785	NUM
ejpam-6162	123	137	0.454	0.454	NUM
ejpam-6162	123	138	0.079	0.079	NUM
ejpam-6162	123	139	0.294	0.294	NUM
ejpam-6162	123	140	0.111	0.111	NUM
ejpam-6162	123	141	0.246	0.246	NUM
ejpam-6162	123	142	0.131	0.131	NUM
ejpam-6162	123	143	0.074	0.074	NUM
ejpam-6162	123	144	0.085	0.085	NUM
ejpam-6162	123	145	0.069	0.069	NUM
ejpam-6162	123	146	0.99	0.99	NUM
ejpam-6162	123	147	20	20	NUM
ejpam-6162	123	148	0.468	0.468	NUM
ejpam-6162	123	149	0.151	0.151	NUM
ejpam-6162	123	150	0.025	0.025	NUM
ejpam-6162	123	151	0.109	0.109	NUM
ejpam-6162	123	152	0.063	0.063	NUM
ejpam-6162	123	153	0.123	0.123	NUM
ejpam-6162	123	154	0.026	0.026	NUM
ejpam-6162	123	155	0.019	0.019	NUM
ejpam-6162	123	156	0.018	0.018	NUM
ejpam-6162	123	157	0.016	0.016	NUM
ejpam-6162	123	158	in	in	ADP
ejpam-6162	123	159	poisson	poisson	PROPN
ejpam-6162	123	160	ridge	ridge	PROPN
ejpam-6162	123	161	regression	regression	PROPN
ejpam-6162	123	162	,	,	PUNCT
ejpam-6162	123	163	the	the	DET
ejpam-6162	123	164	ml	ml	NOUN
ejpam-6162	123	165	estimator	estimator	NOUN
ejpam-6162	123	166	,	,	PUNCT
ejpam-6162	123	167	the	the	DET
ejpam-6162	123	168	known	known	ADJ
ejpam-6162	123	169	hk	hk	PROPN
ejpam-6162	123	170	,	,	PUNCT
ejpam-6162	123	171	k2	k2	PROPN
ejpam-6162	123	172	to	to	ADP
ejpam-6162	123	173	k8	k8	PROPN
ejpam-6162	123	174	estimators	estimator	NOUN
ejpam-6162	123	175	and	and	CCONJ
ejpam-6162	123	176	the	the	DET
ejpam-6162	123	177	proposed	propose	VERB
ejpam-6162	123	178	k9p	k9p	PROPN
ejpam-6162	123	179	estimator	estimator	NOUN
ejpam-6162	123	180	are	be	AUX
ejpam-6162	123	181	applied	apply	VERB
ejpam-6162	123	182	and	and	CCONJ
ejpam-6162	123	183	compared	compare	VERB
ejpam-6162	123	184	in	in	ADP
ejpam-6162	123	185	simulations	simulation	NOUN
ejpam-6162	123	186	.	.	PUNCT
ejpam-6162	124	1	table	table	NOUN
ejpam-6162	124	2	3	3	NUM
ejpam-6162	124	3	shows	show	VERB
ejpam-6162	124	4	some	some	PRON
ejpam-6162	124	5	of	of	ADP
ejpam-6162	124	6	the	the	DET
ejpam-6162	124	7	simulation	simulation	NOUN
ejpam-6162	124	8	results	result	VERB
ejpam-6162	124	9	where	where	SCONJ
ejpam-6162	124	10	the	the	DET
ejpam-6162	124	11	mse	mse	NOUN
ejpam-6162	124	12	values	value	NOUN
ejpam-6162	124	13	of	of	ADP
ejpam-6162	124	14	each	each	DET
ejpam-6162	124	15	estimator	estimator	NOUN
ejpam-6162	124	16	are	be	AUX
ejpam-6162	124	17	compared	compare	VERB
ejpam-6162	124	18	when	when	SCONJ
ejpam-6162	124	19	β0	β0	PROPN
ejpam-6162	124	20	=	=	SYM
ejpam-6162	124	21	0	0	PROPN
ejpam-6162	124	22	,	,	PUNCT
ejpam-6162	124	23	ρ	ρ	PROPN
ejpam-6162	124	24	=	=	SYM
ejpam-6162	124	25	0.85	0.85	NUM
ejpam-6162	124	26	,	,	PUNCT
ejpam-6162	124	27	0.90	0.90	NUM
ejpam-6162	124	28	,	,	PUNCT
ejpam-6162	124	29	0.95	0.95	NUM
ejpam-6162	124	30	,	,	PUNCT
ejpam-6162	124	31	0.96	0.96	NUM
ejpam-6162	124	32	,	,	PUNCT
ejpam-6162	124	33	0.97	0.97	NUM
ejpam-6162	124	34	,	,	PUNCT
ejpam-6162	124	35	0.98	0.98	NUM
ejpam-6162	124	36	,	,	PUNCT
ejpam-6162	124	37	0.99	0.99	NUM
ejpam-6162	124	38	,	,	PUNCT
ejpam-6162	124	39	p	p	X
ejpam-6162	124	40	=	=	NOUN
ejpam-6162	124	41	2	2	NUM
ejpam-6162	124	42	,	,	PUNCT
ejpam-6162	124	43	3	3	NUM
ejpam-6162	124	44	with	with	ADP
ejpam-6162	124	45	n	n	NOUN
ejpam-6162	124	46	=	=	SYM
ejpam-6162	124	47	10	10	NUM
ejpam-6162	124	48	,	,	PUNCT
ejpam-6162	124	49	15	15	NUM
ejpam-6162	124	50	,	,	PUNCT
ejpam-6162	124	51	20	20	NUM
ejpam-6162	124	52	,	,	PUNCT
ejpam-6162	124	53	30	30	NUM
ejpam-6162	124	54	,	,	PUNCT
ejpam-6162	124	55	50	50	NUM
ejpam-6162	124	56	.	.	PUNCT
ejpam-6162	125	1	it	it	PRON
ejpam-6162	125	2	has	have	AUX
ejpam-6162	125	3	been	be	AUX
ejpam-6162	125	4	observed	observe	VERB
ejpam-6162	125	5	that	that	SCONJ
ejpam-6162	125	6	the	the	DET
ejpam-6162	125	7	new	new	ADJ
ejpam-6162	125	8	poisson	poisson	PROPN
ejpam-6162	125	9	ridge	ridge	PROPN
ejpam-6162	125	10	estimator	estimator	PROPN
ejpam-6162	125	11	(	(	PUNCT
ejpam-6162	125	12	k9p	k9p	PROPN
ejpam-6162	125	13	)	)	PUNCT
ejpam-6162	125	14	has	have	VERB
ejpam-6162	125	15	the	the	DET
ejpam-6162	125	16	least	least	ADJ
ejpam-6162	125	17	mse	mse	NOUN
ejpam-6162	125	18	in	in	ADP
ejpam-6162	125	19	some	some	DET
ejpam-6162	125	20	cases	case	NOUN
ejpam-6162	125	21	.	.	PUNCT
ejpam-6162	126	1	specifically	specifically	ADV
ejpam-6162	126	2	,	,	PUNCT
ejpam-6162	126	3	when	when	SCONJ
ejpam-6162	126	4	β0	β0	PROPN
ejpam-6162	126	5	=	=	NOUN
ejpam-6162	126	6	0	0	PROPN
ejpam-6162	126	7	,	,	PUNCT
ejpam-6162	126	8	p	p	NOUN
ejpam-6162	126	9	=	=	NOUN
ejpam-6162	126	10	2	2	NUM
ejpam-6162	126	11	,	,	PUNCT
ejpam-6162	126	12	3	3	NUM
ejpam-6162	126	13	at	at	ADP
ejpam-6162	126	14	the	the	DET
ejpam-6162	126	15	different	different	ADJ
ejpam-6162	126	16	levels	level	NOUN
ejpam-6162	126	17	of	of	ADP
ejpam-6162	126	18	ρ	ρ	NOUN
ejpam-6162	126	19	and	and	CCONJ
ejpam-6162	126	20	values	value	NOUN
ejpam-6162	126	21	of	of	ADP
ejpam-6162	126	22	n.	n.	PROPN
ejpam-6162	126	23	j.	j.	PROPN
ejpam-6162	126	24	mohamad	mohamad	PROPN
ejpam-6162	126	25	,	,	PUNCT
ejpam-6162	126	26	et	et	PROPN
ejpam-6162	126	27	.	.	PUNCT
ejpam-6162	127	1	al	al	PROPN
ejpam-6162	127	2	.	.	PUNCT
ejpam-6162	127	3	/	/	SYM
ejpam-6162	127	4	eur	eur	PROPN
ejpam-6162	127	5	.	.	PUNCT
ejpam-6162	128	1	j.	j.	PROPN
ejpam-6162	128	2	pure	pure	PROPN
ejpam-6162	128	3	appl	appl	PROPN
ejpam-6162	128	4	.	.	PROPN
ejpam-6162	128	5	math	math	PROPN
ejpam-6162	128	6	,	,	PUNCT
ejpam-6162	128	7	18	18	NUM
ejpam-6162	128	8	(	(	PUNCT
ejpam-6162	128	9	2	2	NUM
ejpam-6162	128	10	)	)	PUNCT
ejpam-6162	128	11	(	(	PUNCT
ejpam-6162	128	12	2025	2025	NUM
ejpam-6162	128	13	)	)	PUNCT
ejpam-6162	128	14	,	,	PUNCT
ejpam-6162	128	15	6162	6162	NUM
ejpam-6162	128	16	7	7	NUM
ejpam-6162	128	17	of	of	ADP
ejpam-6162	128	18	10	10	NUM
ejpam-6162	128	19	applying	apply	VERB
ejpam-6162	128	20	the	the	DET
ejpam-6162	128	21	poisson	poisson	PROPN
ejpam-6162	128	22	ridge	ridge	NOUN
ejpam-6162	128	23	estimators	estimator	NOUN
ejpam-6162	128	24	to	to	ADP
ejpam-6162	128	25	the	the	DET
ejpam-6162	128	26	secondary	secondary	ADJ
ejpam-6162	128	27	data	datum	NOUN
ejpam-6162	128	28	from	from	ADP
ejpam-6162	128	29	the	the	DET
ejpam-6162	128	30	botswana	botswana	PROPN
ejpam-6162	128	31	demographic	demographic	ADJ
ejpam-6162	128	32	and	and	CCONJ
ejpam-6162	128	33	health	health	NOUN
ejpam-6162	128	34	survey	survey	NOUN
ejpam-6162	128	35	(	(	PUNCT
ejpam-6162	128	36	central	central	ADJ
ejpam-6162	128	37	statistics	statistic	NOUN
ejpam-6162	128	38	office	office	NOUN
ejpam-6162	128	39	,	,	PUNCT
ejpam-6162	128	40	1988	1988	NUM
ejpam-6162	128	41	)	)	PUNCT
ejpam-6162	128	42	.	.	PUNCT
ejpam-6162	129	1	we	we	PRON
ejpam-6162	129	2	set	set	VERB
ejpam-6162	129	3	the	the	DET
ejpam-6162	129	4	number	number	NOUN
ejpam-6162	129	5	of	of	ADP
ejpam-6162	129	6	children	child	NOUN
ejpam-6162	129	7	as	as	ADP
ejpam-6162	129	8	the	the	DET
ejpam-6162	129	9	dependent	dependent	ADJ
ejpam-6162	129	10	variable	variable	NOUN
ejpam-6162	129	11	,	,	PUNCT
ejpam-6162	129	12	and	and	CCONJ
ejpam-6162	129	13	year	year	NOUN
ejpam-6162	129	14	born	bear	VERB
ejpam-6162	129	15	and	and	CCONJ
ejpam-6162	129	16	age	age	NOUN
ejpam-6162	129	17	as	as	ADP
ejpam-6162	129	18	the	the	DET
ejpam-6162	129	19	independent	independent	ADJ
ejpam-6162	129	20	variables	variable	NOUN
ejpam-6162	129	21	.	.	PUNCT
ejpam-6162	130	1	table	table	NOUN
ejpam-6162	130	2	4	4	NUM
ejpam-6162	130	3	shows	show	VERB
ejpam-6162	130	4	the	the	DET
ejpam-6162	130	5	coefficient	coefficient	NOUN
ejpam-6162	130	6	results	result	NOUN
ejpam-6162	130	7	of	of	ADP
ejpam-6162	130	8	the	the	DET
ejpam-6162	130	9	bivariate	bivariate	ADJ
ejpam-6162	130	10	correlation	correlation	NOUN
ejpam-6162	130	11	coefficients	coefficient	VERB
ejpam-6162	130	12	r	r	NOUN
ejpam-6162	130	13	to	to	ADP
ejpam-6162	130	14	the	the	DET
ejpam-6162	130	15	number	number	NOUN
ejpam-6162	130	16	of	of	ADP
ejpam-6162	130	17	children	child	NOUN
ejpam-6162	130	18	and	and	CCONJ
ejpam-6162	130	19	the	the	DET
ejpam-6162	130	20	different	different	ADJ
ejpam-6162	130	21	poisson	poisson	NOUN
ejpam-6162	130	22	regression	regression	PROPN
ejpam-6162	130	23	estimator	estimator	NOUN
ejpam-6162	130	24	’s	’s	PART
ejpam-6162	130	25	coefficients	coefficient	NOUN
ejpam-6162	130	26	.	.	PUNCT
ejpam-6162	131	1	it	it	PRON
ejpam-6162	131	2	is	be	AUX
ejpam-6162	131	3	observed	observe	VERB
ejpam-6162	131	4	that	that	SCONJ
ejpam-6162	131	5	k3	k3	VERB
ejpam-6162	131	6	to	to	ADP
ejpam-6162	131	7	k8	k8	PROPN
ejpam-6162	131	8	and	and	CCONJ
ejpam-6162	131	9	the	the	DET
ejpam-6162	131	10	proposed	propose	VERB
ejpam-6162	131	11	k9p	k9p	PROPN
ejpam-6162	131	12	estimated	estimate	VERB
ejpam-6162	131	13	coefficients	coefficient	NOUN
ejpam-6162	131	14	coincides	coincide	VERB
ejpam-6162	131	15	with	with	ADP
ejpam-6162	131	16	the	the	DET
ejpam-6162	131	17	signs	sign	NOUN
ejpam-6162	131	18	in	in	ADP
ejpam-6162	131	19	the	the	DET
ejpam-6162	131	20	correlation	correlation	NOUN
ejpam-6162	131	21	coefficients	coefficient	NOUN
ejpam-6162	131	22	of	of	ADP
ejpam-6162	131	23	the	the	DET
ejpam-6162	131	24	independent	independent	ADJ
ejpam-6162	131	25	variables	variable	NOUN
ejpam-6162	131	26	to	to	ADP
ejpam-6162	131	27	the	the	DET
ejpam-6162	131	28	dependent	dependent	NOUN
ejpam-6162	131	29	.	.	PUNCT
ejpam-6162	132	1	on	on	ADP
ejpam-6162	132	2	the	the	DET
ejpam-6162	132	3	other	other	ADJ
ejpam-6162	132	4	hand	hand	NOUN
ejpam-6162	132	5	,	,	PUNCT
ejpam-6162	132	6	the	the	DET
ejpam-6162	132	7	ml	ml	NOUN
ejpam-6162	132	8	and	and	CCONJ
ejpam-6162	132	9	hk	hk	PROPN
ejpam-6162	132	10	estimated	estimate	VERB
ejpam-6162	132	11	coefficients	coefficient	NOUN
ejpam-6162	132	12	does	do	AUX
ejpam-6162	132	13	not	not	PART
ejpam-6162	132	14	match	match	VERB
ejpam-6162	132	15	the	the	DET
ejpam-6162	132	16	sign	sign	NOUN
ejpam-6162	132	17	of	of	ADP
ejpam-6162	132	18	the	the	DET
ejpam-6162	132	19	correlation	correlation	NOUN
ejpam-6162	132	20	coefficient	coefficient	VERB
ejpam-6162	132	21	an	an	DET
ejpam-6162	132	22	indication	indication	NOUN
ejpam-6162	132	23	of	of	ADP
ejpam-6162	132	24	the	the	DET
ejpam-6162	132	25	negative	negative	ADJ
ejpam-6162	132	26	effect	effect	NOUN
ejpam-6162	132	27	of	of	ADP
ejpam-6162	132	28	multicollinearity	multicollinearity	NOUN
ejpam-6162	132	29	in	in	ADP
ejpam-6162	132	30	the	the	DET
ejpam-6162	132	31	secondary	secondary	ADJ
ejpam-6162	132	32	data	datum	NOUN
ejpam-6162	132	33	.	.	PUNCT
ejpam-6162	133	1	table	table	NOUN
ejpam-6162	133	2	4	4	NUM
ejpam-6162	133	3	:	:	PUNCT
ejpam-6162	133	4	correlation	correlation	NOUN
ejpam-6162	133	5	coefficients	coefficient	NOUN
ejpam-6162	133	6	r	r	NOUN
ejpam-6162	133	7	and	and	CCONJ
ejpam-6162	133	8	estimated	estimate	VERB
ejpam-6162	133	9	poisson	poisson	PROPN
ejpam-6162	133	10	ridge	ridge	PROPN
ejpam-6162	133	11	coefficients	coefficient	NOUN
ejpam-6162	133	12	of	of	ADP
ejpam-6162	133	13	estimators	estimator	NOUN
ejpam-6162	133	14	estimators	estimator	NOUN
ejpam-6162	133	15	var	var	AUX
ejpam-6162	133	16	r	r	NOUN
ejpam-6162	133	17	ml	ml	PROPN
ejpam-6162	133	18	hk	hk	PROPN
ejpam-6162	133	19	k2	k2	PROPN
ejpam-6162	133	20	k3	k3	VERB
ejpam-6162	133	21	k4	k4	PROPN
ejpam-6162	133	22	k5	k5	PROPN
ejpam-6162	133	23	k6	k6	PROPN
ejpam-6162	133	24	k7	k7	PROPN
ejpam-6162	133	25	k8	k8	PROPN
ejpam-6162	133	26	k9p	k9p	PROPN
ejpam-6162	133	27	year	year	NOUN
ejpam-6162	133	28	-0.73	-0.73	ADP
ejpam-6162	133	29	4.9	4.9	NUM
ejpam-6162	133	30	0.393	0.393	NUM
ejpam-6162	133	31	1.32	1.32	NUM
ejpam-6162	133	32	-0.53	-0.53	NOUN
ejpam-6162	133	33	-0.57	-0.57	X
ejpam-6162	133	34	-0.57	-0.57	X
ejpam-6162	133	35	-0.59	-0.59	NUM
ejpam-6162	133	36	-0.55	-0.55	NUM
ejpam-6162	133	37	-0.58	-0.58	NUM
ejpam-6162	133	38	-0.57	-0.57	PROPN
ejpam-6162	133	39	age	age	NOUN
ejpam-6162	133	40	0.74	0.74	NUM
ejpam-6162	133	41	5.53	5.53	NUM
ejpam-6162	133	42	1.00	1.00	NUM
ejpam-6162	133	43	1.93	1.93	NUM
ejpam-6162	133	44	0.074	0.074	NUM
ejpam-6162	133	45	0.03	0.03	NUM
ejpam-6162	133	46	0.029	0.029	NUM
ejpam-6162	133	47	0.012	0.012	NUM
ejpam-6162	133	48	0.047	0.047	NUM
ejpam-6162	133	49	0.022	0.022	NUM
ejpam-6162	133	50	0.031	0.031	NUM
ejpam-6162	133	51	3.3	3.3	NUM
ejpam-6162	133	52	.	.	PUNCT
ejpam-6162	134	1	multiple	multiple	PROPN
ejpam-6162	134	2	ridge	ridge	PROPN
ejpam-6162	134	3	regression	regression	PROPN
ejpam-6162	134	4	simulation	simulation	NOUN
ejpam-6162	134	5	results	result	VERB
ejpam-6162	134	6	in	in	ADP
ejpam-6162	134	7	the	the	DET
ejpam-6162	134	8	multiple	multiple	PROPN
ejpam-6162	134	9	ridge	ridge	PROPN
ejpam-6162	134	10	regression	regression	NOUN
ejpam-6162	134	11	,	,	PUNCT
ejpam-6162	134	12	table	table	NOUN
ejpam-6162	134	13	5	5	NUM
ejpam-6162	134	14	shows	show	VERB
ejpam-6162	134	15	some	some	DET
ejpam-6162	134	16	results	result	NOUN
ejpam-6162	134	17	of	of	ADP
ejpam-6162	134	18	the	the	DET
ejpam-6162	134	19	simulation	simulation	NOUN
ejpam-6162	134	20	where	where	SCONJ
ejpam-6162	134	21	the	the	DET
ejpam-6162	134	22	mse	mse	NOUN
ejpam-6162	134	23	values	value	NOUN
ejpam-6162	134	24	of	of	ADP
ejpam-6162	134	25	each	each	DET
ejpam-6162	134	26	estimator	estimator	NOUN
ejpam-6162	134	27	.	.	PUNCT
ejpam-6162	135	1	overall	overall	ADV
ejpam-6162	135	2	,	,	PUNCT
ejpam-6162	135	3	it	it	PRON
ejpam-6162	135	4	has	have	AUX
ejpam-6162	135	5	been	be	AUX
ejpam-6162	135	6	observed	observe	VERB
ejpam-6162	135	7	that	that	SCONJ
ejpam-6162	135	8	the	the	DET
ejpam-6162	135	9	proposed	propose	VERB
ejpam-6162	135	10	ridge	ridge	PROPN
ejpam-6162	135	11	estimator	estimator	PROPN
ejpam-6162	135	12	k9	k9	PROPN
ejpam-6162	135	13	m	m	PROPN
ejpam-6162	135	14	has	have	VERB
ejpam-6162	135	15	the	the	DET
ejpam-6162	135	16	least	least	ADJ
ejpam-6162	135	17	mse	mse	NOUN
ejpam-6162	135	18	in	in	ADP
ejpam-6162	135	19	some	some	DET
ejpam-6162	135	20	cases	case	NOUN
ejpam-6162	135	21	.	.	PUNCT
ejpam-6162	136	1	specifically	specifically	ADV
ejpam-6162	136	2	,	,	PUNCT
ejpam-6162	136	3	when	when	SCONJ
ejpam-6162	136	4	ρ	ρ	PROPN
ejpam-6162	136	5	≥	≥	NOUN
ejpam-6162	136	6	0.72	0.72	NUM
ejpam-6162	136	7	,	,	PUNCT
ejpam-6162	136	8	p	p	PRON
ejpam-6162	136	9	≥	≥	NUM
ejpam-6162	136	10	3	3	NUM
ejpam-6162	136	11	and	and	CCONJ
ejpam-6162	136	12	n	n	PRON
ejpam-6162	136	13	≥	≥	NUM
ejpam-6162	136	14	10	10	NUM
ejpam-6162	136	15	.	.	PUNCT
ejpam-6162	136	16	table	table	NOUN
ejpam-6162	136	17	5	5	NUM
ejpam-6162	136	18	:	:	PUNCT
ejpam-6162	136	19	estimated	estimate	VERB
ejpam-6162	136	20	mses	ms	NOUN
ejpam-6162	136	21	for	for	ADP
ejpam-6162	136	22	the	the	DET
ejpam-6162	136	23	multiple	multiple	PROPN
ejpam-6162	136	24	ridge	ridge	PROPN
ejpam-6162	136	25	regression	regression	PROPN
ejpam-6162	136	26	simulation	simulation	NOUN
ejpam-6162	136	27	with	with	ADP
ejpam-6162	136	28	p	p	NOUN
ejpam-6162	136	29	=	=	SYM
ejpam-6162	136	30	3	3	NUM
ejpam-6162	136	31	estimators	estimator	NOUN
ejpam-6162	136	32	p	p	NOUN
ejpam-6162	136	33	n	n	INTJ
ejpam-6162	136	34	ml	ml	ADP
ejpam-6162	136	35	hk	hk	PROPN
ejpam-6162	136	36	k2	k2	PROPN
ejpam-6162	136	37	k3	k3	VERB
ejpam-6162	136	38	k4	k4	PROPN
ejpam-6162	136	39	k5	k5	PROPN
ejpam-6162	136	40	k6	k6	PROPN
ejpam-6162	136	41	k7	k7	PROPN
ejpam-6162	136	42	k8	k8	PROPN
ejpam-6162	136	43	k9	k9	PROPN
ejpam-6162	136	44	m	m	PROPN
ejpam-6162	136	45	0.72	0.72	NUM
ejpam-6162	136	46	10	10	NUM
ejpam-6162	136	47	0.083	0.083	NUM
ejpam-6162	136	48	0.064	0.064	NUM
ejpam-6162	136	49	0.039	0.039	NUM
ejpam-6162	136	50	0.047	0.047	NUM
ejpam-6162	136	51	0.437	0.437	NUM
ejpam-6162	136	52	0.049	0.049	NUM
ejpam-6162	136	53	0.026	0.026	NUM
ejpam-6162	136	54	0.037	0.037	NUM
ejpam-6162	136	55	0.032	0.032	NUM
ejpam-6162	136	56	0.024	0.024	NUM
ejpam-6162	136	57	0.72	0.72	NUM
ejpam-6162	136	58	20	20	NUM
ejpam-6162	136	59	0.032	0.032	NUM
ejpam-6162	136	60	0.029	0.029	NUM
ejpam-6162	136	61	0.023	0.023	NUM
ejpam-6162	136	62	0.027	0.027	NUM
ejpam-6162	136	63	0.024	0.024	NUM
ejpam-6162	136	64	0.027	0.027	NUM
ejpam-6162	136	65	0.018	0.018	NUM
ejpam-6162	136	66	0.024	0.024	NUM
ejpam-6162	136	67	0.023	0.023	NUM
ejpam-6162	136	68	0.014	0.014	NUM
ejpam-6162	136	69	0.72	0.72	NUM
ejpam-6162	136	70	100	100	NUM
ejpam-6162	136	71	0.007	0.007	NUM
ejpam-6162	136	72	0.007	0.007	NUM
ejpam-6162	136	73	0.006	0.006	NUM
ejpam-6162	136	74	0.004	0.004	NUM
ejpam-6162	136	75	0.005	0.005	NUM
ejpam-6162	136	76	0.006	0.006	NUM
ejpam-6162	136	77	0.006	0.006	NUM
ejpam-6162	136	78	0.007	0.007	NUM
ejpam-6162	136	79	0.007	0.007	NUM
ejpam-6162	136	80	0.004	0.004	NUM
ejpam-6162	136	81	0.85	0.85	NUM
ejpam-6162	136	82	10	10	NUM
ejpam-6162	136	83	0.157	0.157	NUM
ejpam-6162	136	84	0.106	0.106	NUM
ejpam-6162	136	85	0.051	0.051	NUM
ejpam-6162	136	86	0.066	0.066	NUM
ejpam-6162	136	87	0.060	0.060	NUM
ejpam-6162	136	88	0.084	0.084	NUM
ejpam-6162	136	89	0.026	0.026	NUM
ejpam-6162	136	90	0.041	0.041	NUM
ejpam-6162	136	91	0.034	0.034	NUM
ejpam-6162	136	92	0.022	0.022	NUM
ejpam-6162	136	93	0.85	0.85	NUM
ejpam-6162	136	94	20	20	NUM
ejpam-6162	136	95	0.057	0.057	NUM
ejpam-6162	136	96	0.047	0.047	NUM
ejpam-6162	136	97	0.031	0.031	NUM
ejpam-6162	136	98	0.031	0.031	NUM
ejpam-6162	136	99	0.032	0.032	NUM
ejpam-6162	136	100	0.045	0.045	NUM
ejpam-6162	136	101	0.021	0.021	NUM
ejpam-6162	136	102	0.033	0.033	NUM
ejpam-6162	136	103	0.029	0.029	NUM
ejpam-6162	136	104	0.012	0.012	NUM
ejpam-6162	136	105	0.85	0.85	NUM
ejpam-6162	136	106	150	150	NUM
ejpam-6162	136	107	0.006	0.006	NUM
ejpam-6162	136	108	0.006	0.006	NUM
ejpam-6162	136	109	0.006	0.006	NUM
ejpam-6162	136	110	0.005	0.005	NUM
ejpam-6162	136	111	0.005	0.005	NUM
ejpam-6162	136	112	0.006	0.006	NUM
ejpam-6162	136	113	0.005	0.005	NUM
ejpam-6162	136	114	0.006	0.006	NUM
ejpam-6162	136	115	0.006	0.006	NUM
ejpam-6162	136	116	0.005	0.005	NUM
ejpam-6162	136	117	0.90	0.90	NUM
ejpam-6162	136	118	10	10	NUM
ejpam-6162	136	119	0.220	0.220	NUM
ejpam-6162	136	120	0.134	0.134	NUM
ejpam-6162	136	121	0.058	0.058	NUM
ejpam-6162	136	122	0.072	0.072	NUM
ejpam-6162	136	123	0.063	0.063	NUM
ejpam-6162	136	124	0.102	0.102	NUM
ejpam-6162	136	125	0.022	0.022	NUM
ejpam-6162	136	126	0.036	0.036	NUM
ejpam-6162	136	127	0.030	0.030	NUM
ejpam-6162	136	128	0.018	0.018	NUM
ejpam-6162	136	129	0.90	0.90	NUM
ejpam-6162	136	130	20	20	NUM
ejpam-6162	136	131	0.083	0.083	NUM
ejpam-6162	136	132	0.064	0.064	NUM
ejpam-6162	136	133	0.037	0.037	NUM
ejpam-6162	136	134	0.040	0.040	NUM
ejpam-6162	136	135	0.041	0.041	NUM
ejpam-6162	136	136	0.063	0.063	NUM
ejpam-6162	136	137	0.022	0.022	NUM
ejpam-6162	136	138	0.037	0.037	NUM
ejpam-6162	136	139	0.033	0.033	NUM
ejpam-6162	136	140	0.013	0.013	NUM
ejpam-6162	136	141	0.90	0.90	NUM
ejpam-6162	136	142	30	30	NUM
ejpam-6162	136	143	0.049	0.049	NUM
ejpam-6162	136	144	0.041	0.041	NUM
ejpam-6162	136	145	0.027	0.027	NUM
ejpam-6162	136	146	0.026	0.026	NUM
ejpam-6162	136	147	0.027	0.027	NUM
ejpam-6162	136	148	0.041	0.041	NUM
ejpam-6162	136	149	0.019	0.019	NUM
ejpam-6162	136	150	0.030	0.030	NUM
ejpam-6162	136	151	0.028	0.028	NUM
ejpam-6162	136	152	0.009	0.009	NUM
ejpam-6162	136	153	0.95	0.95	NUM
ejpam-6162	136	154	10	10	NUM
ejpam-6162	136	155	0.472	0.472	NUM
ejpam-6162	136	156	0.276	0.276	NUM
ejpam-6162	136	157	0.103	0.103	NUM
ejpam-6162	136	158	0.128	0.128	NUM
ejpam-6162	136	159	0.082	0.082	NUM
ejpam-6162	136	160	0.161	0.161	NUM
ejpam-6162	136	161	0.019	0.019	NUM
ejpam-6162	136	162	0.030	0.030	NUM
ejpam-6162	136	163	0.024	0.024	NUM
ejpam-6162	136	164	0.018	0.018	NUM
ejpam-6162	136	165	0.95	0.95	NUM
ejpam-6162	136	166	20	20	NUM
ejpam-6162	136	167	0.161	0.161	NUM
ejpam-6162	136	168	0.105	0.105	NUM
ejpam-6162	136	169	0.047	0.047	NUM
ejpam-6162	136	170	0.056	0.056	NUM
ejpam-6162	136	171	0.056	0.056	NUM
ejpam-6162	136	172	0.098	0.098	NUM
ejpam-6162	136	173	0.020	0.020	NUM
ejpam-6162	136	174	0.037	0.037	NUM
ejpam-6162	136	175	0.029	0.029	NUM
ejpam-6162	136	176	0.012	0.012	NUM
ejpam-6162	136	177	0.95	0.95	NUM
ejpam-6162	136	178	30	30	NUM
ejpam-6162	136	179	0.109	0.109	NUM
ejpam-6162	136	180	0.080	0.080	NUM
ejpam-6162	136	181	0.042	0.042	NUM
ejpam-6162	136	182	0.046	0.046	NUM
ejpam-6162	136	183	0.048	0.048	NUM
ejpam-6162	136	184	0.079	0.079	NUM
ejpam-6162	136	185	0.022	0.022	NUM
ejpam-6162	136	186	0.038	0.038	NUM
ejpam-6162	136	187	0.033	0.033	NUM
ejpam-6162	136	188	0.010	0.010	NUM
ejpam-6162	136	189	applying	apply	VERB
ejpam-6162	136	190	the	the	DET
ejpam-6162	136	191	estimators	estimator	NOUN
ejpam-6162	136	192	to	to	ADP
ejpam-6162	136	193	secondary	secondary	ADJ
ejpam-6162	136	194	data	datum	NOUN
ejpam-6162	136	195	obtained	obtain	VERB
ejpam-6162	136	196	from	from	ADP
ejpam-6162	136	197	the	the	DET
ejpam-6162	136	198	world	world	NOUN
ejpam-6162	136	199	bank	bank	PROPN
ejpam-6162	136	200	(	(	PUNCT
ejpam-6162	136	201	2023	2023	NUM
ejpam-6162	136	202	)	)	PUNCT
ejpam-6162	136	203	,	,	PUNCT
ejpam-6162	136	204	which	which	PRON
ejpam-6162	136	205	provides	provide	VERB
ejpam-6162	136	206	economic	economic	ADJ
ejpam-6162	136	207	and	and	CCONJ
ejpam-6162	136	208	labor	labor	NOUN
ejpam-6162	136	209	data	datum	NOUN
ejpam-6162	136	210	for	for	ADP
ejpam-6162	136	211	the	the	DET
ejpam-6162	136	212	philippines	philippine	NOUN
ejpam-6162	136	213	from	from	ADP
ejpam-6162	136	214	2010–2021	2010–2021	NUM
ejpam-6162	136	215	as	as	SCONJ
ejpam-6162	136	216	shown	show	VERB
ejpam-6162	136	217	in	in	ADP
ejpam-6162	136	218	table	table	NOUN
ejpam-6162	136	219	6	6	NUM
ejpam-6162	136	220	.	.	PUNCT
ejpam-6162	137	1	we	we	PRON
ejpam-6162	137	2	set	set	VERB
ejpam-6162	137	3	the	the	DET
ejpam-6162	137	4	dependent	dependent	ADJ
ejpam-6162	137	5	variable	variable	ADJ
ejpam-6162	137	6	unemployment	unemployment	NOUN
ejpam-6162	137	7	as	as	ADP
ejpam-6162	137	8	percent	percent	NOUN
ejpam-6162	137	9	of	of	ADP
ejpam-6162	137	10	total	total	ADJ
ejpam-6162	137	11	labor	labor	NOUN
ejpam-6162	137	12	force	force	NOUN
ejpam-6162	137	13	regressed	regress	VERB
ejpam-6162	137	14	by	by	ADP
ejpam-6162	137	15	the	the	DET
ejpam-6162	137	16	independent	independent	ADJ
ejpam-6162	137	17	variables	variable	NOUN
ejpam-6162	137	18	consumer	consumer	NOUN
ejpam-6162	137	19	price	price	NOUN
ejpam-6162	137	20	index	index	NOUN
ejpam-6162	137	21	or	or	CCONJ
ejpam-6162	137	22	cpi	cpi	PROPN
ejpam-6162	137	23	(	(	PUNCT
ejpam-6162	137	24	2010	2010	NUM
ejpam-6162	137	25	base	base	NOUN
ejpam-6162	137	26	year	year	NOUN
ejpam-6162	137	27	)	)	PUNCT
ejpam-6162	137	28	,	,	PUNCT
ejpam-6162	137	29	j.	j.	PROPN
ejpam-6162	137	30	mohamad	mohamad	PROPN
ejpam-6162	137	31	,	,	PUNCT
ejpam-6162	137	32	et	et	PROPN
ejpam-6162	137	33	.	.	PUNCT
ejpam-6162	138	1	al	al	PROPN
ejpam-6162	138	2	.	.	PUNCT
ejpam-6162	138	3	/	/	SYM
ejpam-6162	138	4	eur	eur	PROPN
ejpam-6162	138	5	.	.	PUNCT
ejpam-6162	139	1	j.	j.	PROPN
ejpam-6162	139	2	pure	pure	PROPN
ejpam-6162	139	3	appl	appl	PROPN
ejpam-6162	139	4	.	.	PROPN
ejpam-6162	139	5	math	math	PROPN
ejpam-6162	139	6	,	,	PUNCT
ejpam-6162	139	7	18	18	NUM
ejpam-6162	139	8	(	(	PUNCT
ejpam-6162	139	9	2	2	NUM
ejpam-6162	139	10	)	)	PUNCT
ejpam-6162	139	11	(	(	PUNCT
ejpam-6162	139	12	2025	2025	NUM
ejpam-6162	139	13	)	)	PUNCT
ejpam-6162	139	14	,	,	PUNCT
ejpam-6162	139	15	6162	6162	NUM
ejpam-6162	139	16	8	8	NUM
ejpam-6162	139	17	of	of	ADP
ejpam-6162	139	18	10	10	NUM
ejpam-6162	139	19	wholesale	wholesale	ADJ
ejpam-6162	139	20	price	price	NOUN
ejpam-6162	139	21	index	index	NOUN
ejpam-6162	139	22	or	or	CCONJ
ejpam-6162	139	23	wpi	wpi	NOUN
ejpam-6162	139	24	(	(	PUNCT
ejpam-6162	139	25	2010	2010	NUM
ejpam-6162	139	26	base	base	NOUN
ejpam-6162	139	27	year	year	NOUN
ejpam-6162	139	28	)	)	PUNCT
ejpam-6162	139	29	,	,	PUNCT
ejpam-6162	139	30	total	total	ADJ
ejpam-6162	139	31	labor	labor	NOUN
ejpam-6162	139	32	force	force	NOUN
ejpam-6162	139	33	or	or	CCONJ
ejpam-6162	139	34	labor	labor	NOUN
ejpam-6162	139	35	(	(	PUNCT
ejpam-6162	139	36	l	l	NOUN
ejpam-6162	139	37	)	)	PUNCT
ejpam-6162	139	38	,	,	PUNCT
ejpam-6162	139	39	total	total	ADJ
ejpam-6162	139	40	population	population	NOUN
ejpam-6162	139	41	(	(	PUNCT
ejpam-6162	139	42	p	p	NOUN
ejpam-6162	139	43	)	)	PUNCT
ejpam-6162	139	44	,	,	PUNCT
ejpam-6162	139	45	and	and	CCONJ
ejpam-6162	139	46	household	household	NOUN
ejpam-6162	139	47	(	(	PUNCT
ejpam-6162	139	48	h	h	NOUN
ejpam-6162	139	49	)	)	PUNCT
ejpam-6162	139	50	final	final	ADJ
ejpam-6162	139	51	consumption	consumption	NOUN
ejpam-6162	139	52	expenditure	expenditure	NOUN
ejpam-6162	139	53	(	(	PUNCT
ejpam-6162	139	54	annual	annual	ADJ
ejpam-6162	139	55	percent	percent	NOUN
ejpam-6162	139	56	growth	growth	NOUN
ejpam-6162	139	57	)	)	PUNCT
ejpam-6162	139	58	data	datum	NOUN
ejpam-6162	139	59	from	from	ADP
ejpam-6162	139	60	year	year	NOUN
ejpam-6162	139	61	2010	2010	NUM
ejpam-6162	139	62	to	to	ADP
ejpam-6162	139	63	2021	2021	NUM
ejpam-6162	139	64	.	.	PUNCT
ejpam-6162	140	1	table	table	NOUN
ejpam-6162	140	2	6	6	NUM
ejpam-6162	140	3	:	:	PUNCT
ejpam-6162	140	4	some	some	DET
ejpam-6162	140	5	philippine	philippine	ADJ
ejpam-6162	140	6	indicator	indicator	NOUN
ejpam-6162	140	7	values	value	NOUN
ejpam-6162	140	8	from	from	ADP
ejpam-6162	140	9	world	world	PROPN
ejpam-6162	140	10	bank	bank	PROPN
ejpam-6162	140	11	(	(	PUNCT
ejpam-6162	140	12	2023	2023	NUM
ejpam-6162	140	13	)	)	PUNCT
ejpam-6162	140	14	year	year	NOUN
ejpam-6162	140	15	cpi	cpi	PROPN
ejpam-6162	140	16	wpi	wpi	PROPN
ejpam-6162	140	17	labor(l	labor(l	PROPN
ejpam-6162	140	18	)	)	PUNCT
ejpam-6162	140	19	population(p	population(p	PROPN
ejpam-6162	140	20	)	)	PUNCT
ejpam-6162	140	21	household(h	household(h	NOUN
ejpam-6162	140	22	)	)	PUNCT
ejpam-6162	140	23	unemployment	unemployment	NOUN
ejpam-6162	140	24	2010	2010	NUM
ejpam-6162	140	25	100.0000	100.0000	NUM
ejpam-6162	140	26	100.0000	100.0000	NUM
ejpam-6162	140	27	38081598	38081598	NUM
ejpam-6162	140	28	38081598	38081598	NUM
ejpam-6162	140	29	3.589800	3.589800	NUM
ejpam-6162	140	30	3.61	3.61	NUM
ejpam-6162	140	31	2011	2011	NUM
ejpam-6162	140	32	104.7184	104.7184	NUM
ejpam-6162	140	33	108.6630	108.6630	NUM
ejpam-6162	140	34	39490704	39490704	NUM
ejpam-6162	140	35	96337913	96337913	NUM
ejpam-6162	140	36	5.552134	5.552134	NUM
ejpam-6162	140	37	3.59	3.59	NUM
ejpam-6162	140	38	2012	2012	NUM
ejpam-6162	140	39	107.8882	107.8882	NUM
ejpam-6162	140	40	109.9084	109.9084	NUM
ejpam-6162	140	41	40075145	40075145	NUM
ejpam-6162	140	42	98032317	98032317	NUM
ejpam-6162	140	43	6.798970	6.798970	NUM
ejpam-6162	140	44	3.50	3.50	NUM
ejpam-6162	140	45	2013	2013	NUM
ejpam-6162	140	46	110.6746	110.6746	NUM
ejpam-6162	140	47	111.7949	111.7949	NUM
ejpam-6162	140	48	40789298	40789298	NUM
ejpam-6162	140	49	99700107	99700107	NUM
ejpam-6162	140	50	5.819003	5.819003	NUM
ejpam-6162	140	51	3.50	3.50	NUM
ejpam-6162	140	52	2014	2014	NUM
ejpam-6162	140	53	114.6565	114.6565	NUM
ejpam-6162	140	54	115.7143	115.7143	NUM
ejpam-6162	140	55	42179845	42179845	NUM
ejpam-6162	140	56	101325201	101325201	NUM
ejpam-6162	141	1	5.784455	5.784455	NUM
ejpam-6162	141	2	3.60	3.60	NUM
ejpam-6162	141	3	2015	2015	NUM
ejpam-6162	141	4	115.4295	115.4295	NUM
ejpam-6162	141	5	117.6191	117.6191	NUM
ejpam-6162	141	6	42622144	42622144	NUM
ejpam-6162	141	7	103031365	103031365	NUM
ejpam-6162	141	8	6.444572	6.444572	NUM
ejpam-6162	141	9	3.07	3.07	NUM
ejpam-6162	141	10	2016	2016	NUM
ejpam-6162	141	11	116.8766	116.8766	NUM
ejpam-6162	141	12	118.6996	118.6996	NUM
ejpam-6162	141	13	43756699	43756699	NUM
ejpam-6162	141	14	104875266	104875266	NUM
ejpam-6162	141	15	7.149608	7.149608	NUM
ejpam-6162	141	16	2.70	2.70	NUM
ejpam-6162	141	17	2017	2017	NUM
ejpam-6162	141	18	120.2113	120.2113	NUM
ejpam-6162	141	19	120.9341	120.9341	NUM
ejpam-6162	141	20	42974771	42974771	NUM
ejpam-6162	141	21	106738501	106738501	NUM
ejpam-6162	141	22	5.957367	5.957367	NUM
ejpam-6162	141	23	2.55	2.55	NUM
ejpam-6162	141	24	2018	2018	NUM
ejpam-6162	141	25	126.5938	126.5938	NUM
ejpam-6162	141	26	123.2875	123.2875	NUM
ejpam-6162	141	27	43800369	43800369	NUM
ejpam-6162	141	28	108568836	108568836	NUM
ejpam-6162	141	29	5.765216	5.765216	NUM
ejpam-6162	141	30	2.34	2.34	NUM
ejpam-6162	141	31	2019	2019	NUM
ejpam-6162	141	32	129.6220	129.6220	NUM
ejpam-6162	141	33	125.3114	125.3114	NUM
ejpam-6162	141	34	45091808	45091808	NUM
ejpam-6162	141	35	110380804	110380804	NUM
ejpam-6162	141	36	5.866915	5.866915	NUM
ejpam-6162	141	37	2.24	2.24	NUM
ejpam-6162	141	38	2020	2020	NUM
ejpam-6162	141	39	132.7241	132.7241	NUM
ejpam-6162	141	40	128.3150	128.3150	NUM
ejpam-6162	141	41	42419079	42419079	NUM
ejpam-6162	141	42	112190977	112190977	NUM
ejpam-6162	141	43	-7.956529	-7.956529	NOUN
ejpam-6162	141	44	2.52	2.52	NUM
ejpam-6162	141	45	2021	2021	NUM
ejpam-6162	141	46	137.9364	137.9364	NUM
ejpam-6162	141	47	132.2527	132.2527	NUM
ejpam-6162	141	48	44857443	44857443	NUM
ejpam-6162	141	49	113880328	113880328	NUM
ejpam-6162	141	50	4.211487	4.211487	NUM
ejpam-6162	141	51	3.40	3.40	NUM
ejpam-6162	141	52	table	table	NOUN
ejpam-6162	141	53	7	7	NUM
ejpam-6162	141	54	shows	show	VERB
ejpam-6162	141	55	the	the	DET
ejpam-6162	141	56	bivariate	bivariate	ADJ
ejpam-6162	141	57	correlation	correlation	NOUN
ejpam-6162	141	58	coefficients	coefficient	NOUN
ejpam-6162	141	59	r	r	NOUN
ejpam-6162	141	60	of	of	ADP
ejpam-6162	141	61	each	each	DET
ejpam-6162	141	62	independent	independent	ADJ
ejpam-6162	141	63	variable	variable	NOUN
ejpam-6162	141	64	to	to	ADP
ejpam-6162	141	65	the	the	DET
ejpam-6162	141	66	unemployment	unemployment	NOUN
ejpam-6162	141	67	variable	variable	NOUN
ejpam-6162	141	68	and	and	CCONJ
ejpam-6162	141	69	the	the	DET
ejpam-6162	141	70	different	different	ADJ
ejpam-6162	141	71	multiple	multiple	ADJ
ejpam-6162	141	72	ridge	ridge	NOUN
ejpam-6162	141	73	estimators	estimator	NOUN
ejpam-6162	141	74	’	’	PART
ejpam-6162	141	75	coefficients	coefficient	NOUN
ejpam-6162	141	76	.	.	PUNCT
ejpam-6162	142	1	it	it	PRON
ejpam-6162	142	2	can	can	AUX
ejpam-6162	142	3	be	be	AUX
ejpam-6162	142	4	noted	note	VERB
ejpam-6162	142	5	that	that	SCONJ
ejpam-6162	142	6	k6	k6	NOUN
ejpam-6162	142	7	to	to	ADP
ejpam-6162	142	8	k8	k8	PROPN
ejpam-6162	142	9	and	and	CCONJ
ejpam-6162	142	10	the	the	DET
ejpam-6162	142	11	proposed	propose	VERB
ejpam-6162	142	12	k9	k9	PROPN
ejpam-6162	142	13	m	m	PROPN
ejpam-6162	142	14	coefficients	coefficient	NOUN
ejpam-6162	142	15	match	match	VERB
ejpam-6162	142	16	the	the	DET
ejpam-6162	142	17	signs	sign	NOUN
ejpam-6162	142	18	of	of	ADP
ejpam-6162	142	19	the	the	DET
ejpam-6162	142	20	correlation	correlation	NOUN
ejpam-6162	142	21	coefficients	coefficient	NOUN
ejpam-6162	142	22	.	.	PUNCT
ejpam-6162	143	1	on	on	ADP
ejpam-6162	143	2	the	the	DET
ejpam-6162	143	3	other	other	ADJ
ejpam-6162	143	4	hand	hand	NOUN
ejpam-6162	143	5	,	,	PUNCT
ejpam-6162	143	6	the	the	DET
ejpam-6162	143	7	ols	ol	NOUN
ejpam-6162	143	8	and	and	CCONJ
ejpam-6162	143	9	hk	hk	PROPN
ejpam-6162	143	10	estimated	estimate	VERB
ejpam-6162	143	11	coefficients	coefficient	NOUN
ejpam-6162	143	12	do	do	AUX
ejpam-6162	143	13	not	not	PART
ejpam-6162	143	14	match	match	VERB
ejpam-6162	143	15	all	all	DET
ejpam-6162	143	16	the	the	DET
ejpam-6162	143	17	signs	sign	NOUN
ejpam-6162	143	18	of	of	ADP
ejpam-6162	143	19	the	the	DET
ejpam-6162	143	20	correlation	correlation	NOUN
ejpam-6162	143	21	coefficients	coefficient	VERB
ejpam-6162	143	22	an	an	DET
ejpam-6162	143	23	indication	indication	NOUN
ejpam-6162	143	24	of	of	ADP
ejpam-6162	143	25	the	the	DET
ejpam-6162	143	26	presence	presence	NOUN
ejpam-6162	143	27	of	of	ADP
ejpam-6162	143	28	multicollinearity	multicollinearity	NOUN
ejpam-6162	143	29	in	in	ADP
ejpam-6162	143	30	the	the	DET
ejpam-6162	143	31	secondary	secondary	ADJ
ejpam-6162	143	32	data	datum	NOUN
ejpam-6162	143	33	.	.	PUNCT
ejpam-6162	144	1	table	table	NOUN
ejpam-6162	144	2	7	7	NUM
ejpam-6162	144	3	:	:	PUNCT
ejpam-6162	144	4	correlation	correlation	NOUN
ejpam-6162	144	5	coefficients	coefficient	NOUN
ejpam-6162	144	6	r	r	NOUN
ejpam-6162	144	7	and	and	CCONJ
ejpam-6162	144	8	estimated	estimate	VERB
ejpam-6162	144	9	ridge	ridge	NOUN
ejpam-6162	144	10	regression	regression	NOUN
ejpam-6162	144	11	coefficients	coefficient	NOUN
ejpam-6162	144	12	of	of	ADP
ejpam-6162	144	13	estimators	estimator	NOUN
ejpam-6162	144	14	estimators	estimator	NOUN
ejpam-6162	144	15	var	var	AUX
ejpam-6162	144	16	r	r	NOUN
ejpam-6162	144	17	ml	ml	PROPN
ejpam-6162	144	18	hk	hk	PROPN
ejpam-6162	144	19	k2	k2	PROPN
ejpam-6162	144	20	k3	k3	VERB
ejpam-6162	144	21	k4	k4	PROPN
ejpam-6162	144	22	k5	k5	PROPN
ejpam-6162	144	23	k6	k6	PROPN
ejpam-6162	144	24	k7	k7	PROPN
ejpam-6162	144	25	k8	k8	PROPN
ejpam-6162	144	26	k9	k9	PROPN
ejpam-6162	144	27	m	m	PROPN
ejpam-6162	144	28	cpi	cpi	PROPN
ejpam-6162	144	29	-0.63	-0.63	NUM
ejpam-6162	144	30	2.93	2.93	NUM
ejpam-6162	144	31	2.69	2.69	NUM
ejpam-6162	144	32	1.62	1.62	NUM
ejpam-6162	144	33	0.94	0.94	NUM
ejpam-6162	144	34	0.95	0.95	NUM
ejpam-6162	144	35	0.35	0.35	NUM
ejpam-6162	144	36	-0.10	-0.10	NUM
ejpam-6162	144	37	-0.0006	-0.0006	NOUN
ejpam-6162	144	38	-0.08	-0.08	PRON
ejpam-6162	144	39	-0.095	-0.095	NOUN
ejpam-6162	144	40	wpi	wpi	NOUN
ejpam-6162	144	41	-0.63	-0.63	NUM
ejpam-6162	144	42	1.09	1.09	NUM
ejpam-6162	144	43	1.10	1.10	NUM
ejpam-6162	144	44	1.04	1.04	NUM
ejpam-6162	144	45	0.79	0.79	NUM
ejpam-6162	144	46	0.795	0.795	NUM
ejpam-6162	144	47	0.34	0.34	NUM
ejpam-6162	144	48	-0.01	-0.01	NUM
ejpam-6162	144	49	-0.005	-0.005	PRON
ejpam-6162	144	50	-0.08	-0.08	DET
ejpam-6162	144	51	-0.098	-0.098	PUNCT
ejpam-6162	144	52	l	l	NOUN
ejpam-6162	144	53	-0.69	-0.69	NOUN
ejpam-6162	144	54	-0.88	-0.88	NUM
ejpam-6162	144	55	-0.93	-0.93	PROPN
ejpam-6162	144	56	-1.11	-1.11	PRON
ejpam-6162	144	57	-1.06	-1.06	NUM
ejpam-6162	144	58	-1.06	-1.06	NUM
ejpam-6162	144	59	-0.74	-0.74	NOUN
ejpam-6162	144	60	-0.17	-0.17	ADJ
ejpam-6162	144	61	-0.37	-0.37	NUM
ejpam-6162	144	62	-0.24	-0.24	NOUN
ejpam-6162	144	63	-0.195	-0.195	PUNCT
ejpam-6162	144	64	p	p	X
ejpam-6162	144	65	-0.70	-0.70	NUM
ejpam-6162	144	66	-3.79	-3.79	NUM
ejpam-6162	144	67	-3.51	-3.51	NUM
ejpam-6162	144	68	-2.18	-2.18	NUM
ejpam-6162	144	69	-1.31	-1.31	NUM
ejpam-6162	144	70	-1.32	-1.32	NUM
ejpam-6162	144	71	-0.59	-0.59	NUM
ejpam-6162	144	72	-0.15	-0.15	NUM
ejpam-6162	144	73	-0.27	-0.27	PROPN
ejpam-6162	144	74	-0.19	-0.19	PROPN
ejpam-6162	144	75	-0.167	-0.167	PROPN
ejpam-6162	144	76	h	h	NOUN
ejpam-6162	144	77	0.22	0.22	NUM
ejpam-6162	144	78	0.28	0.28	NUM
ejpam-6162	144	79	0.30	0.30	NUM
ejpam-6162	144	80	0.38	0.38	NUM
ejpam-6162	144	81	0.36	0.36	NUM
ejpam-6162	144	82	0.36	0.36	NUM
ejpam-6162	144	83	0.24	0.24	NUM
ejpam-6162	144	84	0.04	0.04	NUM
ejpam-6162	144	85	0.10	0.10	NUM
ejpam-6162	144	86	0.059	0.059	NUM
ejpam-6162	144	87	0.047	0.047	NUM
ejpam-6162	144	88	4	4	NUM
ejpam-6162	144	89	.	.	PUNCT
ejpam-6162	145	1	conclusion	conclusion	VERB
ejpam-6162	145	2	the	the	DET
ejpam-6162	145	3	method	method	NOUN
ejpam-6162	145	4	of	of	ADP
ejpam-6162	145	5	ridge	ridge	NOUN
ejpam-6162	145	6	regression	regression	NOUN
ejpam-6162	145	7	is	be	AUX
ejpam-6162	145	8	useful	useful	ADJ
ejpam-6162	145	9	in	in	ADP
ejpam-6162	145	10	reducing	reduce	VERB
ejpam-6162	145	11	the	the	DET
ejpam-6162	145	12	negative	negative	ADJ
ejpam-6162	145	13	effects	effect	NOUN
ejpam-6162	145	14	of	of	ADP
ejpam-6162	145	15	multicollinearity	multicollinearity	NOUN
ejpam-6162	145	16	by	by	ADP
ejpam-6162	145	17	using	use	VERB
ejpam-6162	145	18	a	a	DET
ejpam-6162	145	19	small	small	ADJ
ejpam-6162	145	20	bias	bias	NOUN
ejpam-6162	145	21	in	in	ADP
ejpam-6162	145	22	the	the	DET
ejpam-6162	145	23	form	form	NOUN
ejpam-6162	145	24	of	of	ADP
ejpam-6162	145	25	a	a	DET
ejpam-6162	145	26	ridge	ridge	NOUN
ejpam-6162	145	27	parameter	parameter	PROPN
ejpam-6162	145	28	k.	k.	PROPN
ejpam-6162	146	1	there	there	PRON
ejpam-6162	146	2	have	have	AUX
ejpam-6162	146	3	been	be	AUX
ejpam-6162	146	4	many	many	ADJ
ejpam-6162	146	5	proposed	propose	VERB
ejpam-6162	146	6	ridge	ridge	NOUN
ejpam-6162	146	7	parameter	parameter	PROPN
ejpam-6162	146	8	,	,	PUNCT
ejpam-6162	146	9	the	the	DET
ejpam-6162	146	10	best	good	ADJ
ejpam-6162	146	11	ridge	ridge	NOUN
ejpam-6162	146	12	parameter	parameter	NOUN
ejpam-6162	146	13	has	have	AUX
ejpam-6162	146	14	yet	yet	ADV
ejpam-6162	146	15	been	be	AUX
ejpam-6162	146	16	determined	determine	VERB
ejpam-6162	146	17	and	and	CCONJ
ejpam-6162	146	18	no	no	DET
ejpam-6162	146	19	constant	constant	ADJ
ejpam-6162	146	20	value	value	NOUN
ejpam-6162	146	21	of	of	ADP
ejpam-6162	146	22	k	k	PROPN
ejpam-6162	146	23	is	be	AUX
ejpam-6162	146	24	certain	certain	ADJ
ejpam-6162	146	25	to	to	PART
ejpam-6162	146	26	give	give	VERB
ejpam-6162	146	27	an	an	DET
ejpam-6162	146	28	estimator	estimator	NOUN
ejpam-6162	146	29	that	that	PRON
ejpam-6162	146	30	is	be	AUX
ejpam-6162	146	31	consistently	consistently	ADV
ejpam-6162	146	32	better	well	ADJ
ejpam-6162	146	33	in	in	ADP
ejpam-6162	146	34	terms	term	NOUN
ejpam-6162	146	35	of	of	ADP
ejpam-6162	146	36	mse	mse	NOUN
ejpam-6162	146	37	than	than	ADP
ejpam-6162	146	38	the	the	DET
ejpam-6162	146	39	ml	ml	NOUN
ejpam-6162	146	40	or	or	CCONJ
ejpam-6162	146	41	ols	ol	NOUN
ejpam-6162	146	42	.	.	PUNCT
ejpam-6162	147	1	j.	j.	PROPN
ejpam-6162	147	2	mohamad	mohamad	PROPN
ejpam-6162	147	3	,	,	PUNCT
ejpam-6162	147	4	et	et	PROPN
ejpam-6162	147	5	.	.	PUNCT
ejpam-6162	148	1	al	al	PROPN
ejpam-6162	148	2	.	.	PUNCT
ejpam-6162	148	3	/	/	SYM
ejpam-6162	148	4	eur	eur	PROPN
ejpam-6162	148	5	.	.	PUNCT
ejpam-6162	149	1	j.	j.	PROPN
ejpam-6162	149	2	pure	pure	PROPN
ejpam-6162	149	3	appl	appl	PROPN
ejpam-6162	149	4	.	.	PROPN
ejpam-6162	149	5	math	math	PROPN
ejpam-6162	149	6	,	,	PUNCT
ejpam-6162	149	7	18	18	NUM
ejpam-6162	149	8	(	(	PUNCT
ejpam-6162	149	9	2	2	NUM
ejpam-6162	149	10	)	)	PUNCT
ejpam-6162	149	11	(	(	PUNCT
ejpam-6162	149	12	2025	2025	NUM
ejpam-6162	149	13	)	)	PUNCT
ejpam-6162	149	14	,	,	PUNCT
ejpam-6162	149	15	6162	6162	NUM
ejpam-6162	149	16	9	9	NUM
ejpam-6162	149	17	of	of	ADP
ejpam-6162	149	18	10	10	NUM
ejpam-6162	149	19	in	in	ADP
ejpam-6162	149	20	this	this	DET
ejpam-6162	149	21	study	study	NOUN
ejpam-6162	149	22	,	,	PUNCT
ejpam-6162	149	23	we	we	PRON
ejpam-6162	149	24	used	use	VERB
ejpam-6162	149	25	monte	monte	PROPN
ejpam-6162	149	26	carlo	carlo	PROPN
ejpam-6162	149	27	simulation	simulation	NOUN
ejpam-6162	149	28	with	with	ADP
ejpam-6162	149	29	1,000	1,000	NUM
ejpam-6162	149	30	replications	replication	NOUN
ejpam-6162	149	31	in	in	ADP
ejpam-6162	149	32	the	the	DET
ejpam-6162	149	33	r	r	NOUN
ejpam-6162	149	34	software	software	NOUN
ejpam-6162	149	35	.	.	PUNCT
ejpam-6162	150	1	in	in	ADP
ejpam-6162	150	2	all	all	DET
ejpam-6162	150	3	the	the	DET
ejpam-6162	150	4	simulation	simulation	NOUN
ejpam-6162	150	5	combinations	combination	NOUN
ejpam-6162	150	6	considered	consider	VERB
ejpam-6162	150	7	,	,	PUNCT
ejpam-6162	150	8	where	where	SCONJ
ejpam-6162	150	9	the	the	DET
ejpam-6162	150	10	number	number	NOUN
ejpam-6162	150	11	of	of	ADP
ejpam-6162	150	12	independent	independent	ADJ
ejpam-6162	150	13	variables	variable	NOUN
ejpam-6162	150	14	p	p	NOUN
ejpam-6162	150	15	,	,	PUNCT
ejpam-6162	150	16	level	level	NOUN
ejpam-6162	150	17	of	of	ADP
ejpam-6162	150	18	correlation	correlation	NOUN
ejpam-6162	150	19	ρ	ρ	NOUN
ejpam-6162	150	20	,	,	PUNCT
ejpam-6162	150	21	intercept	intercept	NOUN
ejpam-6162	150	22	β0	β0	NOUN
ejpam-6162	150	23	,	,	PUNCT
ejpam-6162	150	24	and	and	CCONJ
ejpam-6162	150	25	sample	sample	NOUN
ejpam-6162	150	26	sizes	size	NOUN
ejpam-6162	150	27	n	n	PRON
ejpam-6162	150	28	are	be	AUX
ejpam-6162	150	29	varied	varied	ADJ
ejpam-6162	150	30	,	,	PUNCT
ejpam-6162	150	31	the	the	DET
ejpam-6162	150	32	simulation	simulation	NOUN
ejpam-6162	150	33	results	result	NOUN
ejpam-6162	150	34	showed	show	VERB
ejpam-6162	150	35	that	that	SCONJ
ejpam-6162	150	36	overall	overall	ADJ
ejpam-6162	150	37	the	the	DET
ejpam-6162	150	38	known	know	VERB
ejpam-6162	150	39	and	and	CCONJ
ejpam-6162	150	40	proposed	propose	VERB
ejpam-6162	150	41	ridge	ridge	NOUN
ejpam-6162	150	42	parameter	parameter	NOUN
ejpam-6162	150	43	estimators	estimator	NOUN
ejpam-6162	150	44	has	have	VERB
ejpam-6162	150	45	lower	low	ADJ
ejpam-6162	150	46	mse	mse	NOUN
ejpam-6162	150	47	than	than	ADP
ejpam-6162	150	48	that	that	PRON
ejpam-6162	150	49	of	of	ADP
ejpam-6162	150	50	the	the	DET
ejpam-6162	150	51	ols	ol	NOUN
ejpam-6162	150	52	,	,	PUNCT
ejpam-6162	150	53	ml	ml	ADP
ejpam-6162	150	54	,	,	PUNCT
ejpam-6162	150	55	and	and	CCONJ
ejpam-6162	150	56	hk	hk	NOUN
ejpam-6162	150	57	estimators	estimator	NOUN
ejpam-6162	150	58	.	.	PUNCT
ejpam-6162	151	1	furthermore	furthermore	ADV
ejpam-6162	151	2	,	,	PUNCT
ejpam-6162	151	3	the	the	DET
ejpam-6162	151	4	proposed	propose	VERB
ejpam-6162	151	5	estimators	estimator	NOUN
ejpam-6162	151	6	performed	perform	VERB
ejpam-6162	151	7	best	well	ADV
ejpam-6162	151	8	on	on	ADP
ejpam-6162	151	9	some	some	DET
ejpam-6162	151	10	cases	case	NOUN
ejpam-6162	151	11	.	.	PUNCT
ejpam-6162	152	1	finally	finally	ADV
ejpam-6162	152	2	,	,	PUNCT
ejpam-6162	152	3	the	the	DET
ejpam-6162	152	4	methods	method	NOUN
ejpam-6162	152	5	of	of	ADP
ejpam-6162	152	6	the	the	DET
ejpam-6162	152	7	known	know	VERB
ejpam-6162	152	8	and	and	CCONJ
ejpam-6162	152	9	proposed	propose	VERB
ejpam-6162	152	10	estimators	estimator	NOUN
ejpam-6162	152	11	were	be	AUX
ejpam-6162	152	12	applied	apply	VERB
ejpam-6162	152	13	to	to	ADP
ejpam-6162	152	14	multicollinear	multicollinear	ADJ
ejpam-6162	152	15	data	datum	NOUN
ejpam-6162	152	16	from	from	ADP
ejpam-6162	152	17	secondary	secondary	ADJ
ejpam-6162	152	18	sources	source	NOUN
ejpam-6162	152	19	and	and	CCONJ
ejpam-6162	152	20	found	find	VERB
ejpam-6162	152	21	that	that	SCONJ
ejpam-6162	152	22	the	the	DET
ejpam-6162	152	23	proposed	propose	VERB
ejpam-6162	152	24	estimators	estimator	NOUN
ejpam-6162	152	25	’	’	PART
ejpam-6162	152	26	coefficients	coefficient	NOUN
ejpam-6162	152	27	match	match	VERB
ejpam-6162	152	28	the	the	DET
ejpam-6162	152	29	signs	sign	NOUN
ejpam-6162	152	30	of	of	ADP
ejpam-6162	152	31	the	the	DET
ejpam-6162	152	32	corresponding	corresponding	ADJ
ejpam-6162	152	33	correlation	correlation	NOUN
ejpam-6162	152	34	coefficient	coefficient	NOUN
ejpam-6162	152	35	.	.	PUNCT
ejpam-6162	153	1	acknowledgements	acknowledgement	NOUN
ejpam-6162	153	2	this	this	DET
ejpam-6162	153	3	research	research	NOUN
ejpam-6162	153	4	is	be	AUX
ejpam-6162	153	5	funded	fund	VERB
ejpam-6162	153	6	by	by	ADP
ejpam-6162	153	7	the	the	DET
ejpam-6162	153	8	higher	high	ADJ
ejpam-6162	153	9	innovations	innovation	NOUN
ejpam-6162	153	10	fund	fund	NOUN
ejpam-6162	153	11	of	of	ADP
ejpam-6162	153	12	the	the	DET
ejpam-6162	153	13	western	western	ADJ
ejpam-6162	153	14	mindanao	mindanao	PROPN
ejpam-6162	153	15	state	state	PROPN
ejpam-6162	153	16	university	university	PROPN
ejpam-6162	153	17	,	,	PUNCT
ejpam-6162	153	18	zamboanga	zamboanga	PROPN
ejpam-6162	153	19	city	city	PROPN
ejpam-6162	153	20	,	,	PUNCT
ejpam-6162	153	21	philippines	philippine	NOUN
ejpam-6162	153	22	.	.	PUNCT
ejpam-6162	154	1	references	reference	NOUN
ejpam-6162	154	2	[	[	X
ejpam-6162	154	3	1	1	NUM
ejpam-6162	154	4	]	]	X
ejpam-6162	154	5	a.e	a.e	PROPN
ejpam-6162	154	6	.	.	PROPN
ejpam-6162	154	7	hoerl	hoerl	PROPN
ejpam-6162	154	8	and	and	CCONJ
ejpam-6162	154	9	r.w	r.w	PROPN
ejpam-6162	154	10	.	.	PROPN
ejpam-6162	154	11	kennard	kennard	PROPN
ejpam-6162	154	12	.	.	PUNCT
ejpam-6162	155	1	ridge	ridge	PROPN
ejpam-6162	155	2	regression	regression	PROPN
ejpam-6162	155	3	:	:	PUNCT
ejpam-6162	155	4	biased	biased	ADJ
ejpam-6162	155	5	estimation	estimation	NOUN
ejpam-6162	155	6	for	for	ADP
ejpam-6162	155	7	nonorthogonal	nonorthogonal	ADJ
ejpam-6162	155	8	problems	problem	NOUN
ejpam-6162	155	9	.	.	PUNCT
ejpam-6162	156	1	technometrics	technometric	NOUN
ejpam-6162	156	2	,	,	PUNCT
ejpam-6162	156	3	12:55–67	12:55–67	NUM
ejpam-6162	156	4	,	,	PUNCT
ejpam-6162	156	5	1970	1970	NUM
ejpam-6162	156	6	.	.	PUNCT
ejpam-6162	157	1	[	[	X
ejpam-6162	157	2	2	2	NUM
ejpam-6162	157	3	]	]	X
ejpam-6162	157	4	a.e	a.e	PROPN
ejpam-6162	157	5	.	.	PROPN
ejpam-6162	157	6	hoerl	hoerl	PROPN
ejpam-6162	157	7	and	and	CCONJ
ejpam-6162	157	8	r.w	r.w	PROPN
ejpam-6162	157	9	.	.	PROPN
ejpam-6162	157	10	kennard	kennard	PROPN
ejpam-6162	157	11	.	.	PUNCT
ejpam-6162	158	1	ridge	ridge	PROPN
ejpam-6162	158	2	regression	regression	PROPN
ejpam-6162	158	3	:	:	PUNCT
ejpam-6162	158	4	application	application	NOUN
ejpam-6162	158	5	to	to	ADP
ejpam-6162	158	6	non	non	ADJ
ejpam-6162	158	7	-	-	ADJ
ejpam-6162	158	8	orthogonal	orthogonal	ADJ
ejpam-6162	158	9	problems	problem	NOUN
ejpam-6162	158	10	.	.	PUNCT
ejpam-6162	159	1	technometrics	technometric	NOUN
ejpam-6162	159	2	,	,	PUNCT
ejpam-6162	159	3	12:69–82	12:69–82	NUM
ejpam-6162	159	4	,	,	PUNCT
ejpam-6162	159	5	1970	1970	NUM
ejpam-6162	159	6	.	.	PUNCT
ejpam-6162	160	1	[	[	X
ejpam-6162	160	2	3	3	X
ejpam-6162	160	3	]	]	PUNCT
ejpam-6162	160	4	k.	k.	PROPN
ejpam-6162	160	5	månsson	månsson	PROPN
ejpam-6162	160	6	and	and	CCONJ
ejpam-6162	160	7	g.	g.	PROPN
ejpam-6162	160	8	shukur	shukur	PROPN
ejpam-6162	160	9	.	.	PUNCT
ejpam-6162	161	1	on	on	ADP
ejpam-6162	161	2	ridge	ridge	NOUN
ejpam-6162	161	3	parameters	parameter	NOUN
ejpam-6162	161	4	in	in	ADP
ejpam-6162	161	5	logistic	logistic	ADJ
ejpam-6162	161	6	regression	regression	NOUN
ejpam-6162	161	7	.	.	PUNCT
ejpam-6162	162	1	communications	communication	NOUN
ejpam-6162	162	2	in	in	ADP
ejpam-6162	162	3	statistics	statistic	NOUN
ejpam-6162	162	4	—	—	PUNCT
ejpam-6162	162	5	theory	theory	NOUN
ejpam-6162	162	6	and	and	CCONJ
ejpam-6162	162	7	methods	method	NOUN
ejpam-6162	162	8	,	,	PUNCT
ejpam-6162	162	9	40:3366–3381	40:3366–3381	NUM
ejpam-6162	162	10	,	,	PUNCT
ejpam-6162	162	11	2011	2011	NUM
ejpam-6162	162	12	.	.	PUNCT
ejpam-6162	163	1	[	[	X
ejpam-6162	163	2	4	4	X
ejpam-6162	163	3	]	]	PUNCT
ejpam-6162	163	4	k.	k.	PROPN
ejpam-6162	163	5	månsson	månsson	PROPN
ejpam-6162	163	6	and	and	CCONJ
ejpam-6162	163	7	g.	g.	PROPN
ejpam-6162	163	8	shukur	shukur	PROPN
ejpam-6162	163	9	.	.	PUNCT
ejpam-6162	164	1	a	a	DET
ejpam-6162	164	2	poisson	poisson	PROPN
ejpam-6162	164	3	ridge	ridge	PROPN
ejpam-6162	164	4	regression	regression	PROPN
ejpam-6162	164	5	estimator	estimator	NOUN
ejpam-6162	164	6	.	.	PUNCT
ejpam-6162	165	1	economic	economic	ADJ
ejpam-6162	165	2	modelling	modelling	NOUN
ejpam-6162	165	3	,	,	PUNCT
ejpam-6162	165	4	28(4):1475–1481	28(4):1475–1481	NUM
ejpam-6162	165	5	,	,	PUNCT
ejpam-6162	165	6	2011	2011	NUM
ejpam-6162	165	7	.	.	PUNCT
ejpam-6162	166	1	[	[	X
ejpam-6162	166	2	5	5	NUM
ejpam-6162	166	3	]	]	PUNCT
ejpam-6162	166	4	a.	a.	NOUN
ejpam-6162	166	5	göktaş	göktaş	NOUN
ejpam-6162	166	6	,	,	PUNCT
ejpam-6162	166	7	ö.	ö.	PROPN
ejpam-6162	166	8	akkuş	akkuş	NOUN
ejpam-6162	166	9	,	,	PUNCT
ejpam-6162	166	10	and	and	CCONJ
ejpam-6162	166	11	a.	a.	NOUN
ejpam-6162	166	12	kuvat	kuvat	PROPN
ejpam-6162	166	13	.	.	PUNCT
ejpam-6162	167	1	a	a	DET
ejpam-6162	167	2	new	new	ADJ
ejpam-6162	167	3	robust	robust	ADJ
ejpam-6162	167	4	ridge	ridge	NOUN
ejpam-6162	167	5	parameter	parameter	PROPN
ejpam-6162	167	6	estimator	estimator	NOUN
ejpam-6162	167	7	based	base	VERB
ejpam-6162	167	8	on	on	ADP
ejpam-6162	167	9	search	search	NOUN
ejpam-6162	167	10	method	method	NOUN
ejpam-6162	167	11	for	for	ADP
ejpam-6162	167	12	linear	linear	PROPN
ejpam-6162	167	13	regression	regression	NOUN
ejpam-6162	167	14	model	model	NOUN
ejpam-6162	167	15	.	.	PUNCT
ejpam-6162	168	1	journal	journal	PROPN
ejpam-6162	168	2	of	of	ADP
ejpam-6162	168	3	applied	apply	VERB
ejpam-6162	168	4	statistics	statistic	NOUN
ejpam-6162	168	5	,	,	PUNCT
ejpam-6162	168	6	48(1315):2457–2472	48(1315):2457–2472	NUM
ejpam-6162	168	7	,	,	PUNCT
ejpam-6162	168	8	2020	2020	NUM
ejpam-6162	168	9	.	.	PUNCT
ejpam-6162	169	1	[	[	X
ejpam-6162	169	2	6	6	NUM
ejpam-6162	169	3	]	]	PUNCT
ejpam-6162	169	4	o.	o.	NOUN
ejpam-6162	169	5	akbilgic	akbilgic	PROPN
ejpam-6162	169	6	and	and	CCONJ
ejpam-6162	169	7	h.	h.	PROPN
ejpam-6162	169	8	bozdogan	bozdogan	PROPN
ejpam-6162	169	9	.	.	PUNCT
ejpam-6162	170	1	predictive	predictive	ADJ
ejpam-6162	170	2	subset	subset	NOUN
ejpam-6162	170	3	selection	selection	NOUN
ejpam-6162	170	4	using	use	VERB
ejpam-6162	170	5	regression	regression	NOUN
ejpam-6162	170	6	trees	tree	NOUN
ejpam-6162	170	7	and	and	CCONJ
ejpam-6162	170	8	rbf	rbf	PROPN
ejpam-6162	170	9	neural	neural	PROPN
ejpam-6162	170	10	networks	network	NOUN
ejpam-6162	170	11	hybridized	hybridize	VERB
ejpam-6162	170	12	with	with	ADP
ejpam-6162	170	13	the	the	DET
ejpam-6162	170	14	genetic	genetic	ADJ
ejpam-6162	170	15	algorithm	algorithm	NOUN
ejpam-6162	170	16	.	.	PUNCT
ejpam-6162	171	1	european	european	ADJ
ejpam-6162	171	2	journal	journal	PROPN
ejpam-6162	171	3	of	of	ADP
ejpam-6162	171	4	pure	pure	ADJ
ejpam-6162	171	5	and	and	CCONJ
ejpam-6162	171	6	applied	applied	ADJ
ejpam-6162	171	7	mathematics	mathematic	NOUN
ejpam-6162	171	8	,	,	PUNCT
ejpam-6162	171	9	4(4):467–485	4(4):467–485	NOUN
ejpam-6162	171	10	,	,	PUNCT
ejpam-6162	171	11	2011	2011	NUM
ejpam-6162	171	12	.	.	PUNCT
ejpam-6162	172	1	[	[	X
ejpam-6162	172	2	7	7	X
ejpam-6162	172	3	]	]	X
ejpam-6162	172	4	s.	s.	PROPN
ejpam-6162	172	5	mermi	mermi	PROPN
ejpam-6162	172	6	,	,	PUNCT
ejpam-6162	172	7	ö.	ö.	PROPN
ejpam-6162	172	8	akkuş	akkuş	NOUN
ejpam-6162	172	9	,	,	PUNCT
ejpam-6162	172	10	and	and	CCONJ
ejpam-6162	172	11	a.	a.	NOUN
ejpam-6162	172	12	göktaş.	göktaş.	PROPN
ejpam-6162	172	13	how	how	SCONJ
ejpam-6162	172	14	well	well	ADV
ejpam-6162	172	15	do	do	AUX
ejpam-6162	172	16	ridge	ridge	NOUN
ejpam-6162	172	17	parameter	parameter	NOUN
ejpam-6162	172	18	estimators	estimator	NOUN
ejpam-6162	172	19	proposed	propose	VERB
ejpam-6162	172	20	so	so	ADV
ejpam-6162	172	21	far	far	ADV
ejpam-6162	172	22	perform	perform	VERB
ejpam-6162	172	23	in	in	ADP
ejpam-6162	172	24	terms	term	NOUN
ejpam-6162	172	25	of	of	ADP
ejpam-6162	172	26	normality	normality	NOUN
ejpam-6162	172	27	,	,	PUNCT
ejpam-6162	172	28	outlier	outlier	NOUN
ejpam-6162	172	29	detection	detection	NOUN
ejpam-6162	172	30	,	,	PUNCT
ejpam-6162	172	31	and	and	CCONJ
ejpam-6162	172	32	mse	mse	NOUN
ejpam-6162	172	33	criteria	criterion	NOUN
ejpam-6162	172	34	?	?	PUNCT
ejpam-6162	173	1	communications	communication	NOUN
ejpam-6162	173	2	in	in	ADP
ejpam-6162	173	3	statistics	statistic	NOUN
ejpam-6162	173	4	simulation	simulation	NOUN
ejpam-6162	173	5	and	and	CCONJ
ejpam-6162	173	6	computation	computation	NOUN
ejpam-6162	173	7	,	,	PUNCT
ejpam-6162	173	8	53(1):1–67	53(1):1–67	NUM
ejpam-6162	173	9	,	,	PUNCT
ejpam-6162	173	10	2024	2024	NUM
ejpam-6162	173	11	.	.	PUNCT
ejpam-6162	174	1	[	[	X
ejpam-6162	174	2	8	8	NUM
ejpam-6162	174	3	]	]	X
ejpam-6162	174	4	s.	s.	PROPN
ejpam-6162	174	5	mermi	mermi	PROPN
ejpam-6162	174	6	,	,	PUNCT
ejpam-6162	174	7	ö.	ö.	PROPN
ejpam-6162	174	8	akkuş	akkuş	PROPN
ejpam-6162	174	9	,	,	PUNCT
ejpam-6162	174	10	a.	a.	NOUN
ejpam-6162	174	11	göktaş	göktaş	NOUN
ejpam-6162	174	12	,	,	PUNCT
ejpam-6162	174	13	and	and	CCONJ
ejpam-6162	174	14	n.	n.	PROPN
ejpam-6162	174	15	gündüz	gündüz	PROPN
ejpam-6162	174	16	.	.	PUNCT
ejpam-6162	175	1	a	a	DET
ejpam-6162	175	2	new	new	ADJ
ejpam-6162	175	3	robust	robust	ADJ
ejpam-6162	175	4	ridge	ridge	NOUN
ejpam-6162	175	5	parameter	parameter	PROPN
ejpam-6162	175	6	estimator	estimator	NOUN
ejpam-6162	175	7	having	have	VERB
ejpam-6162	175	8	no	no	DET
ejpam-6162	175	9	outlier	outlier	NOUN
ejpam-6162	175	10	and	and	CCONJ
ejpam-6162	175	11	ensuring	ensure	VERB
ejpam-6162	175	12	normality	normality	NOUN
ejpam-6162	175	13	for	for	ADP
ejpam-6162	175	14	linear	linear	PROPN
ejpam-6162	175	15	regression	regression	NOUN
ejpam-6162	175	16	model	model	NOUN
ejpam-6162	175	17	.	.	PUNCT
ejpam-6162	176	1	journal	journal	PROPN
ejpam-6162	176	2	of	of	ADP
ejpam-6162	176	3	radiation	radiation	NOUN
ejpam-6162	176	4	research	research	NOUN
ejpam-6162	176	5	and	and	CCONJ
ejpam-6162	176	6	applied	apply	VERB
ejpam-6162	176	7	sciences	science	NOUN
ejpam-6162	176	8	,	,	PUNCT
ejpam-6162	176	9	17(1):100788	17(1):100788	NUM
ejpam-6162	176	10	,	,	PUNCT
ejpam-6162	176	11	2024	2024	NUM
ejpam-6162	176	12	.	.	PUNCT
ejpam-6162	177	1	[	[	X
ejpam-6162	177	2	9	9	NUM
ejpam-6162	177	3	]	]	X
ejpam-6162	177	4	b.m.g	b.m.g	ADJ
ejpam-6162	177	5	.	.	PUNCT
ejpam-6162	177	6	kibria	kibria	PROPN
ejpam-6162	177	7	.	.	PUNCT
ejpam-6162	178	1	performance	performance	NOUN
ejpam-6162	178	2	of	of	ADP
ejpam-6162	178	3	some	some	DET
ejpam-6162	178	4	new	new	PROPN
ejpam-6162	178	5	ridge	ridge	NOUN
ejpam-6162	178	6	regression	regression	NOUN
ejpam-6162	178	7	estimators	estimator	NOUN
ejpam-6162	178	8	.	.	PUNCT
ejpam-6162	179	1	communications	communication	NOUN
ejpam-6162	179	2	in	in	ADP
ejpam-6162	179	3	statistics	statistic	NOUN
ejpam-6162	179	4	—	—	PUNCT
ejpam-6162	179	5	theory	theory	NOUN
ejpam-6162	179	6	and	and	CCONJ
ejpam-6162	179	7	methods	method	NOUN
ejpam-6162	179	8	,	,	PUNCT
ejpam-6162	179	9	32:419–435	32:419–435	NUM
ejpam-6162	179	10	,	,	PUNCT
ejpam-6162	179	11	2003	2003	NUM
ejpam-6162	179	12	.	.	PUNCT
ejpam-6162	180	1	[	[	X
ejpam-6162	180	2	10	10	NUM
ejpam-6162	180	3	]	]	X
ejpam-6162	180	4	m.a	m.a	PROPN
ejpam-6162	180	5	.	.	PROPN
ejpam-6162	180	6	alkhamisi	alkhamisi	PROPN
ejpam-6162	180	7	,	,	PUNCT
ejpam-6162	180	8	g.	g.	PROPN
ejpam-6162	180	9	khalaf	khalaf	PROPN
ejpam-6162	180	10	,	,	PUNCT
ejpam-6162	180	11	and	and	CCONJ
ejpam-6162	180	12	g.	g.	PROPN
ejpam-6162	180	13	shukur	shukur	PROPN
ejpam-6162	180	14	.	.	PUNCT
ejpam-6162	181	1	some	some	DET
ejpam-6162	181	2	modifications	modification	NOUN
ejpam-6162	181	3	for	for	ADP
ejpam-6162	181	4	choosing	choose	VERB
ejpam-6162	181	5	ridge	ridge	NOUN
ejpam-6162	181	6	parameter	parameter	NOUN
ejpam-6162	181	7	.	.	PUNCT
ejpam-6162	182	1	communications	communication	NOUN
ejpam-6162	182	2	in	in	ADP
ejpam-6162	182	3	statistics	statistic	NOUN
ejpam-6162	182	4	—	—	PUNCT
ejpam-6162	182	5	theory	theory	NOUN
ejpam-6162	182	6	and	and	CCONJ
ejpam-6162	182	7	methods	method	NOUN
ejpam-6162	182	8	,	,	PUNCT
ejpam-6162	182	9	35:1–16	35:1–16	NUM
ejpam-6162	182	10	,	,	PUNCT
ejpam-6162	182	11	2006	2006	NUM
ejpam-6162	182	12	.	.	PUNCT
ejpam-6162	183	1	[	[	X
ejpam-6162	183	2	11	11	NUM
ejpam-6162	183	3	]	]	X
ejpam-6162	183	4	g.	g.	PROPN
ejpam-6162	183	5	muniz	muniz	PROPN
ejpam-6162	183	6	and	and	CCONJ
ejpam-6162	183	7	b.m.g	b.m.g	ADJ
ejpam-6162	183	8	.	.	PUNCT
ejpam-6162	184	1	kibria	kibria	PROPN
ejpam-6162	184	2	.	.	PUNCT
ejpam-6162	185	1	on	on	ADP
ejpam-6162	185	2	some	some	DET
ejpam-6162	185	3	ridge	ridge	NOUN
ejpam-6162	185	4	regression	regression	NOUN
ejpam-6162	185	5	estimators	estimator	NOUN
ejpam-6162	185	6	:	:	PUNCT
ejpam-6162	185	7	an	an	DET
ejpam-6162	185	8	empirical	empirical	ADJ
ejpam-6162	185	9	comparison	comparison	NOUN
ejpam-6162	185	10	.	.	PUNCT
ejpam-6162	186	1	communications	communication	NOUN
ejpam-6162	186	2	in	in	ADP
ejpam-6162	186	3	statistics	statistic	NOUN
ejpam-6162	186	4	—	—	PUNCT
ejpam-6162	186	5	simulation	simulation	NOUN
ejpam-6162	186	6	and	and	CCONJ
ejpam-6162	186	7	computation	computation	NOUN
ejpam-6162	186	8	,	,	PUNCT
ejpam-6162	186	9	38:621–630	38:621–630	PROPN
ejpam-6162	186	10	,	,	PUNCT
ejpam-6162	186	11	2009	2009	NUM
ejpam-6162	186	12	.	.	PUNCT
ejpam-6162	187	1	j.	j.	PROPN
ejpam-6162	187	2	mohamad	mohamad	PROPN
ejpam-6162	187	3	,	,	PUNCT
ejpam-6162	187	4	et	et	PROPN
ejpam-6162	187	5	.	.	PUNCT
ejpam-6162	188	1	al	al	PROPN
ejpam-6162	188	2	.	.	PUNCT
ejpam-6162	188	3	/	/	SYM
ejpam-6162	188	4	eur	eur	PROPN
ejpam-6162	188	5	.	.	PUNCT
ejpam-6162	189	1	j.	j.	PROPN
ejpam-6162	189	2	pure	pure	PROPN
ejpam-6162	189	3	appl	appl	PROPN
ejpam-6162	189	4	.	.	PROPN
ejpam-6162	189	5	math	math	PROPN
ejpam-6162	189	6	,	,	PUNCT
ejpam-6162	189	7	18	18	NUM
ejpam-6162	189	8	(	(	PUNCT
ejpam-6162	189	9	2	2	NUM
ejpam-6162	189	10	)	)	PUNCT
ejpam-6162	189	11	(	(	PUNCT
ejpam-6162	189	12	2025	2025	NUM
ejpam-6162	189	13	)	)	PUNCT
ejpam-6162	189	14	,	,	PUNCT
ejpam-6162	189	15	6162	6162	NUM
ejpam-6162	189	16	10	10	NUM
ejpam-6162	189	17	of	of	ADP
ejpam-6162	189	18	10	10	NUM
ejpam-6162	189	19	[	[	X
ejpam-6162	189	20	12	12	NUM
ejpam-6162	189	21	]	]	X
ejpam-6162	189	22	g.c	g.c	PROPN
ejpam-6162	189	23	.	.	PROPN
ejpam-6162	189	24	mcdonald	mcdonald	PROPN
ejpam-6162	189	25	and	and	CCONJ
ejpam-6162	189	26	d.i	d.i	PROPN
ejpam-6162	189	27	.	.	PROPN
ejpam-6162	189	28	galarneau	galarneau	PROPN
ejpam-6162	189	29	.	.	PUNCT
ejpam-6162	190	1	a	a	DET
ejpam-6162	190	2	monte	monte	PROPN
ejpam-6162	190	3	carlo	carlo	NOUN
ejpam-6162	190	4	evaluation	evaluation	NOUN
ejpam-6162	190	5	of	of	ADP
ejpam-6162	190	6	some	some	DET
ejpam-6162	190	7	ridge	ridge	NOUN
ejpam-6162	190	8	-	-	PUNCT
ejpam-6162	190	9	type	type	NOUN
ejpam-6162	190	10	estimators	estimator	NOUN
ejpam-6162	190	11	.	.	PUNCT
ejpam-6162	191	1	journal	journal	NOUN
ejpam-6162	191	2	of	of	ADP
ejpam-6162	191	3	the	the	DET
ejpam-6162	191	4	american	american	PROPN
ejpam-6162	191	5	statistical	statistical	PROPN
ejpam-6162	191	6	association	association	PROPN
ejpam-6162	191	7	,	,	PUNCT
ejpam-6162	191	8	70(350):407–416	70(350):407–416	PROPN
ejpam-6162	191	9	,	,	PUNCT
ejpam-6162	191	10	1975	1975	NUM
ejpam-6162	191	11	.	.	PUNCT