id	sid	tid	token	lemma	pos
cuesj-483	1	1	tx_1	tx_1	PROPN
cuesj-483	1	2	~	~	X
cuesj-483	1	3	abs	ab	NOUN
cuesj-483	1	4	:	:	PUNCT
cuesj-483	1	5	at	at	ADP
cuesj-483	1	6	/	/	SYM
cuesj-483	1	7	add	add	VERB
cuesj-483	1	8	:	:	PUNCT
cuesj-483	1	9	tx_2	tx_2	PROPN
cuesj-483	1	10	~	~	NOUN
cuesj-483	1	11	abs	ab	NOUN
cuesj-483	1	12	:	:	PUNCT
cuesj-483	1	13	at	at	ADP
cuesj-483	1	14	32	32	NUM
cuesj-483	1	15	http://journals.cihanuniversity.edu.iq/index.php/cuesj	http://journals.cihanuniversity.edu.iq/index.php/cuesj	ADJ
cuesj-483	1	16	cuesj	cuesj	ADJ
cuesj-483	1	17	2021	2021	NUM
cuesj-483	1	18	,	,	PUNCT
cuesj-483	1	19	5	5	NUM
cuesj-483	1	20	(	(	PUNCT
cuesj-483	1	21	2	2	NUM
cuesj-483	1	22	):	):	PUNCT
cuesj-483	1	23	32	32	NUM
cuesj-483	1	24	-	-	SYM
cuesj-483	1	25	37	37	NUM
cuesj-483	1	26	research	research	NOUN
cuesj-483	1	27	article	article	NOUN
cuesj-483	1	28	a	a	DET
cuesj-483	1	29	comparison	comparison	NOUN
cuesj-483	1	30	between	between	ADP
cuesj-483	1	31	new	new	ADJ
cuesj-483	1	32	modification	modification	NOUN
cuesj-483	1	33	of	of	ADP
cuesj-483	1	34	aadaptive	aadaptive	ADJ
cuesj-483	1	35	nadaraya	nadaraya	PROPN
cuesj-483	1	36	-	-	PUNCT
cuesj-483	1	37	watson	watson	NOUN
cuesj-483	1	38	kernel	kernel	PROPN
cuesj-483	1	39	and	and	CCONJ
cuesj-483	1	40	classical	classical	ADJ
cuesj-483	1	41	aadaptive	aadaptive	ADJ
cuesj-483	1	42	nadaraya	nadaraya	PROPN
cuesj-483	1	43	-	-	PUNCT
cuesj-483	1	44	watson	watson	NOUN
cuesj-483	1	45	kernel	kernel	PROPN
cuesj-483	1	46	methods	method	NOUN
cuesj-483	1	47	in	in	ADP
cuesj-483	1	48	nonparametric	nonparametric	ADJ
cuesj-483	1	49	regression	regression	NOUN
cuesj-483	1	50	:	:	PUNCT
cuesj-483	1	51	a	a	DET
cuesj-483	1	52	simulation	simulation	NOUN
cuesj-483	1	53	study	study	NOUN
cuesj-483	1	54	hazhar	hazhar	VERB
cuesj-483	1	55	t.	t.	PROPN
cuesj-483	1	56	a.	a.	PROPN
cuesj-483	1	57	blbas1	blbas1	PROPN
cuesj-483	1	58	,	,	PUNCT
cuesj-483	1	59	wasfi	wasfi	NOUN
cuesj-483	1	60	t.	t.	PROPN
cuesj-483	1	61	kahwachi2	kahwachi2	PROPN
cuesj-483	2	1	1department	1department	NUM
cuesj-483	2	2	of	of	ADP
cuesj-483	2	3	statistics	statistic	NOUN
cuesj-483	2	4	,	,	PUNCT
cuesj-483	2	5	college	college	NOUN
cuesj-483	2	6	of	of	ADP
cuesj-483	2	7	administration	administration	NOUN
cuesj-483	2	8	and	and	CCONJ
cuesj-483	2	9	economics	economic	NOUN
cuesj-483	2	10	,	,	PUNCT
cuesj-483	2	11	salahaddin	salahaddin	VERB
cuesj-483	2	12	university	university	NOUN
cuesj-483	2	13	-	-	PUNCT
cuesj-483	2	14	erbil	erbil	PROPN
cuesj-483	2	15	,	,	PUNCT
cuesj-483	2	16	kurdistan	kurdistan	PROPN
cuesj-483	2	17	region	region	NOUN
cuesj-483	2	18	,	,	PUNCT
cuesj-483	2	19	iraq	iraq	PROPN
cuesj-483	2	20	,	,	PUNCT
cuesj-483	2	21	2research	2research	NUM
cuesj-483	2	22	center	center	NOUN
cuesj-483	2	23	,	,	PUNCT
cuesj-483	2	24	tishk	tishk	PROPN
cuesj-483	2	25	international	international	ADJ
cuesj-483	2	26	university	university	NOUN
cuesj-483	2	27	-	-	PUNCT
cuesj-483	2	28	erbil	erbil	PROPN
cuesj-483	2	29	,	,	PUNCT
cuesj-483	2	30	kurdistan	kurdistan	ADJ
cuesj-483	2	31	region	region	NOUN
cuesj-483	2	32	,	,	PUNCT
cuesj-483	2	33	iraq	iraq	PROPN
cuesj-483	2	34	abstract	abstract	PROPN
cuesj-483	2	35	nonparametric	nonparametric	NOUN
cuesj-483	2	36	kernel	kernel	PROPN
cuesj-483	2	37	estimators	estimator	NOUN
cuesj-483	2	38	are	be	AUX
cuesj-483	2	39	mostly	mostly	ADV
cuesj-483	2	40	used	use	VERB
cuesj-483	2	41	in	in	ADP
cuesj-483	2	42	a	a	DET
cuesj-483	2	43	variety	variety	NOUN
cuesj-483	2	44	of	of	ADP
cuesj-483	2	45	statistical	statistical	ADJ
cuesj-483	2	46	research	research	NOUN
cuesj-483	2	47	fields	field	NOUN
cuesj-483	2	48	.	.	PUNCT
cuesj-483	3	1	nadaraya	nadaraya	PROPN
cuesj-483	3	2	-	-	PUNCT
cuesj-483	3	3	watson	watson	PROPN
cuesj-483	3	4	kernel	kernel	PROPN
cuesj-483	3	5	(	(	PUNCT
cuesj-483	3	6	nwk	nwk	NOUN
cuesj-483	3	7	)	)	PUNCT
cuesj-483	3	8	estimator	estimator	NOUN
cuesj-483	3	9	is	be	AUX
cuesj-483	3	10	one	one	NUM
cuesj-483	3	11	of	of	ADP
cuesj-483	3	12	the	the	DET
cuesj-483	3	13	most	most	ADV
cuesj-483	3	14	important	important	ADJ
cuesj-483	3	15	nonparametric	nonparametric	ADJ
cuesj-483	3	16	kernel	kernel	NOUN
cuesj-483	3	17	estimators	estimator	NOUN
cuesj-483	3	18	that	that	PRON
cuesj-483	3	19	is	be	AUX
cuesj-483	3	20	often	often	ADV
cuesj-483	3	21	used	use	VERB
cuesj-483	3	22	in	in	ADP
cuesj-483	3	23	regression	regression	NOUN
cuesj-483	3	24	models	model	NOUN
cuesj-483	3	25	with	with	ADP
cuesj-483	3	26	a	a	DET
cuesj-483	3	27	fixed	fix	VERB
cuesj-483	3	28	bandwidth	bandwidth	NOUN
cuesj-483	3	29	.	.	PUNCT
cuesj-483	4	1	in	in	ADP
cuesj-483	4	2	this	this	DET
cuesj-483	4	3	article	article	NOUN
cuesj-483	4	4	,	,	PUNCT
cuesj-483	4	5	we	we	PRON
cuesj-483	4	6	consider	consider	VERB
cuesj-483	4	7	the	the	DET
cuesj-483	4	8	four	four	NUM
cuesj-483	4	9	new	new	ADJ
cuesj-483	4	10	proposed	propose	VERB
cuesj-483	4	11	adaptive	adaptive	ADJ
cuesj-483	4	12	nwk	nwk	NOUN
cuesj-483	4	13	regression	regression	NOUN
cuesj-483	4	14	estimators	estimator	NOUN
cuesj-483	4	15	(	(	PUNCT
cuesj-483	4	16	interquartile	interquartile	NOUN
cuesj-483	4	17	range	range	NOUN
cuesj-483	4	18	[	[	X
cuesj-483	4	19	iqr	iqr	X
cuesj-483	4	20	]	]	X
cuesj-483	4	21	,	,	PUNCT
cuesj-483	4	22	standard	standard	ADJ
cuesj-483	4	23	deviation	deviation	NOUN
cuesj-483	4	24	[	[	X
cuesj-483	4	25	sd	sd	X
cuesj-483	4	26	]	]	PUNCT
cuesj-483	4	27	,	,	PUNCT
cuesj-483	4	28	mean	mean	VERB
cuesj-483	4	29	absolute	absolute	ADJ
cuesj-483	4	30	devotion	devotion	NOUN
cuesj-483	4	31	,	,	PUNCT
cuesj-483	4	32	and	and	CCONJ
cuesj-483	4	33	median	median	ADJ
cuesj-483	4	34	absolute	absolute	ADJ
cuesj-483	4	35	deviation	deviation	NOUN
cuesj-483	4	36	)	)	PUNCT
cuesj-483	4	37	rather	rather	ADV
cuesj-483	4	38	than	than	ADP
cuesj-483	4	39	(	(	PUNCT
cuesj-483	4	40	fixed	fix	VERB
cuesj-483	4	41	bandwidth	bandwidth	NOUN
cuesj-483	4	42	,	,	PUNCT
cuesj-483	4	43	adaptive	adaptive	ADJ
cuesj-483	4	44	geometric	geometric	ADJ
cuesj-483	4	45	,	,	PUNCT
cuesj-483	4	46	adaptive	adaptive	ADJ
cuesj-483	4	47	mean	mean	NOUN
cuesj-483	4	48	,	,	PUNCT
cuesj-483	4	49	adaptive	adaptive	ADJ
cuesj-483	4	50	range	range	NOUN
cuesj-483	4	51	,	,	PUNCT
cuesj-483	4	52	and	and	CCONJ
cuesj-483	4	53	adaptive	adaptive	ADJ
cuesj-483	4	54	median	median	NOUN
cuesj-483	4	55	)	)	PUNCT
cuesj-483	4	56	.	.	PUNCT
cuesj-483	5	1	the	the	DET
cuesj-483	5	2	outcomes	outcome	NOUN
cuesj-483	5	3	in	in	ADP
cuesj-483	5	4	both	both	PRON
cuesj-483	5	5	simulation	simulation	NOUN
cuesj-483	5	6	and	and	CCONJ
cuesj-483	5	7	actual	actual	ADJ
cuesj-483	5	8	data	datum	NOUN
cuesj-483	5	9	in	in	ADP
cuesj-483	5	10	leukemia	leukemia	NOUN
cuesj-483	5	11	cancer	cancer	NOUN
cuesj-483	5	12	showed	show	VERB
cuesj-483	5	13	that	that	SCONJ
cuesj-483	5	14	the	the	DET
cuesj-483	5	15	four	four	NUM
cuesj-483	5	16	new	new	ADJ
cuesj-483	5	17	aadaptive	aadaptive	ADJ
cuesj-483	5	18	nwk	nwk	NOUN
cuesj-483	5	19	estimators	estimator	NOUN
cuesj-483	5	20	(	(	PUNCT
cuesj-483	5	21	iqr	iqr	NOUN
cuesj-483	5	22	,	,	PUNCT
cuesj-483	5	23	sd	sd	NOUN
cuesj-483	5	24	,	,	PUNCT
cuesj-483	5	25	mean	mean	VERB
cuesj-483	5	26	absolute	absolute	ADJ
cuesj-483	5	27	devotion	devotion	NOUN
cuesj-483	5	28	,	,	PUNCT
cuesj-483	5	29	and	and	CCONJ
cuesj-483	5	30	median	median	ADJ
cuesj-483	5	31	absolute	absolute	ADJ
cuesj-483	5	32	deviation	deviation	NOUN
cuesj-483	5	33	)	)	PUNCT
cuesj-483	5	34	are	be	AUX
cuesj-483	5	35	more	more	ADV
cuesj-483	5	36	effective	effective	ADJ
cuesj-483	5	37	than	than	ADP
cuesj-483	5	38	the	the	DET
cuesj-483	5	39	kernel	kernel	PROPN
cuesj-483	5	40	estimations	estimation	NOUN
cuesj-483	5	41	with	with	ADP
cuesj-483	5	42	fixed	fix	VERB
cuesj-483	5	43	bandwidth	bandwidth	NOUN
cuesj-483	5	44	in	in	ADP
cuesj-483	5	45	previous	previous	ADJ
cuesj-483	5	46	studies	study	NOUN
cuesj-483	5	47	based	base	VERB
cuesj-483	5	48	mean	mean	PROPN
cuesj-483	5	49	square	square	ADJ
cuesj-483	5	50	error	error	NOUN
cuesj-483	5	51	criterion	criterion	NOUN
cuesj-483	5	52	.	.	PUNCT
cuesj-483	6	1	keywords	keyword	NOUN
cuesj-483	6	2	:	:	PUNCT
cuesj-483	6	3	nonparametric	nonparametric	NOUN
cuesj-483	6	4	regression	regression	NOUN
cuesj-483	6	5	,	,	PUNCT
cuesj-483	6	6	kernel	kernel	PROPN
cuesj-483	6	7	regression	regression	PROPN
cuesj-483	6	8	,	,	PUNCT
cuesj-483	6	9	new	new	ADJ
cuesj-483	6	10	aadaptive	aadaptive	ADJ
cuesj-483	6	11	nadaraya	nadaraya	PROPN
cuesj-483	6	12	-	-	PUNCT
cuesj-483	6	13	watson	watson	NOUN
cuesj-483	6	14	estimators	estimator	NOUN
cuesj-483	6	15	,	,	PUNCT
cuesj-483	6	16	leukemia	leukemia	NOUN
cuesj-483	6	17	cancer	cancer	NOUN
cuesj-483	6	18	,	,	PUNCT
cuesj-483	6	19	acute	acute	ADJ
cuesj-483	6	20	myeloid	myeloid	NOUN
cuesj-483	6	21	leukemia	leukemia	NOUN
cuesj-483	6	22	introduction	introduction	NOUN
cuesj-483	6	23	nonparametric	nonparametric	NOUN
cuesj-483	6	24	regression	regression	NOUN
cuesj-483	6	25	models	model	NOUN
cuesj-483	6	26	aim	aim	VERB
cuesj-483	6	27	to	to	PART
cuesj-483	6	28	precisely	precisely	ADV
cuesj-483	6	29	determine	determine	VERB
cuesj-483	6	30	the	the	DET
cuesj-483	6	31	relationship	relationship	NOUN
cuesj-483	6	32	between	between	ADP
cuesj-483	6	33	explanatory	explanatory	ADJ
cuesj-483	6	34	and	and	CCONJ
cuesj-483	6	35	response	response	NOUN
cuesj-483	6	36	variables	variable	NOUN
cuesj-483	6	37	in	in	ADP
cuesj-483	6	38	various	various	ADJ
cuesj-483	6	39	statistical	statistical	ADJ
cuesj-483	6	40	situations	situation	NOUN
cuesj-483	6	41	;	;	PUNCT
cuesj-483	6	42	however	however	ADV
cuesj-483	6	43	,	,	PUNCT
cuesj-483	6	44	they	they	PRON
cuesj-483	6	45	are	be	AUX
cuesj-483	6	46	substantially	substantially	ADV
cuesj-483	6	47	less	less	ADV
cuesj-483	6	48	successful	successful	ADJ
cuesj-483	6	49	than	than	ADP
cuesj-483	6	50	parametric	parametric	ADJ
cuesj-483	6	51	approaches	approach	NOUN
cuesj-483	6	52	when	when	SCONJ
cuesj-483	6	53	fitting	fit	VERB
cuesj-483	6	54	a	a	DET
cuesj-483	6	55	normal	normal	ADJ
cuesj-483	6	56	distribution	distribution	NOUN
cuesj-483	6	57	.	.	PUNCT
cuesj-483	7	1	on	on	ADP
cuesj-483	7	2	the	the	DET
cuesj-483	7	3	opposite	opposite	ADJ
cuesj-483	7	4	side	side	NOUN
cuesj-483	7	5	,	,	PUNCT
cuesj-483	7	6	nonparametric	nonparametric	NOUN
cuesj-483	7	7	models	model	NOUN
cuesj-483	7	8	are	be	AUX
cuesj-483	7	9	highly	highly	ADV
cuesj-483	7	10	efficient	efficient	ADJ
cuesj-483	7	11	in	in	ADP
cuesj-483	7	12	populations	population	NOUN
cuesj-483	7	13	that	that	PRON
cuesj-483	7	14	do	do	AUX
cuesj-483	7	15	not	not	PART
cuesj-483	7	16	fit	fit	VERB
cuesj-483	7	17	normal	normal	ADJ
cuesj-483	7	18	distribution.[10	distribution.[10	NOUN
cuesj-483	7	19	]	]	PUNCT
cuesj-483	7	20	they	they	PRON
cuesj-483	7	21	may	may	AUX
cuesj-483	7	22	be	be	AUX
cuesj-483	7	23	used	use	VERB
cuesj-483	7	24	to	to	ADP
cuesj-483	7	25	a	a	DET
cuesj-483	7	26	wide	wide	ADJ
cuesj-483	7	27	range	range	NOUN
cuesj-483	7	28	of	of	ADP
cuesj-483	7	29	data	datum	NOUN
cuesj-483	7	30	types	type	NOUN
cuesj-483	7	31	such	such	ADJ
cuesj-483	7	32	as	as	ADP
cuesj-483	7	33	ordinal	ordinal	ADJ
cuesj-483	7	34	,	,	PUNCT
cuesj-483	7	35	nominal	nominal	ADJ
cuesj-483	7	36	,	,	PUNCT
cuesj-483	7	37	ratio	ratio	NOUN
cuesj-483	7	38	,	,	PUNCT
cuesj-483	7	39	and	and	CCONJ
cuesj-483	7	40	interval	interval	NOUN
cuesj-483	7	41	data.[17	data.[17	PROPN
cuesj-483	7	42	]	]	PUNCT
cuesj-483	7	43	suppose	suppose	VERB
cuesj-483	7	44	the	the	DET
cuesj-483	7	45	regression	regression	NOUN
cuesj-483	7	46	model	model	NOUN
cuesj-483	7	47	for	for	ADP
cuesj-483	7	48	a	a	DET
cuesj-483	7	49	given	give	VERB
cuesj-483	7	50	data	data	NOUN
cuesj-483	7	51	points	point	NOUN
cuesj-483	7	52	(	(	PUNCT
cuesj-483	7	53	,	,	PUNCT
cuesj-483	7	54	)	)	PUNCT
cuesj-483	7	55	(	(	PUNCT
cuesj-483	7	56	)	)	PUNCT
cuesj-483	8	1	x	x	X
cuesj-483	8	2	y	y	NOUN
cuesj-483	8	3	ri	ri	INTJ
cuesj-483	9	1	i	i	PRON
cuesj-483	9	2	i	i	PROPN
cuesj-483	9	3	n	n	PRON
cuesj-483	9	4	�	�	PROPN
cuesj-483	9	5	�	�	PROPN
cuesj-483	9	6	1	1	NUM
cuesj-483	9	7	is	be	AUX
cuesj-483	9	8	y	y	PROPN
cuesj-483	9	9	f	f	PROPN
cuesj-483	9	10	x	x	X
cuesj-483	9	11	ii	ii	VERB
cuesj-483	10	1	i	i	PRON
cuesj-483	10	2	i	i	PROPN
cuesj-483	10	3	�	�	PROPN
cuesj-483	10	4	�	�	PROPN
cuesj-483	10	5	�	�	PROPN
cuesj-483	10	6	�	�	PROPN
cuesj-483	10	7	�	�	PROPN
cuesj-483	10	8	�	�	PROPN
cuesj-483	10	9	�	�	PROPN
cuesj-483	10	10	;	;	PUNCT
cuesj-483	10	11	,	,	PUNCT
cuesj-483	10	12	,	,	PUNCT
cuesj-483	10	13	,	,	PUNCT
cuesj-483	10	14	,	,	PUNCT
cuesj-483	10	15	1	1	NUM
cuesj-483	10	16	2	2	NUM
cuesj-483	10	17	3	3	NUM
cuesj-483	10	18	(	(	PUNCT
cuesj-483	10	19	1	1	NUM
cuesj-483	10	20	`	`	NUM
cuesj-483	10	21	)	)	PUNCT
cuesj-483	10	22	where	where	SCONJ
cuesj-483	10	23	ℇi	ℇi	PROPN
cuesj-483	10	24	is	be	AUX
cuesj-483	10	25	an	an	DET
cuesj-483	10	26	observation	observation	NOUN
cuesj-483	10	27	error	error	NOUN
cuesj-483	10	28	with	with	ADP
cuesj-483	10	29	zero	zero	NUM
cuesj-483	10	30	mean	mean	NOUN
cuesj-483	10	31	variance	variance	NOUN
cuesj-483	10	32	σ2	σ2	PROPN
cuesj-483	10	33	and	and	CCONJ
cuesj-483	10	34	m	m	PROPN
cuesj-483	10	35	is	be	AUX
cuesj-483	10	36	unknown	unknown	ADJ
cuesj-483	10	37	regression	regression	NOUN
cuesj-483	10	38	function	function	NOUN
cuesj-483	10	39	.	.	PUNCT
cuesj-483	11	1	smoothing	smooth	VERB
cuesj-483	11	2	is	be	AUX
cuesj-483	11	3	a	a	DET
cuesj-483	11	4	significant	significant	ADJ
cuesj-483	11	5	aspect	aspect	NOUN
cuesj-483	11	6	in	in	ADP
cuesj-483	11	7	the	the	DET
cuesj-483	11	8	nonparametric	nonparametric	NOUN
cuesj-483	11	9	regression	regression	NOUN
cuesj-483	11	10	process	process	NOUN
cuesj-483	11	11	and	and	CCONJ
cuesj-483	11	12	is	be	AUX
cuesj-483	11	13	a	a	DET
cuesj-483	11	14	technique	technique	NOUN
cuesj-483	11	15	for	for	ADP
cuesj-483	11	16	expressing	express	VERB
cuesj-483	11	17	the	the	DET
cuesj-483	11	18	dependent	dependent	ADJ
cuesj-483	11	19	variable	variable	NOUN
cuesj-483	11	20	’s	’s	PART
cuesj-483	11	21	pattern.[11	pattern.[11	PROPN
cuesj-483	11	22	]	]	PUNCT
cuesj-483	11	23	there	there	PRON
cuesj-483	11	24	have	have	AUX
cuesj-483	11	25	been	be	AUX
cuesj-483	11	26	four	four	NUM
cuesj-483	11	27	main	main	ADJ
cuesj-483	11	28	factors	factor	NOUN
cuesj-483	11	29	for	for	ADP
cuesj-483	11	30	doing	do	VERB
cuesj-483	11	31	a	a	DET
cuesj-483	11	32	nonparametric	nonparametric	ADJ
cuesj-483	11	33	regression	regression	NOUN
cuesj-483	11	34	approaches	approach	NOUN
cuesj-483	11	35	for	for	ADP
cuesj-483	11	36	fitting	fitting	ADJ
cuesj-483	11	37	data	datum	NOUN
cuesj-483	11	38	depending	depend	VERB
cuesj-483	11	39	on.[17	on.[17	PROPN
cuesj-483	11	40	]	]	PUNCT
cuesj-483	11	41	first	first	ADV
cuesj-483	11	42	,	,	PUNCT
cuesj-483	11	43	to	to	PART
cuesj-483	11	44	know	know	VERB
cuesj-483	11	45	the	the	DET
cuesj-483	11	46	relationship	relationship	NOUN
cuesj-483	11	47	between	between	ADP
cuesj-483	11	48	predictor	predictor	NOUN
cuesj-483	11	49	and	and	CCONJ
cuesj-483	11	50	response	response	NOUN
cuesj-483	11	51	variable	variable	NOUN
cuesj-483	11	52	.	.	PUNCT
cuesj-483	12	1	second	second	ADJ
cuesj-483	12	2	,	,	PUNCT
cuesj-483	12	3	to	to	PART
cuesj-483	12	4	enable	enable	VERB
cuesj-483	12	5	predictions	prediction	NOUN
cuesj-483	12	6	of	of	ADP
cuesj-483	12	7	future	future	ADJ
cuesj-483	12	8	findings	finding	NOUN
cuesj-483	12	9	without	without	ADP
cuesj-483	12	10	using	use	VERB
cuesj-483	12	11	a	a	DET
cuesj-483	12	12	fixed	fix	VERB
cuesj-483	12	13	parametric	parametric	ADJ
cuesj-483	12	14	model	model	NOUN
cuesj-483	12	15	.	.	PUNCT
cuesj-483	13	1	third	third	ADV
cuesj-483	13	2	,	,	PUNCT
cuesj-483	13	3	by	by	ADP
cuesj-483	13	4	studying	study	VERB
cuesj-483	13	5	the	the	DET
cuesj-483	13	6	results	result	NOUN
cuesj-483	13	7	of	of	ADP
cuesj-483	13	8	individual	individual	ADJ
cuesj-483	13	9	locations	location	NOUN
cuesj-483	13	10	,	,	PUNCT
cuesj-483	13	11	it	it	PRON
cuesj-483	13	12	offers	offer	VERB
cuesj-483	13	13	a	a	DET
cuesj-483	13	14	method	method	NOUN
cuesj-483	13	15	for	for	ADP
cuesj-483	13	16	detecting	detect	VERB
cuesj-483	13	17	spurious	spurious	ADJ
cuesj-483	13	18	findings	finding	NOUN
cuesj-483	13	19	.	.	PUNCT
cuesj-483	14	1	finally	finally	ADV
cuesj-483	14	2	,	,	PUNCT
cuesj-483	14	3	working	work	VERB
cuesj-483	14	4	to	to	PART
cuesj-483	14	5	solve	solve	VERB
cuesj-483	14	6	the	the	DET
cuesj-483	14	7	absent	absent	ADJ
cuesj-483	14	8	values	value	NOUN
cuesj-483	14	9	by	by	ADP
cuesj-483	14	10	replacing	replace	VERB
cuesj-483	14	11	or	or	CCONJ
cuesj-483	14	12	merging	merge	VERB
cuesj-483	14	13	neighboring	neighboring	NOUN
cuesj-483	14	14	values	value	NOUN
cuesj-483	14	15	of	of	ADP
cuesj-483	14	16	the	the	DET
cuesj-483	14	17	independent	independent	ADJ
cuesj-483	14	18	variables	variable	NOUN
cuesj-483	14	19	x.[18	x.[18	PROPN
cuesj-483	14	20	]	]	PUNCT
cuesj-483	14	21	kernel	kernel	PROPN
cuesj-483	14	22	regression	regression	PROPN
cuesj-483	14	23	assume	assume	VERB
cuesj-483	14	24	that	that	SCONJ
cuesj-483	14	25	x1	x1	PROPN
cuesj-483	14	26	,	,	PUNCT
cuesj-483	14	27	x2	x2	PROPN
cuesj-483	14	28	,	,	PUNCT
cuesj-483	14	29	…	…	PUNCT
cuesj-483	14	30	,	,	PUNCT
cuesj-483	14	31	xn	xn	PROPN
cuesj-483	14	32	from	from	ADP
cuesj-483	14	33	a	a	DET
cuesj-483	14	34	random	random	ADJ
cuesj-483	14	35	variable	variable	NOUN
cuesj-483	14	36	describe	describe	VERB
cuesj-483	14	37	a	a	DET
cuesj-483	14	38	sample	sample	NOUN
cuesj-483	14	39	of	of	ADP
cuesj-483	14	40	size	size	NOUN
cuesj-483	14	41	(	(	PUNCT
cuesj-483	14	42	n	n	CCONJ
cuesj-483	14	43	)	)	PUNCT
cuesj-483	14	44	with	with	ADP
cuesj-483	14	45	density	density	NOUN
cuesj-483	14	46	f(x).[1	f(x).[1	PROPN
cuesj-483	14	47	]	]	PUNCT
cuesj-483	14	48	bring	bring	VERB
cuesj-483	14	49	the	the	DET
cuesj-483	14	50	kernel	kernel	PROPN
cuesj-483	14	51	density	density	PROPN
cuesj-483	14	52	function	function	NOUN
cuesj-483	14	53	of	of	ADP
cuesj-483	14	54	f(x	f(x	PROPN
cuesj-483	14	55	)	)	PUNCT
cuesj-483	14	56	at	at	ADP
cuesj-483	14	57	point	point	NOUN
cuesj-483	14	58	x	x	SYM
cuesj-483	14	59	:	:	PUNCT
cuesj-483	14	60	(	(	PUNCT
cuesj-483	14	61	)	)	PUNCT
cuesj-483	14	62	1	1	NUM
cuesj-483	14	63	1ˆ	1ˆ	NOUN
cuesj-483	14	64	=	=	SYM
cuesj-483	14	65	−	−	VERB
cuesj-483	14	66	=	=	PROPN
cuesj-483	14	67			NOUN
cuesj-483	14	68			NOUN
cuesj-483	14	69			PRON
cuesj-483	14	70			PUNCT
cuesj-483	15	1	∑	∑	PUNCT
cuesj-483	15	2	n	n	INTJ
cuesj-483	16	1	i	i	PRON
cuesj-483	16	2	h	h	VERB
cuesj-483	17	1	i	i	NOUN
cuesj-483	17	2	x	x	NOUN
cuesj-483	17	3	xf	xf	PROPN
cuesj-483	17	4	x	x	PROPN
cuesj-483	17	5	k	k	PROPN
cuesj-483	17	6	nh	nh	PROPN
cuesj-483	17	7	h	h	PROPN
cuesj-483	17	8	(	(	PUNCT
cuesj-483	17	9	2	2	NUM
cuesj-483	17	10	)	)	PUNCT
cuesj-483	17	11	kernel	kernel	NOUN
cuesj-483	17	12	regression	regression	NOUN
cuesj-483	17	13	(	(	PUNCT
cuesj-483	17	14	nadaraya	nadaraya	NOUN
cuesj-483	17	15	-	-	PUNCT
cuesj-483	17	16	watson	watson	NOUN
cuesj-483	17	17	estimator	estimator	NOUN
cuesj-483	17	18	)	)	PUNCT
cuesj-483	17	19	was	be	AUX
cuesj-483	17	20	established	establish	VERB
cuesj-483	17	21	by	by	ADP
cuesj-483	17	22	nadaraya	nadaraya	NOUN
cuesj-483	17	23	in	in	ADP
cuesj-483	17	24	1965	1965	NUM
cuesj-483	17	25	and	and	CCONJ
cuesj-483	17	26	watson	watson	PROPN
cuesj-483	17	27	in	in	ADP
cuesj-483	17	28	1964	1964	NUM
cuesj-483	17	29	which	which	PRON
cuesj-483	17	30	is	be	AUX
cuesj-483	17	31	corresponding	corresponding	ADJ
cuesj-483	17	32	author	author	NOUN
cuesj-483	17	33	:	:	PUNCT
cuesj-483	17	34	hazhar	hazhar	PROPN
cuesj-483	17	35	t.	t.	PROPN
cuesj-483	17	36	a.	a.	PROPN
cuesj-483	17	37	blbas	blbas	PROPN
cuesj-483	17	38	,	,	PUNCT
cuesj-483	17	39	department	department	NOUN
cuesj-483	17	40	of	of	ADP
cuesj-483	17	41	statistics	statistic	NOUN
cuesj-483	17	42	,	,	PUNCT
cuesj-483	17	43	college	college	NOUN
cuesj-483	17	44	of	of	ADP
cuesj-483	17	45	administration	administration	NOUN
cuesj-483	17	46	and	and	CCONJ
cuesj-483	17	47	economics	economic	NOUN
cuesj-483	17	48	,	,	PUNCT
cuesj-483	17	49	salahaddin	salahaddin	VERB
cuesj-483	17	50	university	university	NOUN
cuesj-483	17	51	-	-	PUNCT
cuesj-483	17	52	erbil	erbil	PROPN
cuesj-483	17	53	,	,	PUNCT
cuesj-483	17	54	kurdistan	kurdistan	PROPN
cuesj-483	17	55	region	region	NOUN
cuesj-483	17	56	,	,	PUNCT
cuesj-483	17	57	iraq	iraq	PROPN
cuesj-483	17	58	.	.	PUNCT
cuesj-483	18	1	e	e	X
cuesj-483	18	2	-	-	NOUN
cuesj-483	18	3	mail	mail	NOUN
cuesj-483	18	4	:	:	PUNCT
cuesj-483	19	1	hazharstat@gmail.com	hazharstat@gmail.com	X
cuesj-483	19	2	received	receive	VERB
cuesj-483	19	3	:	:	PUNCT
cuesj-483	19	4	september	september	PROPN
cuesj-483	19	5	4	4	NUM
cuesj-483	19	6	,	,	PUNCT
cuesj-483	19	7	2021	2021	NUM
cuesj-483	19	8	accepted	accept	VERB
cuesj-483	19	9	:	:	PUNCT
cuesj-483	19	10	october	october	PROPN
cuesj-483	19	11	1	1	NUM
cuesj-483	19	12	,	,	PUNCT
cuesj-483	19	13	2021	2021	NUM
cuesj-483	19	14	published	publish	VERB
cuesj-483	19	15	:	:	PUNCT
cuesj-483	19	16	october	october	PROPN
cuesj-483	19	17	30	30	NUM
cuesj-483	19	18	,	,	PUNCT
cuesj-483	19	19	2021	2021	NUM
cuesj-483	19	20	doi	doi	NOUN
cuesj-483	19	21	:	:	PUNCT
cuesj-483	19	22	10.24086	10.24086	NUM
cuesj-483	19	23	/	/	SYM
cuesj-483	19	24	cuesj.v5n2y2021.pp32	cuesj.v5n2y2021.pp32	NUM
cuesj-483	19	25	-	-	SYM
cuesj-483	19	26	37	37	NUM
cuesj-483	19	27	copyright	copyright	NOUN
cuesj-483	19	28	©	©	PROPN
cuesj-483	19	29	2021	2021	NUM
cuesj-483	19	30	hazhar	hazhar	PROPN
cuesj-483	19	31	t.	t.	PROPN
cuesj-483	19	32	a.	a.	NOUN
cuesj-483	19	33	blbas	blbas	PROPN
cuesj-483	19	34	,	,	PUNCT
cuesj-483	19	35	wasfi	wasfi	NOUN
cuesj-483	19	36	t.	t.	PROPN
cuesj-483	19	37	kahwachi	kahwachi	PROPN
cuesj-483	19	38	.	.	PUNCT
cuesj-483	20	1	this	this	PRON
cuesj-483	20	2	is	be	AUX
cuesj-483	20	3	an	an	DET
cuesj-483	20	4	openaccess	openaccess	ADJ
cuesj-483	20	5	article	article	NOUN
cuesj-483	20	6	distributed	distribute	VERB
cuesj-483	20	7	under	under	ADP
cuesj-483	20	8	the	the	DET
cuesj-483	20	9	creative	creative	ADJ
cuesj-483	20	10	commons	common	NOUN
cuesj-483	20	11	attribution	attribution	NOUN
cuesj-483	20	12	license	license	NOUN
cuesj-483	20	13	(	(	PUNCT
cuesj-483	20	14	cc	cc	NOUN
cuesj-483	20	15	by	by	ADP
cuesj-483	20	16	-	-	PUNCT
cuesj-483	20	17	nc	nc	VERB
cuesj-483	20	18	-	-	PROPN
cuesj-483	20	19	nd	nd	PRON
cuesj-483	20	20	4.0	4.0	NUM
cuesj-483	20	21	)	)	PUNCT
cuesj-483	20	22	.	.	PUNCT
cuesj-483	21	1	cihan	cihan	VERB
cuesj-483	21	2	university	university	NOUN
cuesj-483	21	3	-	-	PUNCT
cuesj-483	21	4	erbil	erbil	PROPN
cuesj-483	21	5	scientific	scientific	ADJ
cuesj-483	21	6	journal	journal	NOUN
cuesj-483	21	7	(	(	PUNCT
cuesj-483	21	8	cuesj	cuesj	PROPN
cuesj-483	21	9	)	)	PUNCT
cuesj-483	21	10	blbas	blbas	PROPN
cuesj-483	21	11	and	and	CCONJ
cuesj-483	21	12	kahwachi	kahwachi	PROPN
cuesj-483	21	13	:	:	PUNCT
cuesj-483	21	14	new	new	ADJ
cuesj-483	21	15	modification	modification	NOUN
cuesj-483	21	16	of	of	ADP
cuesj-483	21	17	anwk	anwk	NOUN
cuesj-483	21	18	in	in	ADP
cuesj-483	21	19	nonparametric	nonparametric	PROPN
cuesj-483	21	20	regression	regression	NOUN
cuesj-483	21	21	33	33	NUM
cuesj-483	21	22	http://journals.cihanuniversity.edu.iq/index.php/cuesj	http://journals.cihanuniversity.edu.iq/index.php/cuesj	ADJ
cuesj-483	21	23	cuesj	cuesj	ADJ
cuesj-483	21	24	2021	2021	NUM
cuesj-483	21	25	,	,	PUNCT
cuesj-483	21	26	5	5	NUM
cuesj-483	21	27	(	(	PUNCT
cuesj-483	21	28	2	2	NUM
cuesj-483	21	29	):	):	PUNCT
cuesj-483	21	30	32	32	NUM
cuesj-483	21	31	-	-	SYM
cuesj-483	21	32	37	37	NUM
cuesj-483	21	33	one	one	NUM
cuesj-483	21	34	of	of	ADP
cuesj-483	21	35	the	the	DET
cuesj-483	21	36	most	most	ADV
cuesj-483	21	37	frequently	frequently	ADV
cuesj-483	21	38	used	use	VERB
cuesj-483	21	39	technique	technique	NOUN
cuesj-483	21	40	in	in	ADP
cuesj-483	21	41	nonparametric.[5,6,12	nonparametric.[5,6,12	PROPN
cuesj-483	21	42	]	]	PUNCT
cuesj-483	21	43	both	both	CCONJ
cuesj-483	21	44	nadaraya	nadaraya	PROPN
cuesj-483	21	45	and	and	CCONJ
cuesj-483	21	46	watson	watson	PROPN
cuesj-483	21	47	indicated	indicate	VERB
cuesj-483	21	48	the	the	DET
cuesj-483	21	49	general	general	ADJ
cuesj-483	21	50	estimator	estimator	NOUN
cuesj-483	21	51	of	of	ADP
cuesj-483	21	52	(	(	PUNCT
cuesj-483	21	53	)	)	PUNCT
cuesj-483	21	54	ˆ	ˆ	NOUN
cuesj-483	21	55	f	f	NOUN
cuesj-483	21	56	x	x	PUNCT
cuesj-483	21	57	in	in	ADP
cuesj-483	21	58	nonparametric	nonparametric	ADJ
cuesj-483	21	59	regression	regression	NOUN
cuesj-483	21	60	related	relate	VERB
cuesj-483	21	61	to	to	ADP
cuesj-483	21	62	smoothing	smooth	VERB
cuesj-483	21	63	bandwidth	bandwidth	NOUN
cuesj-483	21	64	(	(	PUNCT
cuesj-483	21	65	h	h	NOUN
cuesj-483	21	66	)	)	PUNCT
cuesj-483	21	67	and	and	CCONJ
cuesj-483	21	68	kernel	kernel	PROPN
cuesj-483	21	69	(	(	PUNCT
cuesj-483	21	70	k	k	NOUN
cuesj-483	21	71	)	)	PUNCT
cuesj-483	21	72	in	in	ADP
cuesj-483	21	73	bellow	bellow	ADJ
cuesj-483	21	74	formula	formula	NOUN
cuesj-483	21	75	.	.	PUNCT
cuesj-483	22	1	(	(	PUNCT
cuesj-483	22	2	)	)	PUNCT
cuesj-483	22	3	1	1	NUM
cuesj-483	22	4	1	1	NUM
cuesj-483	22	5	ˆ	ˆ	NOUN
cuesj-483	22	6	=	=	SYM
cuesj-483	22	7	=	=	SYM
cuesj-483	22	8	−	−	VERB
cuesj-483	22	9			PROPN
cuesj-483	22	10			NOUN
cuesj-483	22	11			NOUN
cuesj-483	22	12			NOUN
cuesj-483	22	13	=	=	VERB
cuesj-483	22	14	−	−	PROPN
cuesj-483	22	15			PROPN
cuesj-483	22	16			NOUN
cuesj-483	22	17			VERB
cuesj-483	22	18			PRON
cuesj-483	22	19			PUNCT
cuesj-483	22	20	∑	∑	PUNCT
cuesj-483	22	21	∑	∑	PROPN
cuesj-483	22	22	n	n	PROPN
cuesj-483	22	23	i	i	PRON
cuesj-483	22	24	ii	ii	VERB
cuesj-483	23	1	n	n	ADV
cuesj-483	23	2	i	i	PRON
cuesj-483	24	1	i	i	INTJ
cuesj-483	24	2	x	x	VERB
cuesj-483	24	3	xk	xk	PROPN
cuesj-483	24	4	y	y	PROPN
cuesj-483	24	5	hf	hf	PROPN
cuesj-483	24	6	x	x	PUNCT
cuesj-483	24	7	x	x	PUNCT
cuesj-483	24	8	xk	xk	PROPN
cuesj-483	24	9	h	h	PROPN
cuesj-483	24	10	(	(	PUNCT
cuesj-483	24	11	3	3	NUM
cuesj-483	24	12	)	)	PUNCT
cuesj-483	24	13	(	(	PUNCT
cuesj-483	24	14	)	)	PUNCT
cuesj-483	24	15	1	1	NUM
cuesj-483	24	16	ˆ	ˆ	X
cuesj-483	24	17	=	=	SYM
cuesj-483	24	18	=	=	SYM
cuesj-483	24	19	∑	∑	PUNCT
cuesj-483	24	20	n	n	PROPN
cuesj-483	25	1	i	i	PRON
cuesj-483	25	2	i	i	PRON
cuesj-483	26	1	i	i	PRON
cuesj-483	26	2	f	f	X
cuesj-483	27	1	x	x	X
cuesj-483	27	2	w	w	PROPN
cuesj-483	27	3	y	y	PROPN
cuesj-483	27	4	(	(	PUNCT
cuesj-483	27	5	4	4	NUM
cuesj-483	27	6	)	)	PUNCT
cuesj-483	27	7	u	u	NOUN
cuesj-483	27	8	x	x	NOUN
cuesj-483	27	9	x	x	SYM
cuesj-483	27	10	h	h	VERB
cuesj-483	27	11	i	i	PROPN
cuesj-483	27	12	�	�	PROPN
cuesj-483	27	13	�	�	PROPN
cuesj-483	27	14	�	�	PROPN
cuesj-483	27	15	�	�	PROPN
cuesj-483	27	16	�	�	PROPN
cuesj-483	27	17	�	�	PROPN
cuesj-483	27	18	�	�	PROPN
cuesj-483	27	19	�	�	PROPN
cuesj-483	27	20	(	(	PUNCT
cuesj-483	27	21	5	5	NUM
cuesj-483	27	22	)	)	PUNCT
cuesj-483	27	23	the	the	DET
cuesj-483	27	24	smoothing	smoothing	NOUN
cuesj-483	27	25	or	or	CCONJ
cuesj-483	27	26	bandwidth	bandwidth	ADJ
cuesj-483	27	27	parameter	parameter	NOUN
cuesj-483	27	28	h	h	NOUN
cuesj-483	27	29	is	be	AUX
cuesj-483	27	30	used	use	VERB
cuesj-483	27	31	to	to	PART
cuesj-483	27	32	control	control	VERB
cuesj-483	27	33	the	the	DET
cuesj-483	27	34	smoothness	smoothness	NOUN
cuesj-483	27	35	of	of	ADP
cuesj-483	27	36	the	the	DET
cuesj-483	27	37	approximate	approximate	ADJ
cuesj-483	27	38	graph	graph	NOUN
cuesj-483	27	39	,	,	PUNCT
cuesj-483	27	40	and	and	CCONJ
cuesj-483	27	41	the	the	DET
cuesj-483	27	42	kernel	kernel	NOUN
cuesj-483	27	43	weights	weight	VERB
cuesj-483	27	44	as	as	SCONJ
cuesj-483	27	45	identified	identify	VERB
cuesj-483	27	46	by	by	ADP
cuesj-483	27	47	w	w	PROPN
cuesj-483	27	48	x	x	PROPN
cuesj-483	28	1	x	x	SYM
cuesj-483	28	2	h	h	NOUN
cuesj-483	28	3	k	k	NOUN
cuesj-483	28	4	x	x	PUNCT
cuesj-483	28	5	x	x	X
cuesj-483	28	6	h	h	NOUN
cuesj-483	29	1	i	i	PRON
cuesj-483	29	2	i	i	PRON
cuesj-483	30	1	n	n	VERB
cuesj-483	31	1	i	i	PRON
cuesj-483	31	2	i	i	PRON
cuesj-483	32	1	n	n	VERB
cuesj-483	32	2	i	i	PROPN
cuesj-483	32	3	�	�	PROPN
cuesj-483	32	4	�	�	PROPN
cuesj-483	32	5	�	�	PROPN
cuesj-483	32	6	�	�	PROPN
cuesj-483	32	7	�	�	PROPN
cuesj-483	32	8	�	�	PROPN
cuesj-483	32	9	�	�	PROPN
cuesj-483	32	10	�	�	PROPN
cuesj-483	32	11	�	�	PROPN
cuesj-483	32	12	�	�	PROPN
cuesj-483	32	13	�	�	PROPN
cuesj-483	32	14	�	�	PROPN
cuesj-483	32	15	�	�	PROPN
cuesj-483	32	16	�	�	PROPN
cuesj-483	32	17	�	�	PROPN
cuesj-483	32	18	�	�	PROPN
cuesj-483	32	19	�	�	PROPN
cuesj-483	32	20	�	�	PROPN
cuesj-483	32	21	�	�	PROPN
cuesj-483	32	22	1	1	NUM
cuesj-483	32	23	1	1	NUM
cuesj-483	32	24	(	(	PUNCT
cuesj-483	32	25	6	6	NUM
cuesj-483	32	26	)	)	PUNCT
cuesj-483	32	27	the	the	DET
cuesj-483	32	28	most	most	ADV
cuesj-483	32	29	important	important	ADJ
cuesj-483	32	30	factor	factor	NOUN
cuesj-483	32	31	to	to	PART
cuesj-483	32	32	consider	consider	VERB
cuesj-483	32	33	in	in	ADP
cuesj-483	32	34	nonparametric	nonparametric	ADJ
cuesj-483	32	35	regression	regression	NOUN
cuesj-483	32	36	is	be	AUX
cuesj-483	32	37	choosing	choose	VERB
cuesj-483	32	38	bandwidth	bandwidth	ADJ
cuesj-483	32	39	and	and	CCONJ
cuesj-483	32	40	kernel	kernel	PROPN
cuesj-483	32	41	function	function	NOUN
cuesj-483	32	42	.	.	PUNCT
cuesj-483	33	1	on	on	ADP
cuesj-483	33	2	the	the	DET
cuesj-483	33	3	other	other	ADJ
cuesj-483	33	4	hand	hand	NOUN
cuesj-483	33	5	,	,	PUNCT
cuesj-483	33	6	the	the	DET
cuesj-483	33	7	selection	selection	NOUN
cuesj-483	33	8	of	of	ADP
cuesj-483	33	9	bandwidth	bandwidth	NOUN
cuesj-483	33	10	is	be	AUX
cuesj-483	33	11	much	much	ADV
cuesj-483	33	12	more	more	ADV
cuesj-483	33	13	essential	essential	ADJ
cuesj-483	33	14	than	than	ADP
cuesj-483	33	15	the	the	DET
cuesj-483	33	16	choice	choice	NOUN
cuesj-483	33	17	of	of	ADP
cuesj-483	33	18	kernel	kernel	PROPN
cuesj-483	33	19	function	function	PROPN
cuesj-483	33	20	on	on	ADP
cuesj-483	33	21	estimation.[8	estimation.[8	NOUN
cuesj-483	33	22	]	]	X
cuesj-483	33	23	the	the	DET
cuesj-483	33	24	smoothed	smooth	VERB
cuesj-483	33	25	function	function	NOUN
cuesj-483	33	26	can	can	AUX
cuesj-483	33	27	be	be	AUX
cuesj-483	33	28	expressed	express	VERB
cuesj-483	33	29	by	by	ADP
cuesj-483	33	30	scanning	scan	VERB
cuesj-483	33	31	each	each	DET
cuesj-483	33	32	data	datum	NOUN
cuesj-483	33	33	point	point	NOUN
cuesj-483	33	34	with	with	ADP
cuesj-483	33	35	a	a	DET
cuesj-483	33	36	weighted	weight	VERB
cuesj-483	33	37	kernel	kernel	NOUN
cuesj-483	33	38	function	function	NOUN
cuesj-483	33	39	and	and	CCONJ
cuesj-483	33	40	then	then	ADV
cuesj-483	33	41	evaluating	evaluate	VERB
cuesj-483	33	42	the	the	DET
cuesj-483	33	43	input	input	NOUN
cuesj-483	33	44	at	at	ADP
cuesj-483	33	45	each	each	DET
cuesj-483	33	46	point	point	NOUN
cuesj-483	33	47	.	.	PUNCT
cuesj-483	34	1	the	the	DET
cuesj-483	34	2	kernel	kernel	PROPN
cuesj-483	34	3	function	function	NOUN
cuesj-483	34	4	is	be	AUX
cuesj-483	34	5	penalized	penalize	VERB
cuesj-483	34	6	based	base	VERB
cuesj-483	34	7	on	on	ADP
cuesj-483	34	8	its	its	PRON
cuesj-483	34	9	range	range	NOUN
cuesj-483	34	10	from	from	ADP
cuesj-483	34	11	the	the	DET
cuesj-483	34	12	centered	center	VERB
cuesj-483	34	13	location	location	NOUN
cuesj-483	34	14	,	,	PUNCT
cuesj-483	34	15	and	and	CCONJ
cuesj-483	34	16	the	the	DET
cuesj-483	34	17	degree	degree	NOUN
cuesj-483	34	18	of	of	ADP
cuesj-483	34	19	this	this	DET
cuesj-483	34	20	penalty	penalty	NOUN
cuesj-483	34	21	is	be	AUX
cuesj-483	34	22	defined	define	VERB
cuesj-483	34	23	by	by	ADP
cuesj-483	34	24	the	the	DET
cuesj-483	34	25	bandwidth.[8	bandwidth.[8	NOUN
cuesj-483	34	26	]	]	X
cuesj-483	34	27	a	a	DET
cuesj-483	34	28	narrow	narrow	ADJ
cuesj-483	34	29	(	(	PUNCT
cuesj-483	34	30	small	small	ADJ
cuesj-483	34	31	)	)	PUNCT
cuesj-483	34	32	bandwidth	bandwidth	NOUN
cuesj-483	34	33	of	of	ADP
cuesj-483	34	34	h	h	NOUN
cuesj-483	34	35	results	result	NOUN
cuesj-483	34	36	in	in	ADP
cuesj-483	34	37	a	a	DET
cuesj-483	34	38	wiggly	wiggly	ADJ
cuesj-483	34	39	curve	curve	NOUN
cuesj-483	34	40	and	and	CCONJ
cuesj-483	34	41	a	a	DET
cuesj-483	34	42	wealth	wealth	NOUN
cuesj-483	34	43	of	of	ADP
cuesj-483	34	44	noise	noise	NOUN
cuesj-483	34	45	in	in	ADP
cuesj-483	34	46	estimation	estimation	NOUN
cuesj-483	34	47	,	,	PUNCT
cuesj-483	34	48	whereas	whereas	SCONJ
cuesj-483	34	49	a	a	DET
cuesj-483	34	50	vast	vast	ADJ
cuesj-483	34	51	(	(	PUNCT
cuesj-483	34	52	big	big	ADJ
cuesj-483	34	53	)	)	PUNCT
cuesj-483	34	54	bandwidth	bandwidth	NOUN
cuesj-483	34	55	of	of	ADP
cuesj-483	34	56	h	h	NOUN
cuesj-483	34	57	results	result	NOUN
cuesj-483	34	58	in	in	ADP
cuesj-483	34	59	a	a	DET
cuesj-483	34	60	flat	flat	ADJ
cuesj-483	34	61	curve	curve	NOUN
cuesj-483	34	62	and	and	CCONJ
cuesj-483	34	63	over	over	ADV
cuesj-483	34	64	-	-	PUNCT
cuesj-483	34	65	smoothed	smooth	VERB
cuesj-483	34	66	curves	curve	NOUN
cuesj-483	34	67	in	in	ADP
cuesj-483	34	68	estimation	estimation	NOUN
cuesj-483	34	69	.	.	PUNCT
cuesj-483	35	1	one	one	NUM
cuesj-483	35	2	of	of	ADP
cuesj-483	35	3	the	the	DET
cuesj-483	35	4	assumptions	assumption	NOUN
cuesj-483	35	5	of	of	ADP
cuesj-483	35	6	kernel	kernel	PROPN
cuesj-483	35	7	density	density	PROPN
cuesj-483	35	8	function	function	NOUN
cuesj-483	35	9	is	be	AUX
cuesj-483	35	10	a	a	DET
cuesj-483	35	11	symmetric	symmetric	NOUN
cuesj-483	35	12	that	that	PRON
cuesj-483	35	13	is	be	AUX
cuesj-483	35	14	often	often	ADV
cuesj-483	35	15	applied	apply	VERB
cuesj-483	35	16	with	with	ADP
cuesj-483	35	17	a	a	DET
cuesj-483	35	18	standard	standard	ADJ
cuesj-483	35	19	normal	normal	ADJ
cuesj-483	35	20	density.[13	density.[13	PROPN
cuesj-483	35	21	]	]	PUNCT
cuesj-483	35	22	the	the	DET
cuesj-483	35	23	kernel	kernel	PROPN
cuesj-483	35	24	’s	’s	PART
cuesj-483	35	25	functions	function	NOUN
cuesj-483	35	26	of	of	ADP
cuesj-483	35	27	k	k	PROPN
cuesj-483	35	28	can	can	AUX
cuesj-483	35	29	be	be	AUX
cuesj-483	35	30	used	use	VERB
cuesj-483	35	31	to	to	ADP
cuesj-483	35	32	one	one	NUM
cuesj-483	35	33	of	of	ADP
cuesj-483	35	34	several	several	ADJ
cuesj-483	35	35	frequently	frequently	ADV
cuesj-483	35	36	used	use	VERB
cuesj-483	35	37	functions	function	NOUN
cuesj-483	35	38	,	,	PUNCT
cuesj-483	35	39	namely	namely	ADV
cuesj-483	35	40	epanechnikov	epanechnikov	NOUN
cuesj-483	35	41	,	,	PUNCT
cuesj-483	35	42	triangle	triangle	NOUN
cuesj-483	35	43	,	,	PUNCT
cuesj-483	35	44	quartic	quartic	ADJ
cuesj-483	35	45	,	,	PUNCT
cuesj-483	35	46	gaussian	gaussian	ADJ
cuesj-483	35	47	,	,	PUNCT
cuesj-483	35	48	uniform	uniform	ADJ
cuesj-483	35	49	,	,	PUNCT
cuesj-483	35	50	and	and	CCONJ
cuesj-483	35	51	tricube	tricube	NOUN
cuesj-483	35	52	(	(	PUNCT
cuesj-483	35	53	triweight).[3	triweight).[3	PROPN
cuesj-483	35	54	]	]	X
cuesj-483	35	55	gaussian	gaussian	NOUN
cuesj-483	35	56	is	be	AUX
cuesj-483	35	57	a	a	DET
cuesj-483	35	58	common	common	ADJ
cuesj-483	35	59	and	and	CCONJ
cuesj-483	35	60	practical	practical	ADJ
cuesj-483	35	61	kernel	kernel	NOUN
cuesj-483	35	62	density	density	NOUN
cuesj-483	35	63	function[2	function[2	PROPN
cuesj-483	35	64	]	]	PUNCT
cuesj-483	35	65	which	which	PRON
cuesj-483	35	66	is	be	AUX
cuesj-483	35	67	used	use	VERB
cuesj-483	35	68	in	in	ADP
cuesj-483	35	69	this	this	DET
cuesj-483	35	70	paper	paper	NOUN
cuesj-483	35	71	as	as	SCONJ
cuesj-483	35	72	shown	show	VERB
cuesj-483	35	73	below	below	ADP
cuesj-483	35	74	.	.	PUNCT
cuesj-483	36	1	k	k	X
cuesj-483	36	2	u	u	X
cuesj-483	36	3	e	e	PROPN
cuesj-483	36	4	uu	uu	PRON
cuesj-483	36	5	�	�	PROPN
cuesj-483	36	6	�	�	PROPN
cuesj-483	36	7	�	�	PROPN
cuesj-483	36	8	�	�	PROPN
cuesj-483	36	9	�	�	PROPN
cuesj-483	36	10	�	�	PROPN
cuesj-483	36	11	�	�	PROPN
cuesj-483	36	12	�	�	PROPN
cuesj-483	36	13	�	�	PROPN
cuesj-483	36	14	�	�	PROPN
cuesj-483	36	15	1	1	NUM
cuesj-483	36	16	2	2	NUM
cuesj-483	36	17	2	2	NUM
cuesj-483	36	18	2	2	NUM
cuesj-483	36	19	�	�	PROPN
cuesj-483	36	20	/	/	PUNCT
cuesj-483	36	21	;	;	PUNCT
cuesj-483	36	22	,	,	PUNCT
cuesj-483	36	23	(	(	PUNCT
cuesj-483	36	24	7	7	NUM
cuesj-483	36	25	)	)	PUNCT
cuesj-483	36	26	(	(	PUNCT
cuesj-483	36	27	)	)	PUNCT
cuesj-483	36	28	2	2	NUM
cuesj-483	36	29	1	1	NUM
cuesj-483	36	30	2	2	NUM
cuesj-483	36	31	1	1	NUM
cuesj-483	36	32	1	1	NUM
cuesj-483	36	33	1	1	NUM
cuesj-483	36	34	22ˆ	22ˆ	NUM
cuesj-483	36	35	1	1	NUM
cuesj-483	36	36	1	1	NUM
cuesj-483	36	37	22	22	NUM
cuesj-483	36	38	π	π	NOUN
cuesj-483	36	39	π	π	X
cuesj-483	36	40	=	=	PUNCT
cuesj-483	37	1	=	=	SYM
cuesj-483	38	1	−	−	VERB
cuesj-483	38	2	−	−	NOUN
cuesj-483	38	3			NOUN
cuesj-483	38	4			NOUN
cuesj-483	38	5			NOUN
cuesj-483	38	6	=	=	VERB
cuesj-483	38	7	−	−	ADJ
cuesj-483	38	8	−	−	NOUN
cuesj-483	38	9			NOUN
cuesj-483	38	10			VERB
cuesj-483	38	11			PRON
cuesj-483	38	12			PUNCT
cuesj-483	39	1	∑	∑	PUNCT
cuesj-483	39	2	∑	∑	PROPN
cuesj-483	39	3	n	n	PROPN
cuesj-483	39	4	i	i	NOUN
cuesj-483	39	5	ii	ii	NOUN
cuesj-483	39	6	h	h	NOUN
cuesj-483	40	1	n	n	CCONJ
cuesj-483	40	2	i	i	PRON
cuesj-483	41	1	i	i	INTJ
cuesj-483	41	2	x	x	PROPN
cuesj-483	41	3	xexp	xexp	PROPN
cuesj-483	41	4	y	y	PROPN
cuesj-483	41	5	hf	hf	NOUN
cuesj-483	41	6	x	x	PUNCT
cuesj-483	42	1	x	x	SYM
cuesj-483	42	2	xexp	xexp	PROPN
cuesj-483	42	3	h	h	PROPN
cuesj-483	42	4	(	(	PUNCT
cuesj-483	42	5	8)	8)	NUM
cuesj-483	42	6	if	if	SCONJ
cuesj-483	42	7	you	you	PRON
cuesj-483	42	8	already	already	ADV
cuesj-483	42	9	have	have	VERB
cuesj-483	42	10	over	over	ADP
cuesj-483	42	11	one	one	NUM
cuesj-483	42	12	predictive	predictive	ADJ
cuesj-483	42	13	variable	variable	NOUN
cuesj-483	42	14	,	,	PUNCT
cuesj-483	42	15	lengthy	lengthy	ADJ
cuesj-483	42	16	distributions	distribution	NOUN
cuesj-483	42	17	,	,	PUNCT
cuesj-483	42	18	or	or	CCONJ
cuesj-483	42	19	multi	multi	ADJ
cuesj-483	42	20	modal	modal	ADJ
cuesj-483	42	21	distributions	distribution	NOUN
cuesj-483	42	22	,	,	PUNCT
cuesj-483	42	23	fixed	fix	VERB
cuesj-483	42	24	nadaraya	nadaraya	PROPN
cuesj-483	42	25	watson	watson	PROPN
cuesj-483	42	26	(	(	PUNCT
cuesj-483	42	27	fnw	fnw	PROPN
cuesj-483	42	28	)	)	PUNCT
cuesj-483	42	29	is	be	AUX
cuesj-483	42	30	not	not	PART
cuesj-483	42	31	always	always	ADV
cuesj-483	42	32	the	the	DET
cuesj-483	42	33	best	good	ADJ
cuesj-483	42	34	option.[9	option.[9	NUM
cuesj-483	42	35	]	]	PUNCT
cuesj-483	42	36	in	in	ADP
cuesj-483	42	37	this	this	DET
cuesj-483	42	38	situation	situation	NOUN
cuesj-483	42	39	,	,	PUNCT
cuesj-483	42	40	we	we	PRON
cuesj-483	42	41	can	can	AUX
cuesj-483	42	42	use	use	VERB
cuesj-483	42	43	the	the	DET
cuesj-483	42	44	variable	variable	ADJ
cuesj-483	42	45	nadaraya	nadaraya	PROPN
cuesj-483	42	46	-	-	PUNCT
cuesj-483	42	47	watson	watson	NOUN
cuesj-483	42	48	kernel	kernel	PROPN
cuesj-483	42	49	(	(	PUNCT
cuesj-483	42	50	vnwk	vnwk	NOUN
cuesj-483	42	51	)	)	PUNCT
cuesj-483	42	52	estimator	estimator	NOUN
cuesj-483	42	53	with	with	ADP
cuesj-483	42	54	a	a	DET
cuesj-483	42	55	variable	variable	ADJ
cuesj-483	42	56	bandwidth	bandwidth	NOUN
cuesj-483	42	57	i(xi	i(xi	PROPN
cuesj-483	42	58	)	)	PUNCT
cuesj-483	42	59	as	as	SCONJ
cuesj-483	42	60	seen	see	VERB
cuesj-483	42	61	below	below	ADV
cuesj-483	42	62	:	:	PUNCT
cuesj-483	42	63	(	(	PUNCT
cuesj-483	42	64	)	)	PUNCT
cuesj-483	42	65	1	1	NUM
cuesj-483	42	66	1	1	NUM
cuesj-483	42	67	(	(	PUNCT
cuesj-483	42	68	)	)	PUNCT
cuesj-483	42	69	(	(	PUNCT
cuesj-483	42	70	)	)	PUNCT
cuesj-483	42	71	1	1	NUM
cuesj-483	42	72	(	(	PUNCT
cuesj-483	42	73	(	(	PUNCT
cuesj-483	42	74	)	)	PUNCT
cuesj-483	42	75	ˆ	ˆ	X
cuesj-483	42	76	)	)	PUNCT
cuesj-483	42	77	=	=	SYM
cuesj-483	43	1	=	=	SYM
cuesj-483	43	2			NOUN
cuesj-483	43	3	−	−	VERB
cuesj-483	43	4			NOUN
cuesj-483	43	5			NOUN
cuesj-483	43	6			NOUN
cuesj-483	43	7	=	=	VERB
cuesj-483	43	8			PROPN
cuesj-483	43	9	−	−	ADJ
cuesj-483	43	10			NOUN
cuesj-483	43	11			VERB
cuesj-483	43	12			PRON
cuesj-483	43	13			PUNCT
cuesj-483	43	14	∑	∑	PUNCT
cuesj-483	43	15	∑	∑	PROPN
cuesj-483	43	16	n	n	PROPN
cuesj-483	44	1	i	i	PRON
cuesj-483	45	1	i	i	PRON
cuesj-483	46	1	i	i	PRON
cuesj-483	47	1	i	i	PRON
cuesj-483	48	1	i	i	PRON
cuesj-483	48	2	vnw	vnw	VERB
cuesj-483	48	3	n	n	PRON
cuesj-483	49	1	i	i	PRON
cuesj-483	49	2	i	i	PRON
cuesj-483	50	1	i	i	PRON
cuesj-483	50	2	i	i	VERB
cuesj-483	50	3	x	x	VERB
cuesj-483	51	1	x	x	VERB
cuesj-483	51	2	yk	yk	NOUN
cuesj-483	51	3	h	h	NOUN
cuesj-483	52	1	x	x	NOUN
cuesj-483	52	2	h	h	NOUN
cuesj-483	52	3	x	x	X
cuesj-483	52	4	f	f	NOUN
cuesj-483	52	5	x	x	X
cuesj-483	52	6	x	x	PUNCT
cuesj-483	52	7	xk	xk	PROPN
cuesj-483	52	8	h	h	PROPN
cuesj-483	53	1	x	x	PROPN
cuesj-483	53	2	h	h	NOUN
cuesj-483	53	3	x	x	X
cuesj-483	53	4	(	(	PUNCT
cuesj-483	53	5	9	9	NUM
cuesj-483	53	6	)	)	PUNCT
cuesj-483	54	1	[	[	X
cuesj-483	54	2	14	14	NUM
cuesj-483	54	3	]	]	PUNCT
cuesj-483	54	4	showed	show	VERB
cuesj-483	54	5	a	a	DET
cuesj-483	54	6	formula	formula	NOUN
cuesj-483	54	7	to	to	PART
cuesj-483	54	8	compute	compute	VERB
cuesj-483	54	9	h(xi	h(xi	NOUN
cuesj-483	54	10	)	)	PUNCT
cuesj-483	54	11	in	in	ADP
cuesj-483	54	12	1982	1982	NUM
cuesj-483	54	13	,	,	PUNCT
cuesj-483	54	14	h	h	NOUN
cuesj-483	55	1	x	x	PUNCT
cuesj-483	55	2	h	h	NOUN
cuesj-483	56	1	f	f	X
cuesj-483	56	2	xi	xi	INTJ
cuesj-483	56	3	i	i	PROPN
cuesj-483	56	4	�	�	PROPN
cuesj-483	56	5	�	�	PROPN
cuesj-483	56	6	�	�	PROPN
cuesj-483	56	7	(	(	PUNCT
cuesj-483	56	8	)	)	PUNCT
cuesj-483	56	9	(	(	PUNCT
cuesj-483	56	10	10	10	NUM
cuesj-483	56	11	)	)	PUNCT
cuesj-483	56	12	while	while	SCONJ
cuesj-483	56	13	f(xi	f(xi	NOUN
cuesj-483	56	14	)	)	PUNCT
cuesj-483	56	15	is	be	AUX
cuesj-483	56	16	determined	determine	VERB
cuesj-483	56	17	by	by	ADP
cuesj-483	56	18	the	the	DET
cuesj-483	56	19	kernel	kernel	PROPN
cuesj-483	56	20	function	function	PROPN
cuesj-483	56	21	estimator	estimator	NOUN
cuesj-483	56	22	which	which	PRON
cuesj-483	56	23	is	be	AUX
cuesj-483	56	24	a	a	DET
cuesj-483	56	25	probability	probability	NOUN
cuesj-483	56	26	density	density	NOUN
cuesj-483	56	27	function	function	NOUN
cuesj-483	56	28	of	of	ADP
cuesj-483	56	29	xi	xi	PROPN
cuesj-483	56	30	.	.	PUNCT
cuesj-483	57	1	a	a	DET
cuesj-483	57	2	new	new	ADJ
cuesj-483	57	3	algorithm	algorithm	NOUN
cuesj-483	57	4	developed	develop	VERB
cuesj-483	57	5	for	for	ADP
cuesj-483	57	6	the	the	DET
cuesj-483	57	7	abramson	abramson	PROPN
cuesj-483	57	8	design	design	NOUN
cuesj-483	57	9	estimator	estimator	NOUN
cuesj-483	57	10	by	by	ADP
cuesj-483	57	11	silverman	silverman	NOUN
cuesj-483	57	12	in	in	ADP
cuesj-483	57	13	1986	1986	NUM
cuesj-483	57	14	,	,	PUNCT
cuesj-483	57	15	which	which	PRON
cuesj-483	57	16	he	he	PRON
cuesj-483	57	17	called	call	VERB
cuesj-483	57	18	an	an	DET
cuesj-483	57	19	aadaptive	aadaptive	ADJ
cuesj-483	57	20	nwk	nwk	NOUN
cuesj-483	57	21	(	(	PUNCT
cuesj-483	57	22	anwk	anwk	NOUN
cuesj-483	57	23	)	)	PUNCT
cuesj-483	57	24	function	function	NOUN
cuesj-483	57	25	estimator	estimator	NOUN
cuesj-483	57	26	.	.	PUNCT
cuesj-483	58	1	for	for	ADP
cuesj-483	58	2	a	a	DET
cuesj-483	58	3	fixed	fixed	ADJ
cuesj-483	58	4	h	h	NOUN
cuesj-483	58	5	,	,	PUNCT
cuesj-483	58	6	the	the	DET
cuesj-483	58	7	previous	previous	ADJ
cuesj-483	58	8	kernel	kernel	PROPN
cuesj-483	58	9	function	function	PROPN
cuesj-483	58	10	estimator	estimator	NOUN
cuesj-483	58	11	was	be	AUX
cuesj-483	58	12	used	use	VERB
cuesj-483	58	13	as	as	ADP
cuesj-483	58	14	a	a	DET
cuesj-483	58	15	first	first	ADJ
cuesj-483	58	16	stage,[4	stage,[4	NOUN
cuesj-483	58	17	]	]	PUNCT
cuesj-483	58	18	which	which	PRON
cuesj-483	58	19	is	be	AUX
cuesj-483	58	20	represented	represent	VERB
cuesj-483	58	21	by	by	ADP
cuesj-483	58	22	(	(	PUNCT
cuesj-483	58	23	)	)	PUNCT
cuesj-483	58	24	ˆ	ˆ	NOUN
cuesj-483	58	25	if	if	SCONJ
cuesj-483	58	26	x	x	PROPN
cuesj-483	58	27	and	and	CCONJ
cuesj-483	58	28	he	he	PRON
cuesj-483	58	29	established	establish	VERB
cuesj-483	58	30	local	local	ADJ
cuesj-483	58	31	h	h	NOUN
cuesj-483	58	32	factor	factor	NOUN
cuesj-483	58	33	θi	θi	ADP
cuesj-483	58	34	as	as	ADP
cuesj-483	58	35	:	:	PUNCT
cuesj-483	58	36	ˆ	ˆ	X
cuesj-483	58	37	(	(	PUNCT
cuesj-483	58	38	)	)	PUNCT
cuesj-483	58	39	α	α	NUM
cuesj-483	58	40	θ	θ	NOUN
cuesj-483	58	41	−	−	PROPN
cuesj-483	58	42			NOUN
cuesj-483	58	43			NUM
cuesj-483	58	44	=	=	SYM
cuesj-483	58	45			ADJ
cuesj-483	58	46			PROPN
cuesj-483	58	47			ADJ
cuesj-483	58	48			ADJ
cuesj-483	58	49			NOUN
cuesj-483	58	50	i	i	PRON
cuesj-483	58	51	i	i	PRON
cuesj-483	59	1	g	g	NOUN
cuesj-483	59	2	f	f	NOUN
cuesj-483	59	3	x	x	PROPN
cuesj-483	59	4	g	g	PROPN
cuesj-483	59	5	(	(	PUNCT
cuesj-483	59	6	11	11	NUM
cuesj-483	59	7	)	)	PUNCT
cuesj-483	59	8	while	while	SCONJ
cuesj-483	59	9	g	g	NOUN
cuesj-483	59	10	represents	represent	VERB
cuesj-483	59	11	the	the	DET
cuesj-483	59	12	geometric	geometric	ADJ
cuesj-483	59	13	mean	mean	NOUN
cuesj-483	59	14	of	of	ADP
cuesj-483	59	15	ˆ	ˆ	NOUN
cuesj-483	59	16	)	)	PUNCT
cuesj-483	59	17	(	(	PUNCT
cuesj-483	59	18	if	if	SCONJ
cuesj-483	59	19	x	x	PUNCT
cuesj-483	59	20	with	with	ADP
cuesj-483	59	21	g≠0	g≠0	PROPN
cuesj-483	59	22	and	and	CCONJ
cuesj-483	59	23	a	a	DET
cuesj-483	59	24	illustrates	illustrate	VERB
cuesj-483	59	25	the	the	DET
cuesj-483	59	26	sensitivity	sensitivity	NOUN
cuesj-483	59	27	parameter	parameter	NOUN
cuesj-483	59	28	between	between	ADP
cuesj-483	59	29	0	0	NUM
cuesj-483	59	30	and	and	CCONJ
cuesj-483	59	31	1	1	NUM
cuesj-483	59	32	(	(	PUNCT
cuesj-483	59	33	0≤α≤1).[14	0≤α≤1).[14	PROPN
cuesj-483	59	34	]	]	PUNCT
cuesj-483	59	35	selected	select	VERB
cuesj-483	59	36	the	the	DET
cuesj-483	59	37	value	value	NOUN
cuesj-483	59	38	of	of	ADP
cuesj-483	59	39	α=0.5	α=0.5	NOUN
cuesj-483	59	40	because	because	SCONJ
cuesj-483	59	41	its	its	PRON
cuesj-483	59	42	gives	give	VERB
cuesj-483	59	43	an	an	DET
cuesj-483	59	44	accurate	accurate	ADJ
cuesj-483	59	45	predictive	predictive	ADJ
cuesj-483	59	46	results	result	NOUN
cuesj-483	59	47	.	.	PUNCT
cuesj-483	60	1	moreover	moreover	ADV
cuesj-483	60	2	then	then	ADV
cuesj-483	60	3	,	,	PUNCT
cuesj-483	60	4	silverman	silverman	NOUN
cuesj-483	60	5	provided	provide	VERB
cuesj-483	60	6	an	an	DET
cuesj-483	60	7	adaptive	adaptive	ADJ
cuesj-483	60	8	h	h	NOUN
cuesj-483	60	9	as	as	SCONJ
cuesj-483	60	10	seen	see	VERB
cuesj-483	60	11	below	below	ADV
cuesj-483	60	12	:	:	PUNCT
cuesj-483	60	13	h	h	NOUN
cuesj-483	60	14	x	x	INTJ
cuesj-483	60	15	hi	hi	INTJ
cuesj-483	60	16	gi	gi	INTJ
cuesj-483	60	17	�	�	PROPN
cuesj-483	60	18	�	�	PROPN
cuesj-483	60	19	�	�	PROPN
cuesj-483	60	20	�	�	PROPN
cuesj-483	60	21	(	(	PUNCT
cuesj-483	60	22	12	12	NUM
cuesj-483	60	23	)	)	PUNCT
cuesj-483	60	24	in	in	ADP
cuesj-483	60	25	2010,[15	2010,[15	NUM
cuesj-483	60	26	]	]	X
cuesj-483	60	27	it	it	PRON
cuesj-483	60	28	is	be	AUX
cuesj-483	60	29	introduced	introduce	VERB
cuesj-483	60	30	a	a	DET
cuesj-483	60	31	change	change	NOUN
cuesj-483	60	32	to	to	ADP
cuesj-483	60	33	the	the	DET
cuesj-483	60	34	anw	anw	PROPN
cuesj-483	60	35	approach	approach	NOUN
cuesj-483	60	36	that	that	SCONJ
cuesj-483	60	37	they	they	PRON
cuesj-483	60	38	have	have	AUX
cuesj-483	60	39	used	use	VERB
cuesj-483	60	40	arithmetic	arithmetic	ADJ
cuesj-483	60	41	mean	mean	NOUN
cuesj-483	60	42	x	x	SYM
cuesj-483	60	43	of	of	ADP
cuesj-483	60	44	(	(	PUNCT
cuesj-483	60	45	)	)	PUNCT
cuesj-483	60	46	ˆ	ˆ	NOUN
cuesj-483	60	47	if	if	SCONJ
cuesj-483	60	48	x	x	PRON
cuesj-483	60	49	instead	instead	ADV
cuesj-483	60	50	of	of	ADP
cuesj-483	60	51	using	use	VERB
cuesj-483	60	52	g	g	NOUN
cuesj-483	60	53	for	for	ADP
cuesj-483	60	54	figuring	figure	VERB
cuesj-483	60	55	out	out	ADP
cuesj-483	60	56	the	the	DET
cuesj-483	60	57	h	h	NOUN
cuesj-483	60	58	factor	factor	NOUN
cuesj-483	60	59	in	in	ADP
cuesj-483	60	60	nwk	nwk	NOUN
cuesj-483	60	61	estimator	estimator	NOUN
cuesj-483	60	62	.	.	PUNCT
cuesj-483	61	1	ˆ	ˆ	X
cuesj-483	61	2	(	(	PUNCT
cuesj-483	61	3	)	)	PUNCT
cuesj-483	61	4	α	α	NUM
cuesj-483	61	5	θ	θ	NOUN
cuesj-483	61	6	−	−	PROPN
cuesj-483	61	7			NOUN
cuesj-483	61	8			NUM
cuesj-483	61	9	=	=	SYM
cuesj-483	61	10			ADJ
cuesj-483	61	11			PROPN
cuesj-483	61	12			ADJ
cuesj-483	61	13			ADJ
cuesj-483	61	14			NOUN
cuesj-483	61	15	i	i	PRON
cuesj-483	61	16	i	i	NOUN
cuesj-483	61	17	x	x	X
cuesj-483	61	18	f	f	NOUN
cuesj-483	61	19	x	x	SYM
cuesj-483	61	20	x	x	X
cuesj-483	61	21	(	(	PUNCT
cuesj-483	61	22	13	13	NUM
cuesj-483	61	23	)	)	PUNCT
cuesj-483	61	24	in	in	ADP
cuesj-483	61	25	2014,[7	2014,[7	NUM
cuesj-483	61	26	]	]	PUNCT
cuesj-483	61	27	it	it	PRON
cuesj-483	61	28	modified	modify	VERB
cuesj-483	61	29	the	the	DET
cuesj-483	61	30	anw	anw	PROPN
cuesj-483	61	31	approach	approach	NOUN
cuesj-483	61	32	that	that	SCONJ
cuesj-483	61	33	they	they	PRON
cuesj-483	61	34	have	have	AUX
cuesj-483	61	35	used	use	VERB
cuesj-483	61	36	range	range	NOUN
cuesj-483	61	37	r	r	NOUN
cuesj-483	61	38	of	of	ADP
cuesj-483	61	39	(	(	PUNCT
cuesj-483	61	40	)	)	PUNCT
cuesj-483	61	41	ˆ	ˆ	NOUN
cuesj-483	61	42	if	if	SCONJ
cuesj-483	61	43	x	x	PRON
cuesj-483	61	44	instead	instead	ADV
cuesj-483	61	45	of	of	ADP
cuesj-483	61	46	using	use	VERB
cuesj-483	61	47	g	g	PROPN
cuesj-483	61	48	or	or	CCONJ
cuesj-483	61	49	x	x	X
cuesj-483	61	50	for	for	ADP
cuesj-483	61	51	figuring	figure	VERB
cuesj-483	61	52	out	out	ADP
cuesj-483	61	53	the	the	DET
cuesj-483	61	54	h	h	NOUN
cuesj-483	61	55	factor	factor	NOUN
cuesj-483	61	56	in	in	ADP
cuesj-483	61	57	nwk	nwk	NOUN
cuesj-483	61	58	estimator	estimator	NOUN
cuesj-483	61	59	.	.	PUNCT
cuesj-483	62	1	ˆ	ˆ	X
cuesj-483	62	2	(	(	PUNCT
cuesj-483	62	3	)	)	PUNCT
cuesj-483	62	4	α	α	NUM
cuesj-483	62	5	θ	θ	NOUN
cuesj-483	62	6	−	−	PROPN
cuesj-483	62	7			NOUN
cuesj-483	62	8			NUM
cuesj-483	62	9	=	=	SYM
cuesj-483	62	10			ADJ
cuesj-483	62	11			PROPN
cuesj-483	62	12			ADJ
cuesj-483	62	13			ADJ
cuesj-483	62	14			NOUN
cuesj-483	62	15	i	i	PRON
cuesj-483	62	16	i	i	NOUN
cuesj-483	62	17	r	r	NOUN
cuesj-483	62	18	f	f	NOUN
cuesj-483	62	19	x	x	SYM
cuesj-483	62	20	r	r	NOUN
cuesj-483	62	21	(	(	PUNCT
cuesj-483	62	22	14	14	NUM
cuesj-483	62	23	)	)	PUNCT
cuesj-483	62	24	in	in	ADP
cuesj-483	62	25	2019,[16	2019,[16	NUM
cuesj-483	62	26	]	]	PUNCT
cuesj-483	63	1	it	it	PRON
cuesj-483	63	2	proposed	propose	VERB
cuesj-483	63	3	another	another	DET
cuesj-483	63	4	change	change	NOUN
cuesj-483	63	5	for	for	ADP
cuesj-483	63	6	the	the	DET
cuesj-483	63	7	anw	anw	PROPN
cuesj-483	63	8	approach	approach	NOUN
cuesj-483	63	9	that	that	PRON
cuesj-483	63	10	he	he	PRON
cuesj-483	63	11	used	use	VERB
cuesj-483	63	12	median	median	NOUN
cuesj-483	63	13	instead	instead	ADV
cuesj-483	63	14	of	of	ADP
cuesj-483	63	15	using	use	VERB
cuesj-483	63	16	geometric	geometric	ADJ
cuesj-483	63	17	,	,	PUNCT
cuesj-483	63	18	mean	mean	ADJ
cuesj-483	63	19	,	,	PUNCT
cuesj-483	63	20	or	or	CCONJ
cuesj-483	63	21	range	range	VERB
cuesj-483	63	22	for	for	ADP
cuesj-483	63	23	calculating	calculate	VERB
cuesj-483	63	24	the	the	DET
cuesj-483	63	25	h	h	NOUN
cuesj-483	63	26	factor	factor	NOUN
cuesj-483	63	27	in	in	ADP
cuesj-483	63	28	nwk	nwk	NOUN
cuesj-483	63	29	estimator	estimator	NOUN
cuesj-483	63	30	.	.	PUNCT
cuesj-483	64	1	(	(	PUNCT
cuesj-483	64	2	)	)	PUNCT
cuesj-483	64	3	ˆ	ˆ	NOUN
cuesj-483	64	4	α	α	NUM
cuesj-483	64	5	θ	θ	NOUN
cuesj-483	64	6	−	−	PROPN
cuesj-483	64	7			NOUN
cuesj-483	64	8			NUM
cuesj-483	64	9	=	=	SYM
cuesj-483	64	10			ADJ
cuesj-483	64	11			PROPN
cuesj-483	64	12			ADJ
cuesj-483	64	13			ADJ
cuesj-483	64	14			NOUN
cuesj-483	64	15	i	i	PRON
cuesj-483	64	16	i	i	PRON
cuesj-483	64	17	me	i	PRON
cuesj-483	64	18	f	f	NOUN
cuesj-483	64	19	x	x	VERB
cuesj-483	64	20	me	i	PRON
cuesj-483	64	21	(	(	PUNCT
cuesj-483	64	22	15	15	NUM
cuesj-483	64	23	)	)	PUNCT
cuesj-483	64	24	new	new	ADJ
cuesj-483	64	25	proposed	propose	VERB
cuesj-483	64	26	nwk	nwk	NOUN
cuesj-483	64	27	function	function	NOUN
cuesj-483	64	28	estimator	estimator	NOUN
cuesj-483	64	29	in	in	ADP
cuesj-483	64	30	this	this	DET
cuesj-483	64	31	study	study	NOUN
cuesj-483	64	32	,	,	PUNCT
cuesj-483	64	33	a	a	DET
cuesj-483	64	34	new	new	ADJ
cuesj-483	64	35	changes	change	NOUN
cuesj-483	64	36	for	for	ADP
cuesj-483	64	37	the	the	DET
cuesj-483	64	38	adaptive	adaptive	ADJ
cuesj-483	64	39	nadarayawatson	nadarayawatson	NOUN
cuesj-483	64	40	approach	approach	NOUN
cuesj-483	64	41	was	be	AUX
cuesj-483	64	42	proposed	propose	VERB
cuesj-483	64	43	,	,	PUNCT
cuesj-483	64	44	which	which	PRON
cuesj-483	64	45	used	use	VERB
cuesj-483	64	46	four	four	NUM
cuesj-483	64	47	different	different	ADJ
cuesj-483	64	48	statistical	statistical	ADJ
cuesj-483	64	49	techniques	technique	NOUN
cuesj-483	64	50	such	such	ADJ
cuesj-483	64	51	as	as	ADP
cuesj-483	64	52	interquartile	interquartile	ADJ
cuesj-483	64	53	range	range	NOUN
cuesj-483	64	54	(	(	PUNCT
cuesj-483	64	55	iqr	iqr	NOUN
cuesj-483	64	56	)	)	PUNCT
cuesj-483	64	57	,	,	PUNCT
cuesj-483	64	58	standard	standard	ADJ
cuesj-483	64	59	deviation	deviation	NOUN
cuesj-483	64	60	(	(	PUNCT
cuesj-483	64	61	sd	sd	NOUN
cuesj-483	64	62	)	)	PUNCT
cuesj-483	64	63	,	,	PUNCT
cuesj-483	64	64	mean	mean	VERB
cuesj-483	64	65	absolute	absolute	ADJ
cuesj-483	64	66	deviation	deviation	NOUN
cuesj-483	64	67	(	(	PUNCT
cuesj-483	64	68	mad	mad	ADJ
cuesj-483	64	69	)	)	PUNCT
cuesj-483	64	70	,	,	PUNCT
cuesj-483	64	71	and	and	CCONJ
cuesj-483	64	72	median	median	ADJ
cuesj-483	64	73	absolute	absolute	ADJ
cuesj-483	64	74	deviation	deviation	NOUN
cuesj-483	64	75	(	(	PUNCT
cuesj-483	64	76	mead	mead	NOUN
cuesj-483	64	77	)	)	PUNCT
cuesj-483	64	78	of	of	ADP
cuesj-483	64	79	(	(	PUNCT
cuesj-483	64	80	)	)	PUNCT
cuesj-483	64	81	ˆ	ˆ	NOUN
cuesj-483	64	82	if	if	SCONJ
cuesj-483	64	83	x	x	PRON
cuesj-483	64	84	instead	instead	ADV
cuesj-483	64	85	of	of	ADP
cuesj-483	64	86	using	use	VERB
cuesj-483	64	87	geometric	geometric	ADJ
cuesj-483	64	88	mean	mean	NOUN
cuesj-483	64	89	,	,	PUNCT
cuesj-483	64	90	arithmetic	arithmetic	ADJ
cuesj-483	64	91	mean	mean	NOUN
cuesj-483	64	92	,	,	PUNCT
cuesj-483	64	93	range	range	NOUN
cuesj-483	64	94	,	,	PUNCT
cuesj-483	64	95	or	or	CCONJ
cuesj-483	64	96	median	median	NOUN
cuesj-483	64	97	for	for	ADP
cuesj-483	64	98	figuring	figure	VERB
cuesj-483	64	99	out	out	ADP
cuesj-483	64	100	the	the	DET
cuesj-483	64	101	h	h	NOUN
cuesj-483	64	102	factor	factor	NOUN
cuesj-483	64	103	in	in	ADP
cuesj-483	64	104	nwk	nwk	NOUN
cuesj-483	64	105	estimator	estimator	NOUN
cuesj-483	64	106	.	.	PUNCT
cuesj-483	65	1	blbas	blbas	PROPN
cuesj-483	65	2	and	and	CCONJ
cuesj-483	65	3	kahwachi	kahwachi	PROPN
cuesj-483	65	4	:	:	PUNCT
cuesj-483	65	5	new	new	ADJ
cuesj-483	65	6	modification	modification	NOUN
cuesj-483	65	7	of	of	ADP
cuesj-483	65	8	anwk	anwk	NOUN
cuesj-483	65	9	in	in	ADP
cuesj-483	65	10	nonparametric	nonparametric	PROPN
cuesj-483	65	11	regression	regression	NOUN
cuesj-483	65	12	34	34	NUM
cuesj-483	65	13	http://journals.cihanuniversity.edu.iq/index.php/cuesj	http://journals.cihanuniversity.edu.iq/index.php/cuesj	ADJ
cuesj-483	65	14	cuesj	cuesj	ADJ
cuesj-483	65	15	2021	2021	NUM
cuesj-483	65	16	,	,	PUNCT
cuesj-483	65	17	5	5	NUM
cuesj-483	65	18	(	(	PUNCT
cuesj-483	65	19	2	2	NUM
cuesj-483	65	20	):	):	PUNCT
cuesj-483	65	21	32	32	NUM
cuesj-483	65	22	-	-	SYM
cuesj-483	65	23	37	37	NUM
cuesj-483	65	24	ˆ	ˆ	NOUN
cuesj-483	65	25	ˆ	ˆ	NOUN
cuesj-483	65	26	ˆ	ˆ	NOUN
cuesj-483	65	27	ˆ	ˆ	ADV
cuesj-483	65	28	(	(	PUNCT
cuesj-483	65	29	)	)	PUNCT
cuesj-483	65	30	(	(	PUNCT
cuesj-483	65	31	)	)	PUNCT
cuesj-483	65	32	(	(	PUNCT
cuesj-483	65	33	)	)	PUNCT
cuesj-483	65	34	(	(	PUNCT
cuesj-483	65	35	)	)	PUNCT
cuesj-483	66	1	α	α	NOUN
cuesj-483	66	2	α	α	NOUN
cuesj-483	66	3	α	α	NOUN
cuesj-483	66	4	α	α	NOUN
cuesj-483	66	5	θ	θ	NOUN
cuesj-483	66	6	−	−	NOUN
cuesj-483	66	7	−	−	NOUN
cuesj-483	67	1	−	−	NOUN
cuesj-483	67	2	−	−	NOUN
cuesj-483	67	3			NOUN
cuesj-483	67	4			VERB
cuesj-483	67	5			PROPN
cuesj-483	67	6			ADJ
cuesj-483	67	7			ADJ
cuesj-483	67	8			PROPN
cuesj-483	67	9			ADJ
cuesj-483	67	10			ADJ
cuesj-483	67	11			NOUN
cuesj-483	67	12			NOUN
cuesj-483	67	13			ADJ
cuesj-483	67	14			NOUN
cuesj-483	67	15			PROPN
cuesj-483	67	16			ADJ
cuesj-483	67	17			ADJ
cuesj-483	67	18			PROPN
cuesj-483	67	19			ADJ
cuesj-483	67	20			ADJ
cuesj-483	67	21			ADJ
cuesj-483	67	22			NOUN
cuesj-483	67	23			ADJ
cuesj-483	67	24			ADJ
cuesj-483	67	25			NOUN
cuesj-483	67	26	=	=	ADJ
cuesj-483	67	27			ADJ
cuesj-483	67	28			NOUN
cuesj-483	67	29			ADJ
cuesj-483	67	30			VERB
cuesj-483	67	31			SYM
cuesj-483	67	32			NOUN
cuesj-483	67	33			ADJ
cuesj-483	67	34			NOUN
cuesj-483	67	35			PUNCT
cuesj-483	67	36			ADJ
cuesj-483	67	37			VERB
cuesj-483	67	38			ADJ
cuesj-483	67	39			ADJ
cuesj-483	67	40			NOUN
cuesj-483	67	41			X
cuesj-483	67	42			PROPN
cuesj-483	67	43			PROPN
cuesj-483	67	44			NOUN
cuesj-483	68	1	i	i	PRON
cuesj-483	69	1	i	i	PRON
cuesj-483	70	1	i	i	PRON
cuesj-483	71	1	i	i	PRON
cuesj-483	71	2	p	p	VERB
cuesj-483	72	1	i	i	PRON
cuesj-483	72	2	f	f	PROPN
cuesj-483	72	3	x	x	X
cuesj-483	72	4	iqr	iqr	PROPN
cuesj-483	73	1	f	f	NOUN
cuesj-483	73	2	x	x	PROPN
cuesj-483	73	3	sd	sd	ADP
cuesj-483	73	4	f	f	PROPN
cuesj-483	73	5	x	x	PROPN
cuesj-483	73	6	mad	mad	ADJ
cuesj-483	73	7	f	f	X
cuesj-483	73	8	x	x	X
cuesj-483	73	9	mead	mead	NOUN
cuesj-483	73	10	(	(	PUNCT
cuesj-483	73	11	16	16	NUM
cuesj-483	73	12	)	)	PUNCT
cuesj-483	73	13	where	where	SCONJ
cuesj-483	73	14	iqr	iqr	PROPN
cuesj-483	73	15	is	be	AUX
cuesj-483	73	16	an	an	DET
cuesj-483	73	17	abbreviation	abbreviation	NOUN
cuesj-483	73	18	for	for	ADP
cuesj-483	73	19	iqr	iqr	PROPN
cuesj-483	73	20	,	,	PUNCT
cuesj-483	73	21	sd	sd	PROPN
cuesj-483	73	22	represents	represent	VERB
cuesj-483	73	23	sd	sd	NOUN
cuesj-483	73	24	,	,	PUNCT
cuesj-483	73	25	mad	mad	ADJ
cuesj-483	73	26	is	be	AUX
cuesj-483	73	27	an	an	DET
cuesj-483	73	28	acronym	acronym	NOUN
cuesj-483	73	29	for	for	ADP
cuesj-483	73	30	mad	mad	ADJ
cuesj-483	73	31	,	,	PUNCT
cuesj-483	73	32	and	and	CCONJ
cuesj-483	73	33	mead	mead	NOUN
cuesj-483	73	34	stands	stand	VERB
cuesj-483	73	35	for	for	ADP
cuesj-483	73	36	median	median	ADJ
cuesj-483	73	37	absolute	absolute	ADJ
cuesj-483	73	38	deviation	deviation	NOUN
cuesj-483	73	39	.	.	PUNCT
cuesj-483	74	1	mean	mean	VERB
cuesj-483	74	2	square	square	ADJ
cuesj-483	74	3	error	error	NOUN
cuesj-483	74	4	(	(	PUNCT
cuesj-483	74	5	mse	mse	NOUN
cuesj-483	74	6	)	)	PUNCT
cuesj-483	74	7	in	in	ADP
cuesj-483	74	8	this	this	DET
cuesj-483	74	9	paper	paper	NOUN
cuesj-483	74	10	,	,	PUNCT
cuesj-483	74	11	mse	mse	PROPN
cuesj-483	74	12	is	be	AUX
cuesj-483	74	13	used	use	VERB
cuesj-483	74	14	as	as	ADP
cuesj-483	74	15	an	an	DET
cuesj-483	74	16	estimation	estimation	NOUN
cuesj-483	74	17	criterion	criterion	NOUN
cuesj-483	74	18	to	to	PART
cuesj-483	74	19	find	find	VERB
cuesj-483	74	20	out	out	ADP
cuesj-483	74	21	the	the	DET
cuesj-483	74	22	difference	difference	NOUN
cuesj-483	74	23	between	between	ADP
cuesj-483	74	24	(	(	PUNCT
cuesj-483	74	25	classical	classical	ADJ
cuesj-483	74	26	)	)	PUNCT
cuesj-483	74	27	traditional	traditional	ADJ
cuesj-483	74	28	and	and	CCONJ
cuesj-483	74	29	newly	newly	ADV
cuesj-483	74	30	proposed	propose	VERB
cuesj-483	74	31	nwk	nwk	NOUN
cuesj-483	74	32	estimators	estimator	NOUN
cuesj-483	74	33	.	.	PUNCT
cuesj-483	75	1	as	as	SCONJ
cuesj-483	75	2	mentioned	mention	VERB
cuesj-483	75	3	below	below	ADV
cuesj-483	75	4	,	,	PUNCT
cuesj-483	75	5	the	the	DET
cuesj-483	75	6	best	good	ADJ
cuesj-483	75	7	estimator	estimator	NOUN
cuesj-483	75	8	will	will	AUX
cuesj-483	75	9	be	be	AUX
cuesj-483	75	10	the	the	DET
cuesj-483	75	11	one	one	NOUN
cuesj-483	75	12	with	with	ADP
cuesj-483	75	13	lowest	low	ADJ
cuesj-483	75	14	mse	mse	NOUN
cuesj-483	75	15	value	value	NOUN
cuesj-483	75	16	.	.	PUNCT
cuesj-483	76	1	2	2	NUM
cuesj-483	76	2	1	1	NUM
cuesj-483	76	3	1	1	NUM
cuesj-483	76	4	(	(	PUNCT
cuesj-483	76	5	)	)	PUNCT
cuesj-483	76	6	ˆ	ˆ	NOUN
cuesj-483	76	7	=	=	SYM
cuesj-483	76	8	=	=	SYM
cuesj-483	76	9	−∑	−∑	PROPN
cuesj-483	76	10	n	n	CCONJ
cuesj-483	77	1	i	i	PRON
cuesj-483	77	2	i	i	PRON
cuesj-483	78	1	i	i	PRON
cuesj-483	78	2	mse	mse	VERB
cuesj-483	78	3	y	y	PROPN
cuesj-483	78	4	y	y	PROPN
cuesj-483	78	5	n	n	PROPN
cuesj-483	78	6	(	(	PUNCT
cuesj-483	78	7	17	17	NUM
cuesj-483	78	8	)	)	PUNCT
cuesj-483	78	9	materials	material	NOUN
cuesj-483	78	10	and	and	CCONJ
cuesj-483	78	11	methods	method	NOUN
cuesj-483	78	12	leukemia	leukemia	NOUN
cuesj-483	78	13	cancer	cancer	NOUN
cuesj-483	78	14	data	datum	NOUN
cuesj-483	78	15	are	be	AUX
cuesj-483	78	16	used	use	VERB
cuesj-483	78	17	to	to	PART
cuesj-483	78	18	undertake	undertake	VERB
cuesj-483	78	19	the	the	DET
cuesj-483	78	20	performance	performance	NOUN
cuesj-483	78	21	of	of	ADP
cuesj-483	78	22	all	all	DET
cuesj-483	78	23	proposed	propose	VERB
cuesj-483	78	24	methods	method	NOUN
cuesj-483	78	25	such	such	ADJ
cuesj-483	78	26	as	as	ADP
cuesj-483	78	27	anw	anw	PROPN
cuesj-483	78	28	irq	irq	PROPN
cuesj-483	78	29	,	,	PUNCT
cuesj-483	78	30	anw	anw	PROPN
cuesj-483	78	31	sd	sd	PROPN
cuesj-483	78	32	,	,	PUNCT
cuesj-483	78	33	anw	anw	X
cuesj-483	78	34	mad	mad	ADJ
cuesj-483	78	35	,	,	PUNCT
cuesj-483	78	36	and	and	CCONJ
cuesj-483	78	37	anw	anw	PROPN
cuesj-483	78	38	mead	mead	NOUN
cuesj-483	78	39	in	in	ADP
cuesj-483	78	40	real	real	ADJ
cuesj-483	78	41	application	application	NOUN
cuesj-483	78	42	which	which	PRON
cuesj-483	78	43	collected	collect	VERB
cuesj-483	78	44	from	from	ADP
cuesj-483	78	45	january	january	PROPN
cuesj-483	78	46	2015	2015	NUM
cuesj-483	78	47	to	to	ADP
cuesj-483	78	48	december	december	PROPN
cuesj-483	78	49	2020	2020	NUM
cuesj-483	78	50	at	at	ADP
cuesj-483	78	51	nanakali	nanakali	ADJ
cuesj-483	78	52	hospital	hospital	NOUN
cuesj-483	78	53	for	for	ADP
cuesj-483	78	54	blood	blood	NOUN
cuesj-483	78	55	in	in	ADP
cuesj-483	78	56	erbil	erbil	PROPN
cuesj-483	78	57	city	city	PROPN
cuesj-483	78	58	of	of	ADP
cuesj-483	78	59	iraq	iraq	PROPN
cuesj-483	78	60	.	.	PUNCT
cuesj-483	79	1	furthermore	furthermore	ADV
cuesj-483	79	2	,	,	PUNCT
cuesj-483	79	3	the	the	DET
cuesj-483	79	4	cd45	cd45	PROPN
cuesj-483	79	5	outcome	outcome	NOUN
cuesj-483	79	6	as	as	ADP
cuesj-483	79	7	an	an	DET
cuesj-483	79	8	explanatory	explanatory	ADJ
cuesj-483	79	9	variable	variable	NOUN
cuesj-483	79	10	and	and	CCONJ
cuesj-483	79	11	platelet	platelet	NOUN
cuesj-483	79	12	(	(	PUNCT
cuesj-483	79	13	plt	plt	NOUN
cuesj-483	79	14	)	)	PUNCT
cuesj-483	79	15	as	as	ADP
cuesj-483	79	16	a	a	DET
cuesj-483	79	17	response	response	NOUN
cuesj-483	79	18	variable	variable	NOUN
cuesj-483	79	19	in	in	ADP
cuesj-483	79	20	aml	aml	PROPN
cuesj-483	79	21	type	type	NOUN
cuesj-483	79	22	of	of	ADP
cuesj-483	79	23	leukemia	leukemia	NOUN
cuesj-483	79	24	cancer	cancer	NOUN
cuesj-483	79	25	from	from	ADP
cuesj-483	79	26	30	30	NUM
cuesj-483	79	27	patients	patient	NOUN
cuesj-483	79	28	in	in	ADP
cuesj-483	79	29	table	table	NOUN
cuesj-483	79	30	1	1	NUM
cuesj-483	79	31	is	be	AUX
cuesj-483	79	32	used	use	VERB
cuesj-483	79	33	to	to	PART
cuesj-483	79	34	compare	compare	VERB
cuesj-483	79	35	between	between	ADP
cuesj-483	79	36	proposed	propose	VERB
cuesj-483	79	37	methods	method	NOUN
cuesj-483	79	38	and	and	CCONJ
cuesj-483	79	39	classical	classical	ADJ
cuesj-483	79	40	methods	method	NOUN
cuesj-483	79	41	.	.	PUNCT
cuesj-483	80	1	since	since	SCONJ
cuesj-483	80	2	simple	simple	ADJ
cuesj-483	80	3	regression	regression	NOUN
cuesj-483	80	4	can	can	AUX
cuesj-483	80	5	not	not	PART
cuesj-483	80	6	be	be	AUX
cuesj-483	80	7	met	meet	VERB
cuesj-483	80	8	due	due	ADJ
cuesj-483	80	9	to	to	ADP
cuesj-483	80	10	assumptions	assumption	NOUN
cuesj-483	80	11	such	such	ADJ
cuesj-483	80	12	as	as	ADP
cuesj-483	80	13	linearity	linearity	NOUN
cuesj-483	80	14	and	and	CCONJ
cuesj-483	80	15	autocorrelation	autocorrelation	NOUN
cuesj-483	80	16	,	,	PUNCT
cuesj-483	80	17	nonparametric	nonparametric	NOUN
cuesj-483	80	18	regression	regression	NOUN
cuesj-483	80	19	is	be	AUX
cuesj-483	80	20	used	use	VERB
cuesj-483	80	21	for	for	ADP
cuesj-483	80	22	both	both	CCONJ
cuesj-483	80	23	classical	classical	ADJ
cuesj-483	80	24	and	and	CCONJ
cuesj-483	80	25	proposed	propose	VERB
cuesj-483	80	26	approaches	approach	NOUN
cuesj-483	80	27	based	base	VERB
cuesj-483	80	28	on	on	ADP
cuesj-483	80	29	mse	mse	PROPN
cuesj-483	80	30	.	.	PUNCT
cuesj-483	80	31	table	table	NOUN
cuesj-483	80	32	2	2	NUM
cuesj-483	80	33	compares	compare	VERB
cuesj-483	80	34	the	the	DET
cuesj-483	80	35	findings	finding	NOUN
cuesj-483	80	36	of	of	ADP
cuesj-483	80	37	classical	classical	ADJ
cuesj-483	80	38	methods	method	NOUN
cuesj-483	80	39	to	to	ADP
cuesj-483	80	40	a	a	DET
cuesj-483	80	41	new	new	ADJ
cuesj-483	80	42	proposed	propose	VERB
cuesj-483	80	43	modification	modification	NOUN
cuesj-483	80	44	of	of	ADP
cuesj-483	80	45	the	the	DET
cuesj-483	80	46	anw	anw	PROPN
cuesj-483	80	47	kernel	kernel	PROPN
cuesj-483	80	48	estimator	estimator	NOUN
cuesj-483	80	49	for	for	ADP
cuesj-483	80	50	iqr	iqr	PROPN
cuesj-483	80	51	,	,	PUNCT
cuesj-483	80	52	sd	sd	NOUN
cuesj-483	80	53	,	,	PUNCT
cuesj-483	80	54	mad	mad	ADJ
cuesj-483	80	55	,	,	PUNCT
cuesj-483	80	56	and	and	CCONJ
cuesj-483	80	57	mead	mead	NOUN
cuesj-483	80	58	based	base	VERB
cuesj-483	80	59	on	on	ADP
cuesj-483	80	60	improving	improve	VERB
cuesj-483	80	61	the	the	DET
cuesj-483	80	62	prediction	prediction	NOUN
cuesj-483	80	63	accuracy	accuracy	NOUN
cuesj-483	80	64	of	of	ADP
cuesj-483	80	65	the	the	DET
cuesj-483	80	66	anw	anw	PROPN
cuesj-483	80	67	kernel	kernel	PROPN
cuesj-483	80	68	estimator	estimator	NOUN
cuesj-483	80	69	.	.	PUNCT
cuesj-483	81	1	the	the	DET
cuesj-483	81	2	proposed	propose	VERB
cuesj-483	81	3	mead	mead	NOUN
cuesj-483	81	4	approach	approach	NOUN
cuesj-483	81	5	has	have	VERB
cuesj-483	81	6	the	the	DET
cuesj-483	81	7	smallest	small	ADJ
cuesj-483	81	8	mse	mse	NOUN
cuesj-483	81	9	in	in	ADP
cuesj-483	81	10	various	various	ADJ
cuesj-483	81	11	bandwidths	bandwidth	NOUN
cuesj-483	81	12	and	and	CCONJ
cuesj-483	81	13	sample	sample	NOUN
cuesj-483	81	14	sizes	size	NOUN
cuesj-483	81	15	,	,	PUNCT
cuesj-483	81	16	followed	follow	VERB
cuesj-483	81	17	by	by	ADP
cuesj-483	81	18	mad	mad	ADJ
cuesj-483	81	19	,	,	PUNCT
cuesj-483	81	20	sd	sd	NOUN
cuesj-483	81	21	,	,	PUNCT
cuesj-483	81	22	and	and	CCONJ
cuesj-483	81	23	iqr	iqr	NOUN
cuesj-483	81	24	,	,	PUNCT
cuesj-483	81	25	respectively	respectively	ADV
cuesj-483	81	26	.	.	PUNCT
cuesj-483	82	1	we	we	PRON
cuesj-483	82	2	achieved	achieve	VERB
cuesj-483	82	3	the	the	DET
cuesj-483	82	4	same	same	ADJ
cuesj-483	82	5	results	result	NOUN
cuesj-483	82	6	as	as	ADP
cuesj-483	82	7	in	in	ADP
cuesj-483	82	8	the	the	DET
cuesj-483	82	9	simulation	simulation	NOUN
cuesj-483	82	10	analysis	analysis	NOUN
cuesj-483	82	11	,	,	PUNCT
cuesj-483	82	12	namely	namely	ADV
cuesj-483	82	13	that	that	SCONJ
cuesj-483	82	14	all	all	DET
cuesj-483	82	15	new	new	ADJ
cuesj-483	82	16	proposed	propose	VERB
cuesj-483	82	17	methods	method	NOUN
cuesj-483	82	18	have	have	VERB
cuesj-483	82	19	smaller	small	ADJ
cuesj-483	82	20	mse	mse	NOUN
cuesj-483	82	21	than	than	ADP
cuesj-483	82	22	all	all	DET
cuesj-483	82	23	classical	classical	ADJ
cuesj-483	82	24	methods	method	NOUN
cuesj-483	82	25	.	.	PUNCT
cuesj-483	83	1	simulation	simulation	NOUN
cuesj-483	83	2	study	study	VERB
cuesj-483	83	3	a	a	DET
cuesj-483	83	4	simulation	simulation	NOUN
cuesj-483	83	5	analysis	analysis	NOUN
cuesj-483	83	6	was	be	AUX
cuesj-483	83	7	carried	carry	VERB
cuesj-483	83	8	out	out	ADP
cuesj-483	83	9	to	to	PART
cuesj-483	83	10	compare	compare	VERB
cuesj-483	83	11	the	the	DET
cuesj-483	83	12	efficiency	efficiency	NOUN
cuesj-483	83	13	between	between	ADP
cuesj-483	83	14	traditional	traditional	ADJ
cuesj-483	83	15	nadaraya	nadaraya	PROPN
cuesj-483	83	16	-	-	PUNCT
cuesj-483	83	17	watson	watson	NOUN
cuesj-483	83	18	and	and	CCONJ
cuesj-483	83	19	new	new	ADJ
cuesj-483	83	20	proposed	propose	VERB
cuesj-483	83	21	methods	method	NOUN
cuesj-483	83	22	of	of	ADP
cuesj-483	83	23	anw	anw	NOUN
cuesj-483	83	24	estimators	estimator	NOUN
cuesj-483	83	25	using	use	VERB
cuesj-483	83	26	the	the	DET
cuesj-483	83	27	r	r	NOUN
cuesj-483	83	28	(	(	PUNCT
cuesj-483	83	29	4.0.2	4.0.2	NUM
cuesj-483	83	30	)	)	PUNCT
cuesj-483	83	31	language	language	NOUN
cuesj-483	83	32	software	software	NOUN
cuesj-483	83	33	.	.	PUNCT
cuesj-483	84	1	an	an	DET
cuesj-483	84	2	explanatory	explanatory	ADJ
cuesj-483	84	3	variable	variable	ADJ
cuesj-483	84	4	and	and	CCONJ
cuesj-483	84	5	response	response	NOUN
cuesj-483	84	6	variable	variable	NOUN
cuesj-483	84	7	with	with	ADP
cuesj-483	84	8	adding	add	VERB
cuesj-483	84	9	noise	noise	NOUN
cuesj-483	84	10	to	to	ADP
cuesj-483	84	11	an	an	DET
cuesj-483	84	12	exponential	exponential	ADJ
cuesj-483	84	13	wave	wave	NOUN
cuesj-483	84	14	are	be	AUX
cuesj-483	84	15	simulated	simulate	VERB
cuesj-483	84	16	in	in	ADP
cuesj-483	84	17	this	this	DET
cuesj-483	84	18	nonlinear	nonlinear	ADJ
cuesj-483	84	19	regression	regression	NOUN
cuesj-483	84	20	function	function	NOUN
cuesj-483	84	21	to	to	PART
cuesj-483	84	22	identify	identify	VERB
cuesj-483	84	23	that	that	SCONJ
cuesj-483	84	24	proposed	propose	VERB
cuesj-483	84	25	methods	method	NOUN
cuesj-483	84	26	outperforms	outperform	VERB
cuesj-483	84	27	classical	classical	ADJ
cuesj-483	84	28	models	model	NOUN
cuesj-483	84	29	.	.	PUNCT
cuesj-483	85	1	y	y	NOUN
cuesj-483	85	2	x	x	PUNCT
cuesj-483	86	1	x	x	PUNCT
cuesj-483	86	2	ni	ni	NOUN
cuesj-483	87	1	i	i	PRON
cuesj-483	87	2	i	i	PRON
cuesj-483	88	1	i	i	PROPN
cuesj-483	88	2	�	�	PROPN
cuesj-483	88	3	�	�	PROPN
cuesj-483	88	4	�	�	PROPN
cuesj-483	88	5	�	�	PROPN
cuesj-483	88	6	�	�	PROPN
cuesj-483	88	7	exp	exp	NOUN
cuesj-483	88	8	~	~	PUNCT
cuesj-483	88	9	(	(	PUNCT
cuesj-483	88	10	,	,	PUNCT
cuesj-483	88	11	)	)	PUNCT
cuesj-483	88	12	3	3	NUM
cuesj-483	88	13	0	0	NUM
cuesj-483	88	14	1	1	NUM
cuesj-483	88	15	�	�	PROPN
cuesj-483	88	16	(	(	PUNCT
cuesj-483	88	17	18	18	NUM
cuesj-483	88	18	)	)	PUNCT
cuesj-483	88	19	where	where	SCONJ
cuesj-483	88	20	xi	xi	PROPN
cuesj-483	88	21	was	be	AUX
cuesj-483	88	22	chosen	choose	VERB
cuesj-483	88	23	at	at	ADP
cuesj-483	88	24	random	random	ADJ
cuesj-483	88	25	from	from	ADP
cuesj-483	88	26	a	a	DET
cuesj-483	88	27	uniform	uniform	ADJ
cuesj-483	88	28	distribution	distribution	NOUN
cuesj-483	88	29	on	on	ADP
cuesj-483	88	30	the	the	DET
cuesj-483	88	31	interval	interval	NOUN
cuesj-483	88	32	[	[	X
cuesj-483	88	33	–	–	PUNCT
cuesj-483	88	34	2	2	NUM
cuesj-483	88	35	,	,	PUNCT
cuesj-483	88	36	2	2	NUM
cuesj-483	88	37	]	]	PUNCT
cuesj-483	88	38	and	and	CCONJ
cuesj-483	88	39	generated	generate	VERB
cuesj-483	88	40	different	different	ADJ
cuesj-483	88	41	samples	sample	NOUN
cuesj-483	88	42	of	of	ADP
cuesj-483	88	43	size	size	NOUN
cuesj-483	88	44	(	(	PUNCT
cuesj-483	88	45	25	25	NUM
cuesj-483	88	46	,	,	PUNCT
cuesj-483	88	47	50	50	NUM
cuesj-483	88	48	,	,	PUNCT
cuesj-483	88	49	75	75	NUM
cuesj-483	88	50	and	and	CCONJ
cuesj-483	88	51	150	150	NUM
cuesj-483	88	52	)	)	PUNCT
cuesj-483	88	53	with	with	ADP
cuesj-483	88	54	different	different	ADJ
cuesj-483	88	55	fixed	fix	VERB
cuesj-483	88	56	h	h	NOUN
cuesj-483	88	57	(	(	PUNCT
cuesj-483	88	58	0.5	0.5	NUM
cuesj-483	88	59	,	,	PUNCT
cuesj-483	88	60	0.75	0.75	NUM
cuesj-483	88	61	,	,	PUNCT
cuesj-483	88	62	1	1	NUM
cuesj-483	88	63	,	,	PUNCT
cuesj-483	88	64	and	and	CCONJ
cuesj-483	88	65	1.5	1.5	NUM
cuesj-483	88	66	)	)	PUNCT
cuesj-483	88	67	.	.	PUNCT
cuesj-483	89	1	in	in	ADP
cuesj-483	89	2	this	this	DET
cuesj-483	89	3	paper	paper	NOUN
cuesj-483	89	4	,	,	PUNCT
cuesj-483	89	5	comparison	comparison	NOUN
cuesj-483	89	6	between	between	ADP
cuesj-483	89	7	classical	classical	ADJ
cuesj-483	89	8	methods	method	NOUN
cuesj-483	89	9	such	such	ADJ
cuesj-483	89	10	as	as	ADP
cuesj-483	89	11	fnw	fnw	PROPN
cuesj-483	89	12	,	,	PUNCT
cuesj-483	89	13	vnw	vnw	VERB
cuesj-483	89	14	geometric	geometric	ADJ
cuesj-483	89	15	,	,	PUNCT
cuesj-483	89	16	anw	anw	NOUN
cuesj-483	89	17	mean	mean	VERB
cuesj-483	89	18	,	,	PUNCT
cuesj-483	89	19	anw	anw	PROPN
cuesj-483	89	20	median	median	NOUN
cuesj-483	89	21	,	,	PUNCT
cuesj-483	89	22	anw	anw	PROPN
cuesj-483	89	23	range	range	VERB
cuesj-483	89	24	with	with	ADP
cuesj-483	89	25	new	new	ADJ
cuesj-483	89	26	proposed	propose	VERB
cuesj-483	89	27	methods	method	NOUN
cuesj-483	89	28	such	such	ADJ
cuesj-483	89	29	as	as	ADP
cuesj-483	89	30	anw	anw	PROPN
cuesj-483	89	31	irq	irq	PROPN
cuesj-483	89	32	,	,	PUNCT
cuesj-483	89	33	anw	anw	PROPN
cuesj-483	89	34	sd	sd	PROPN
cuesj-483	89	35	,	,	PUNCT
cuesj-483	89	36	anw	anw	X
cuesj-483	89	37	mad	mad	ADJ
cuesj-483	89	38	,	,	PUNCT
cuesj-483	89	39	and	and	CCONJ
cuesj-483	89	40	anw	anw	PROPN
cuesj-483	89	41	mead	mead	PROPN
cuesj-483	89	42	kernel	kernel	PROPN
cuesj-483	89	43	estimations	estimation	NOUN
cuesj-483	89	44	were	be	AUX
cuesj-483	89	45	computed	compute	VERB
cuesj-483	89	46	by	by	ADP
cuesj-483	89	47	gaussian	gaussian	ADJ
cuesj-483	89	48	kernel	kernel	PROPN
cuesj-483	89	49	function	function	NOUN
cuesj-483	89	50	with	with	ADP
cuesj-483	89	51	20000000	20000000	NUM
cuesj-483	89	52	repetitions	repetition	NOUN
cuesj-483	89	53	in	in	ADP
cuesj-483	89	54	each	each	DET
cuesj-483	89	55	estimation	estimation	NOUN
cuesj-483	89	56	.	.	PUNCT
cuesj-483	90	1	figure	figure	NOUN
cuesj-483	90	2	1	1	NUM
cuesj-483	90	3	represents	represent	VERB
cuesj-483	90	4	the	the	DET
cuesj-483	90	5	results	result	NOUN
cuesj-483	90	6	between	between	ADP
cuesj-483	90	7	classical	classical	ADJ
cuesj-483	90	8	and	and	CCONJ
cuesj-483	90	9	new	new	ADJ
cuesj-483	90	10	proposed	propose	VERB
cuesj-483	90	11	methods	method	NOUN
cuesj-483	90	12	at	at	ADP
cuesj-483	90	13	h	h	PROPN
cuesj-483	90	14	(	(	PUNCT
cuesj-483	90	15	5	5	NUM
cuesj-483	90	16	,	,	PUNCT
cuesj-483	90	17	15	15	NUM
cuesj-483	90	18	,	,	PUNCT
cuesj-483	90	19	and	and	CCONJ
cuesj-483	90	20	30	30	NUM
cuesj-483	90	21	)	)	PUNCT
cuesj-483	90	22	for	for	ADP
cuesj-483	90	23	real	real	ADJ
cuesj-483	90	24	data	datum	NOUN
cuesj-483	90	25	.	.	PUNCT
cuesj-483	91	1	on	on	ADP
cuesj-483	91	2	the	the	DET
cuesj-483	91	3	table	table	NOUN
cuesj-483	91	4	1	1	NUM
cuesj-483	91	5	:	:	PUNCT
cuesj-483	91	6	aml	aml	NOUN
cuesj-483	91	7	type	type	NOUN
cuesj-483	91	8	of	of	ADP
cuesj-483	91	9	leukemia	leukemia	NOUN
cuesj-483	91	10	cancer	cancer	NOUN
cuesj-483	91	11	from	from	ADP
cuesj-483	91	12	2015	2015	NUM
cuesj-483	91	13	to	to	ADP
cuesj-483	91	14	2020	2020	NUM
cuesj-483	91	15	cd45	cd45	PROPN
cuesj-483	91	16	plt	plt	NOUN
cuesj-483	91	17	cd45	cd45	PROPN
cuesj-483	91	18	plt	plt	NOUN
cuesj-483	91	19	cd45	cd45	PROPN
cuesj-483	91	20	plt	plt	NOUN
cuesj-483	91	21	cd45	cd45	PROPN
cuesj-483	91	22	plt	plt	NOUN
cuesj-483	91	23	cd45	cd45	PROPN
cuesj-483	91	24	plt	plt	NOUN
cuesj-483	91	25	70	70	NUM
cuesj-483	91	26	17	17	NUM
cuesj-483	91	27	80	80	NUM
cuesj-483	91	28	54	54	NUM
cuesj-483	91	29	62	62	NUM
cuesj-483	91	30	13	13	NUM
cuesj-483	91	31	80	80	NUM
cuesj-483	91	32	89	89	NUM
cuesj-483	91	33	74	74	NUM
cuesj-483	91	34	61	61	NUM
cuesj-483	91	35	70	70	NUM
cuesj-483	91	36	51	51	NUM
cuesj-483	91	37	88	88	NUM
cuesj-483	91	38	31	31	NUM
cuesj-483	91	39	60	60	NUM
cuesj-483	91	40	15	15	NUM
cuesj-483	91	41	90	90	NUM
cuesj-483	91	42	6	6	NUM
cuesj-483	91	43	77	77	NUM
cuesj-483	91	44	16	16	NUM
cuesj-483	91	45	80	80	NUM
cuesj-483	91	46	7	7	NUM
cuesj-483	91	47	58	58	NUM
cuesj-483	91	48	16	16	NUM
cuesj-483	91	49	32	32	NUM
cuesj-483	91	50	62	62	NUM
cuesj-483	91	51	88	88	NUM
cuesj-483	91	52	137	137	NUM
cuesj-483	91	53	80	80	NUM
cuesj-483	91	54	155	155	NUM
cuesj-483	91	55	94	94	NUM
cuesj-483	91	56	79	79	NUM
cuesj-483	91	57	54	54	NUM
cuesj-483	91	58	40	40	NUM
cuesj-483	91	59	42	42	NUM
cuesj-483	91	60	71	71	NUM
cuesj-483	91	61	60	60	NUM
cuesj-483	91	62	2	2	NUM
cuesj-483	91	63	55	55	NUM
cuesj-483	91	64	24	24	NUM
cuesj-483	91	65	40	40	NUM
cuesj-483	91	66	44	44	NUM
cuesj-483	91	67	70	70	NUM
cuesj-483	91	68	95	95	NUM
cuesj-483	91	69	54	54	NUM
cuesj-483	91	70	19	19	NUM
cuesj-483	91	71	35	35	NUM
cuesj-483	91	72	58.9	58.9	NUM
cuesj-483	91	73	70	70	NUM
cuesj-483	91	74	31	31	NUM
cuesj-483	91	75	85	85	NUM
cuesj-483	91	76	68	68	NUM
cuesj-483	91	77	74	74	NUM
cuesj-483	91	78	46	46	NUM
cuesj-483	91	79	86	86	NUM
cuesj-483	91	80	5	5	NUM
cuesj-483	91	81	43	43	NUM
cuesj-483	91	82	33	33	NUM
cuesj-483	91	83	80	80	NUM
cuesj-483	91	84	229	229	NUM
cuesj-483	91	85	table	table	NOUN
cuesj-483	91	86	2	2	NUM
cuesj-483	91	87	:	:	PUNCT
cuesj-483	91	88	mse	mse	NOUN
cuesj-483	91	89	values	value	NOUN
cuesj-483	91	90	between	between	ADP
cuesj-483	91	91	classical	classical	ADJ
cuesj-483	91	92	methods	method	NOUN
cuesj-483	91	93	and	and	CCONJ
cuesj-483	91	94	proposed	propose	VERB
cuesj-483	91	95	methods	method	NOUN
cuesj-483	91	96	of	of	ADP
cuesj-483	91	97	nwk	nwk	NOUN
cuesj-483	91	98	estimators	estimator	NOUN
cuesj-483	91	99	in	in	ADP
cuesj-483	91	100	real	real	ADJ
cuesj-483	91	101	data	datum	NOUN
cuesj-483	91	102	(	(	PUNCT
cuesj-483	91	103	n=30	n=30	NOUN
cuesj-483	91	104	)	)	PUNCT
cuesj-483	91	105	h	h	NOUN
cuesj-483	91	106	fixed	fix	VERB
cuesj-483	91	107	nw	nw	PROPN
cuesj-483	91	108	variable	variable	PROPN
cuesj-483	91	109	nw	nw	PROPN
cuesj-483	91	110	g	g	PROPN
cuesj-483	91	111	anw	anw	PROPN
cuesj-483	91	112	m	m	VERB
cuesj-483	92	1	anw	anw	INTJ
cuesj-483	93	1	me	i	PRON
cuesj-483	94	1	anw	anw	INTJ
cuesj-483	94	2	r	r	NOUN
cuesj-483	94	3	anw	anw	PROPN
cuesj-483	94	4	iqr	iqr	PROPN
cuesj-483	94	5	anw	anw	PROPN
cuesj-483	95	1	sd	sd	ADP
cuesj-483	95	2	anw	anw	PROPN
cuesj-483	95	3	mad	mad	ADJ
cuesj-483	95	4	anw	anw	PROPN
cuesj-483	95	5	mead	mead	NOUN
cuesj-483	95	6	5	5	NUM
cuesj-483	95	7	1890.7	1890.7	NUM
cuesj-483	95	8	1751.1	1751.1	NUM
cuesj-483	95	9	1768.2	1768.2	NUM
cuesj-483	95	10	1781	1781	NUM
cuesj-483	95	11	1787.9	1787.9	NUM
cuesj-483	95	12	1609.8	1609.8	NUM
cuesj-483	95	13	1609.7	1609.7	NUM
cuesj-483	95	14	1574.3	1574.3	NUM
cuesj-483	95	15	1572.4	1572.4	NUM
cuesj-483	95	16	10	10	NUM
cuesj-483	95	17	2071	2071	NUM
cuesj-483	95	18	2010.9	2010.9	NUM
cuesj-483	95	19	2017.1	2017.1	NUM
cuesj-483	95	20	2015.6	2015.6	NUM
cuesj-483	95	21	1964.9	1964.9	NUM
cuesj-483	95	22	1909.1	1909.1	NUM
cuesj-483	95	23	1827.6	1827.6	NUM
cuesj-483	95	24	1803.2	1803.2	NUM
cuesj-483	95	25	1802.8	1802.8	NUM
cuesj-483	95	26	15	15	NUM
cuesj-483	95	27	2214.5	2214.5	NUM
cuesj-483	95	28	2176.2	2176.2	NUM
cuesj-483	95	29	2179.1	2179.1	NUM
cuesj-483	95	30	2179.2	2179.2	NUM
cuesj-483	95	31	2046.3	2046.3	NUM
cuesj-483	95	32	1983.4	1983.4	NUM
cuesj-483	95	33	1906	1906	NUM
cuesj-483	95	34	1889.1	1889.1	NUM
cuesj-483	95	35	1889	1889	NUM
cuesj-483	95	36	20	20	NUM
cuesj-483	95	37	2297.3	2297.3	NUM
cuesj-483	95	38	2277.5	2277.5	NUM
cuesj-483	95	39	2278.5	2278.5	NUM
cuesj-483	95	40	2279.3	2279.3	NUM
cuesj-483	95	41	2111.5	2111.5	NUM
cuesj-483	95	42	2021.5	2021.5	NUM
cuesj-483	95	43	1945.7	1945.7	NUM
cuesj-483	95	44	1928.5	1928.5	NUM
cuesj-483	95	45	1927.2	1927.2	NUM
cuesj-483	95	46	25	25	NUM
cuesj-483	95	47	2340.4	2340.4	NUM
cuesj-483	95	48	2331.2	2331.2	NUM
cuesj-483	95	49	2331.6	2331.6	NUM
cuesj-483	95	50	2332.1	2332.1	NUM
cuesj-483	95	51	2152.3	2152.3	NUM
cuesj-483	95	52	2029.6	2029.6	NUM
cuesj-483	95	53	1966.8	1966.8	NUM
cuesj-483	95	54	1947.9	1947.9	NUM
cuesj-483	95	55	1945.8	1945.8	NUM
cuesj-483	95	56	30	30	NUM
cuesj-483	95	57	2365.4	2365.4	NUM
cuesj-483	95	58	2360.9	2360.9	NUM
cuesj-483	95	59	2361.1	2361.1	NUM
cuesj-483	95	60	2361.4	2361.4	NUM
cuesj-483	95	61	2174.6	2174.6	NUM
cuesj-483	95	62	2033.7	2033.7	NUM
cuesj-483	95	63	1978	1978	NUM
cuesj-483	95	64	1958	1958	NUM
cuesj-483	95	65	1955.5	1955.5	NUM
cuesj-483	95	66	blbas	blbas	NOUN
cuesj-483	95	67	and	and	CCONJ
cuesj-483	95	68	kahwachi	kahwachi	ADJ
cuesj-483	95	69	:	:	PUNCT
cuesj-483	95	70	new	new	ADJ
cuesj-483	95	71	modification	modification	NOUN
cuesj-483	95	72	of	of	ADP
cuesj-483	95	73	anwk	anwk	NOUN
cuesj-483	95	74	in	in	ADP
cuesj-483	95	75	nonparametric	nonparametric	PROPN
cuesj-483	95	76	regression	regression	NOUN
cuesj-483	95	77	35	35	NUM
cuesj-483	95	78	http://journals.cihanuniversity.edu.iq/index.php/cuesj	http://journals.cihanuniversity.edu.iq/index.php/cuesj	ADJ
cuesj-483	95	79	cuesj	cuesj	ADJ
cuesj-483	95	80	2021	2021	NUM
cuesj-483	95	81	,	,	PUNCT
cuesj-483	95	82	5	5	NUM
cuesj-483	95	83	(	(	PUNCT
cuesj-483	95	84	2	2	NUM
cuesj-483	95	85	):	):	PUNCT
cuesj-483	95	86	32	32	NUM
cuesj-483	95	87	-	-	SYM
cuesj-483	95	88	37	37	NUM
cuesj-483	95	89	other	other	ADJ
cuesj-483	95	90	hand	hand	NOUN
cuesj-483	95	91	,	,	PUNCT
cuesj-483	95	92	figures	figure	NOUN
cuesj-483	95	93	2	2	NUM
cuesj-483	95	94	and	and	CCONJ
cuesj-483	95	95	3	3	NUM
cuesj-483	95	96	illustrate	illustrate	VERB
cuesj-483	95	97	the	the	DET
cuesj-483	95	98	simulation	simulation	NOUN
cuesj-483	95	99	results	result	VERB
cuesj-483	95	100	for	for	ADP
cuesj-483	95	101	both	both	CCONJ
cuesj-483	95	102	classical	classical	ADJ
cuesj-483	95	103	and	and	CCONJ
cuesj-483	95	104	proposed	propose	VERB
cuesj-483	95	105	methods	method	NOUN
cuesj-483	95	106	in	in	ADP
cuesj-483	95	107	nonparametric	nonparametric	NOUN
cuesj-483	95	108	regression	regression	NOUN
cuesj-483	95	109	functions	function	NOUN
cuesj-483	95	110	with	with	ADP
cuesj-483	95	111	sample	sample	NOUN
cuesj-483	95	112	size	size	NOUN
cuesj-483	95	113	of	of	ADP
cuesj-483	95	114	75	75	NUM
cuesj-483	95	115	and	and	CCONJ
cuesj-483	95	116	at	at	ADP
cuesj-483	95	117	h	h	PROPN
cuesj-483	95	118	(	(	PUNCT
cuesj-483	95	119	0.5	0.5	NUM
cuesj-483	95	120	,	,	PUNCT
cuesj-483	95	121	07.75	07.75	NUM
cuesj-483	95	122	,	,	PUNCT
cuesj-483	95	123	1	1	NUM
cuesj-483	95	124	,	,	PUNCT
cuesj-483	95	125	and	and	CCONJ
cuesj-483	95	126	1.5	1.5	NUM
cuesj-483	95	127	)	)	PUNCT
cuesj-483	95	128	,	,	PUNCT
cuesj-483	95	129	respectively	respectively	ADV
cuesj-483	95	130	.	.	PUNCT
cuesj-483	96	1	table	table	NOUN
cuesj-483	96	2	3	3	NUM
cuesj-483	96	3	compares	compare	NOUN
cuesj-483	96	4	simulation	simulation	NOUN
cuesj-483	96	5	results	result	NOUN
cuesj-483	96	6	between	between	ADP
cuesj-483	96	7	all	all	DET
cuesj-483	96	8	classical	classical	ADJ
cuesj-483	96	9	(	(	PUNCT
cuesj-483	96	10	traditional	traditional	ADJ
cuesj-483	96	11	)	)	PUNCT
cuesj-483	96	12	methods	method	NOUN
cuesj-483	96	13	and	and	CCONJ
cuesj-483	96	14	new	new	ADJ
cuesj-483	96	15	proposed	propose	VERB
cuesj-483	96	16	update	update	NOUN
cuesj-483	96	17	of	of	ADP
cuesj-483	96	18	adaptive	adaptive	ADJ
cuesj-483	96	19	nw	nw	PROPN
cuesj-483	96	20	kernel	kernel	PROPN
cuesj-483	96	21	such	such	ADJ
cuesj-483	96	22	as	as	ADP
cuesj-483	96	23	iqr	iqr	PROPN
cuesj-483	96	24	,	,	PUNCT
cuesj-483	96	25	sd	sd	NOUN
cuesj-483	96	26	,	,	PUNCT
cuesj-483	96	27	mad	mad	ADJ
cuesj-483	96	28	,	,	PUNCT
cuesj-483	96	29	and	and	CCONJ
cuesj-483	96	30	mead	mead	NOUN
cuesj-483	96	31	aimed	aim	VERB
cuesj-483	96	32	at	at	ADP
cuesj-483	96	33	figure	figure	NOUN
cuesj-483	96	34	1	1	NUM
cuesj-483	96	35	:	:	PUNCT
cuesj-483	96	36	left	leave	VERB
cuesj-483	96	37	hand	hand	NOUN
cuesj-483	96	38	classical	classical	ADJ
cuesj-483	96	39	methods	method	NOUN
cuesj-483	96	40	and	and	CCONJ
cuesj-483	96	41	right	right	ADJ
cuesj-483	96	42	hand	hand	NOUN
cuesj-483	96	43	proposed	propose	VERB
cuesj-483	96	44	methods	method	NOUN
cuesj-483	96	45	at	at	ADP
cuesj-483	96	46	h=5	h=5	PROPN
cuesj-483	96	47	,	,	PUNCT
cuesj-483	96	48	15	15	NUM
cuesj-483	96	49	,	,	PUNCT
cuesj-483	96	50	and	and	CCONJ
cuesj-483	96	51	30	30	NUM
cuesj-483	96	52	for	for	ADP
cuesj-483	96	53	real	real	ADJ
cuesj-483	96	54	data	datum	NOUN
cuesj-483	96	55	.	.	PUNCT
cuesj-483	97	1	(	(	PUNCT
cuesj-483	97	2	a	a	X
cuesj-483	97	3	)	)	PUNCT
cuesj-483	97	4	cd45	cd45	PROPN
cuesj-483	97	5	versus	versus	ADP
cuesj-483	97	6	plt	plt	NOUN
cuesj-483	97	7	at	at	ADP
cuesj-483	97	8	h=5	h=5	PROPN
cuesj-483	97	9	,	,	PUNCT
cuesj-483	97	10	(	(	PUNCT
cuesj-483	97	11	b	b	X
cuesj-483	97	12	)	)	PUNCT
cuesj-483	97	13	cd45	cd45	PROPN
cuesj-483	97	14	versus	versus	ADP
cuesj-483	97	15	plt	plt	NOUN
cuesj-483	97	16	at	at	ADP
cuesj-483	97	17	h=5	h=5	PROPN
cuesj-483	97	18	,	,	PUNCT
cuesj-483	97	19	(	(	PUNCT
cuesj-483	97	20	c	c	X
cuesj-483	97	21	)	)	PUNCT
cuesj-483	97	22	cd45	cd45	PROPN
cuesj-483	97	23	versus	versus	ADP
cuesj-483	97	24	plt	plt	NOUN
cuesj-483	97	25	at	at	ADP
cuesj-483	97	26	h=15	h=15	PROPN
cuesj-483	97	27	,	,	PUNCT
cuesj-483	97	28	(	(	PUNCT
cuesj-483	97	29	d	d	X
cuesj-483	97	30	)	)	PUNCT
cuesj-483	97	31	cd45	cd45	PROPN
cuesj-483	97	32	versus	versus	ADP
cuesj-483	97	33	plt	plt	NOUN
cuesj-483	97	34	at	at	ADP
cuesj-483	97	35	h=15	h=15	PROPN
cuesj-483	97	36	(	(	PUNCT
cuesj-483	97	37	e	e	NOUN
cuesj-483	97	38	)	)	PUNCT
cuesj-483	97	39	cd45	cd45	PROPN
cuesj-483	97	40	versus	versus	ADP
cuesj-483	97	41	plt	plt	NOUN
cuesj-483	97	42	at	at	ADP
cuesj-483	97	43	h=30	h=30	PROPN
cuesj-483	97	44	fcd45	fcd45	PROPN
cuesj-483	97	45	versus	versus	ADP
cuesj-483	97	46	plt	plt	NOUN
cuesj-483	97	47	at	at	ADP
cuesj-483	97	48	h=30	h=30	NOUN
cuesj-483	97	49	improving	improve	VERB
cuesj-483	97	50	the	the	DET
cuesj-483	97	51	prediction	prediction	NOUN
cuesj-483	97	52	accuracy	accuracy	NOUN
cuesj-483	97	53	of	of	ADP
cuesj-483	97	54	anwk	anwk	NOUN
cuesj-483	97	55	estimator	estimator	NOUN
cuesj-483	97	56	.	.	PUNCT
cuesj-483	98	1	according	accord	VERB
cuesj-483	98	2	to	to	ADP
cuesj-483	98	3	mse	mse	NOUN
cuesj-483	98	4	criteria	criterion	NOUN
cuesj-483	98	5	,	,	PUNCT
cuesj-483	98	6	the	the	DET
cuesj-483	98	7	new	new	ADJ
cuesj-483	98	8	proposed	propose	VERB
cuesj-483	98	9	methods	method	NOUN
cuesj-483	98	10	outperform	outperform	VERB
cuesj-483	98	11	classical	classical	ADJ
cuesj-483	98	12	methods	method	NOUN
cuesj-483	98	13	of	of	ADP
cuesj-483	98	14	using	use	VERB
cuesj-483	98	15	various	various	ADJ
cuesj-483	98	16	sample	sample	NOUN
cuesj-483	98	17	sizes	size	NOUN
cuesj-483	98	18	and	and	CCONJ
cuesj-483	98	19	initial	initial	ADJ
cuesj-483	98	20	bandwidth	bandwidth	ADJ
cuesj-483	98	21	values	value	NOUN
cuesj-483	98	22	.	.	PUNCT
cuesj-483	99	1	while	while	SCONJ
cuesj-483	99	2	the	the	DET
cuesj-483	99	3	new	new	ADJ
cuesj-483	99	4	proposed	propose	VERB
cuesj-483	99	5	iqr	iqr	PROPN
cuesj-483	99	6	is	be	AUX
cuesj-483	99	7	better	well	ADJ
cuesj-483	99	8	than	than	ADP
cuesj-483	99	9	other	other	ADJ
cuesj-483	99	10	classical	classical	ADJ
cuesj-483	99	11	approaches	approach	NOUN
cuesj-483	99	12	,	,	PUNCT
cuesj-483	99	13	it	it	PRON
cuesj-483	99	14	is	be	AUX
cuesj-483	99	15	less	less	ADV
cuesj-483	99	16	effective	effective	ADJ
cuesj-483	99	17	than	than	ADP
cuesj-483	99	18	other	other	ADJ
cuesj-483	99	19	proposed	propose	VERB
cuesj-483	99	20	methods	method	NOUN
cuesj-483	99	21	such	such	ADJ
cuesj-483	99	22	as	as	ADP
cuesj-483	99	23	sd	sd	NOUN
cuesj-483	99	24	,	,	PUNCT
cuesj-483	99	25	mad	mad	ADJ
cuesj-483	99	26	,	,	PUNCT
cuesj-483	99	27	and	and	CCONJ
cuesj-483	99	28	mead	mead	NOUN
cuesj-483	99	29	,	,	PUNCT
cuesj-483	99	30	respectively	respectively	ADV
cuesj-483	99	31	.	.	PUNCT
cuesj-483	100	1	on	on	ADP
cuesj-483	100	2	the	the	DET
cuesj-483	100	3	other	other	ADJ
cuesj-483	100	4	hand	hand	NOUN
cuesj-483	100	5	,	,	PUNCT
cuesj-483	100	6	dc	dc	PROPN
cuesj-483	100	7	b	b	PROPN
cuesj-483	100	8	f	f	PROPN
cuesj-483	100	9	a	a	DET
cuesj-483	100	10	e	e	NOUN
cuesj-483	100	11	blbas	blbas	NOUN
cuesj-483	100	12	and	and	CCONJ
cuesj-483	100	13	kahwachi	kahwachi	PROPN
cuesj-483	100	14	:	:	PUNCT
cuesj-483	100	15	new	new	ADJ
cuesj-483	100	16	modification	modification	NOUN
cuesj-483	100	17	of	of	ADP
cuesj-483	100	18	anwk	anwk	NOUN
cuesj-483	100	19	in	in	ADP
cuesj-483	100	20	nonparametric	nonparametric	PROPN
cuesj-483	100	21	regression	regression	NOUN
cuesj-483	100	22	36	36	NUM
cuesj-483	100	23	http://journals.cihanuniversity.edu.iq/index.php/cuesj	http://journals.cihanuniversity.edu.iq/index.php/cuesj	ADJ
cuesj-483	100	24	cuesj	cuesj	ADJ
cuesj-483	100	25	2021	2021	NUM
cuesj-483	100	26	,	,	PUNCT
cuesj-483	100	27	5	5	NUM
cuesj-483	100	28	(	(	PUNCT
cuesj-483	100	29	2	2	NUM
cuesj-483	100	30	):	):	PUNCT
cuesj-483	100	31	32	32	NUM
cuesj-483	100	32	-	-	SYM
cuesj-483	100	33	37	37	NUM
cuesj-483	100	34	the	the	DET
cuesj-483	100	35	proposed	propose	VERB
cuesj-483	100	36	method	method	NOUN
cuesj-483	100	37	using	use	VERB
cuesj-483	100	38	mead	mead	NOUN
cuesj-483	100	39	has	have	VERB
cuesj-483	100	40	less	less	ADJ
cuesj-483	100	41	mse	mse	NOUN
cuesj-483	100	42	than	than	ADP
cuesj-483	100	43	mad	mad	ADJ
cuesj-483	100	44	,	,	PUNCT
cuesj-483	100	45	in	in	ADP
cuesj-483	100	46	turn	turn	NOUN
cuesj-483	100	47	mad	mad	ADJ
cuesj-483	100	48	is	be	AUX
cuesj-483	100	49	less	less	ADJ
cuesj-483	100	50	than	than	ADP
cuesj-483	100	51	sd	sd	NOUN
cuesj-483	100	52	,	,	PUNCT
cuesj-483	100	53	and	and	CCONJ
cuesj-483	100	54	sd	sd	NOUN
cuesj-483	100	55	is	be	AUX
cuesj-483	100	56	less	less	ADJ
cuesj-483	100	57	than	than	ADP
cuesj-483	100	58	iqr	iqr	PROPN
cuesj-483	100	59	in	in	ADP
cuesj-483	100	60	different	different	ADJ
cuesj-483	100	61	bandwidth	bandwidth	NOUN
cuesj-483	100	62	and	and	CCONJ
cuesj-483	100	63	sample	sample	NOUN
cuesj-483	100	64	size	size	NOUN
cuesj-483	100	65	.	.	PUNCT
cuesj-483	101	1	conclussion	conclussion	NOUN
cuesj-483	101	2	1the	1the	NUM
cuesj-483	101	3	new	new	ADJ
cuesj-483	101	4	proposed	propose	VERB
cuesj-483	101	5	method	method	NOUN
cuesj-483	101	6	estimator	estimator	NOUN
cuesj-483	101	7	for	for	ADP
cuesj-483	101	8	median	median	ADJ
cuesj-483	101	9	absolute	absolute	ADJ
cuesj-483	101	10	deviation	deviation	NOUN
cuesj-483	101	11	(	(	PUNCT
cuesj-483	101	12	mead	mead	NOUN
cuesj-483	101	13	)	)	PUNCT
cuesj-483	101	14	was	be	AUX
cuesj-483	101	15	more	more	ADV
cuesj-483	101	16	reliable	reliable	ADJ
cuesj-483	101	17	than	than	ADP
cuesj-483	101	18	any	any	PRON
cuesj-483	101	19	of	of	ADP
cuesj-483	101	20	the	the	DET
cuesj-483	101	21	other	other	ADJ
cuesj-483	101	22	classical	classical	ADJ
cuesj-483	101	23	methods	method	NOUN
cuesj-483	101	24	for	for	ADP
cuesj-483	101	25	both	both	PRON
cuesj-483	101	26	simulation	simulation	NOUN
cuesj-483	101	27	and	and	CCONJ
cuesj-483	101	28	actual	actual	ADJ
cuesj-483	101	29	data	datum	NOUN
cuesj-483	101	30	depending	depend	VERB
cuesj-483	101	31	on	on	ADP
cuesj-483	101	32	mse	mse	NOUN
cuesj-483	101	33	criteria	criterion	NOUN
cuesj-483	101	34	because	because	SCONJ
cuesj-483	101	35	it	it	PRON
cuesj-483	101	36	is	be	AUX
cuesj-483	101	37	able	able	ADJ
cuesj-483	101	38	to	to	PART
cuesj-483	101	39	reduce	reduce	VERB
cuesj-483	101	40	the	the	DET
cuesj-483	101	41	effect	effect	NOUN
cuesj-483	101	42	of	of	ADP
cuesj-483	101	43	outliers	outlier	NOUN
cuesj-483	101	44	on	on	ADP
cuesj-483	101	45	the	the	DET
cuesj-483	101	46	fitting	fitting	ADJ
cuesj-483	101	47	kernel	kernel	PROPN
cuesj-483	101	48	model	model	NOUN
cuesj-483	101	49	.	.	PUNCT
cuesj-483	102	1	2new	2new	ADJ
cuesj-483	102	2	proposed	propose	VERB
cuesj-483	102	3	method	method	NOUN
cuesj-483	102	4	estimator	estimator	NOUN
cuesj-483	102	5	for	for	ADP
cuesj-483	102	6	mad	mad	ADJ
cuesj-483	102	7	was	be	AUX
cuesj-483	102	8	more	more	ADV
cuesj-483	102	9	reliable	reliable	ADJ
cuesj-483	102	10	than	than	ADP
cuesj-483	102	11	any	any	PRON
cuesj-483	102	12	of	of	ADP
cuesj-483	102	13	the	the	DET
cuesj-483	102	14	other	other	ADJ
cuesj-483	102	15	classical	classical	ADJ
cuesj-483	102	16	methods	method	NOUN
cuesj-483	102	17	for	for	ADP
cuesj-483	102	18	both	both	PRON
cuesj-483	102	19	simulation	simulation	NOUN
cuesj-483	102	20	and	and	CCONJ
cuesj-483	102	21	specific	specific	ADJ
cuesj-483	102	22	data	datum	NOUN
cuesj-483	102	23	because	because	SCONJ
cuesj-483	102	24	the	the	DET
cuesj-483	102	25	absolute	absolute	ADJ
cuesj-483	102	26	mean	mean	ADJ
cuesj-483	102	27	difference	difference	NOUN
cuesj-483	102	28	in	in	ADP
cuesj-483	102	29	mad	mad	ADJ
cuesj-483	102	30	gives	give	VERB
cuesj-483	102	31	lower	low	ADJ
cuesj-483	102	32	value	value	NOUN
cuesj-483	102	33	of	of	ADP
cuesj-483	102	34	mse	mse	PROPN
cuesj-483	102	35	.	.	PUNCT
cuesj-483	103	1	figure	figure	NOUN
cuesj-483	103	2	2	2	NUM
cuesj-483	103	3	:	:	PUNCT
cuesj-483	103	4	left	leave	VERB
cuesj-483	103	5	hand	hand	NOUN
cuesj-483	103	6	classical	classical	ADJ
cuesj-483	103	7	methods	method	NOUN
cuesj-483	103	8	and	and	CCONJ
cuesj-483	103	9	right	right	ADJ
cuesj-483	103	10	hand	hand	NOUN
cuesj-483	103	11	new	new	ADJ
cuesj-483	103	12	proposed	propose	VERB
cuesj-483	103	13	methods	method	NOUN
cuesj-483	103	14	at	at	ADP
cuesj-483	103	15	h=0.5	h=0.5	NOUN
cuesj-483	103	16	and	and	CCONJ
cuesj-483	103	17	0.75	0.75	NUM
cuesj-483	103	18	with	with	ADP
cuesj-483	103	19	ample	ample	ADJ
cuesj-483	103	20	size	size	NOUN
cuesj-483	103	21	75	75	NUM
cuesj-483	103	22	,	,	PUNCT
cuesj-483	103	23	(	(	PUNCT
cuesj-483	103	24	a)-x	a)-x	NOUN
cuesj-483	103	25	versus	versus	ADP
cuesj-483	103	26	y	y	PROPN
cuesj-483	103	27	at	at	ADP
cuesj-483	103	28	h=0.5	h=0.5	NOUN
cuesj-483	103	29	and	and	CCONJ
cuesj-483	103	30	n	n	CCONJ
cuesj-483	103	31	=	=	SYM
cuesj-483	103	32	7	7	NUM
cuesj-483	103	33	,	,	PUNCT
cuesj-483	103	34	(	(	PUNCT
cuesj-483	103	35	b)-x	b)-x	NOUN
cuesj-483	103	36	versus	versus	ADP
cuesj-483	103	37	y	y	NOUN
cuesj-483	103	38	at	at	ADP
cuesj-483	103	39	h=0.5	h=0.5	NOUN
cuesj-483	103	40	and	and	CCONJ
cuesj-483	103	41	n	n	CCONJ
cuesj-483	103	42	=	=	NUM
cuesj-483	103	43	75	75	NUM
cuesj-483	103	44	,	,	PUNCT
cuesj-483	103	45	(	(	PUNCT
cuesj-483	103	46	c)-x	c)-x	NOUN
cuesj-483	103	47	versus	versus	ADP
cuesj-483	103	48	y	y	PROPN
cuesj-483	103	49	at	at	ADP
cuesj-483	103	50	h=0.75	h=0.75	PROPN
cuesj-483	103	51	and	and	CCONJ
cuesj-483	103	52	n	n	CCONJ
cuesj-483	103	53	=	=	NUM
cuesj-483	103	54	75	75	NUM
cuesj-483	103	55	,	,	PUNCT
cuesj-483	103	56	(	(	PUNCT
cuesj-483	103	57	d)-x	d)-x	ADP
cuesj-483	103	58	versus	versus	ADP
cuesj-483	103	59	y	y	PROPN
cuesj-483	103	60	at	at	ADP
cuesj-483	103	61	h=0.75	h=0.75	PROPN
cuesj-483	103	62	and	and	CCONJ
cuesj-483	103	63	n	n	CCONJ
cuesj-483	103	64	=	=	SYM
cuesj-483	103	65	75	75	NUM
cuesj-483	103	66	figure	figure	NOUN
cuesj-483	103	67	3	3	NUM
cuesj-483	103	68	:	:	PUNCT
cuesj-483	103	69	left	leave	VERB
cuesj-483	103	70	hand	hand	NOUN
cuesj-483	103	71	classical	classical	ADJ
cuesj-483	103	72	methods	method	NOUN
cuesj-483	103	73	and	and	CCONJ
cuesj-483	103	74	right	right	ADJ
cuesj-483	103	75	hand	hand	NOUN
cuesj-483	103	76	new	new	ADJ
cuesj-483	103	77	proposed	propose	VERB
cuesj-483	103	78	methods	method	NOUN
cuesj-483	103	79	at	at	ADP
cuesj-483	103	80	h=1	h=1	PROPN
cuesj-483	103	81	and	and	CCONJ
cuesj-483	103	82	1.5	1.5	NUM
cuesj-483	103	83	with	with	ADP
cuesj-483	103	84	sample	sample	NOUN
cuesj-483	103	85	size	size	NOUN
cuesj-483	103	86	75	75	NUM
cuesj-483	103	87	,	,	PUNCT
cuesj-483	103	88	(	(	PUNCT
cuesj-483	103	89	a)-x	a)-x	NOUN
cuesj-483	103	90	versus	versus	ADP
cuesj-483	103	91	y	y	PROPN
cuesj-483	103	92	at	at	ADP
cuesj-483	103	93	h=1	h=1	PROPN
cuesj-483	103	94	and	and	CCONJ
cuesj-483	103	95	n	n	CCONJ
cuesj-483	103	96	=	=	SYM
cuesj-483	103	97	75	75	NUM
cuesj-483	103	98	(	(	PUNCT
cuesj-483	103	99	b)-x	b)-x	NOUN
cuesj-483	103	100	versus	versus	ADP
cuesj-483	103	101	y	y	PROPN
cuesj-483	103	102	at	at	ADP
cuesj-483	103	103	h=1	h=1	PROPN
cuesj-483	103	104	and	and	CCONJ
cuesj-483	103	105	n	n	CCONJ
cuesj-483	103	106	=	=	SYM
cuesj-483	103	107	75	75	NUM
cuesj-483	103	108	,	,	PUNCT
cuesj-483	103	109	(	(	PUNCT
cuesj-483	103	110	c)-x	c)-x	NOUN
cuesj-483	103	111	versus	versus	ADP
cuesj-483	103	112	y	y	PROPN
cuesj-483	103	113	at	at	ADP
cuesj-483	103	114	h=1.5	h=1.5	NOUN
cuesj-483	103	115	and	and	CCONJ
cuesj-483	103	116	n	n	CCONJ
cuesj-483	103	117	=	=	SYM
cuesj-483	103	118	75	75	NUM
cuesj-483	103	119	(	(	PUNCT
cuesj-483	103	120	d)-x	d)-x	X
cuesj-483	103	121	versus	versus	ADP
cuesj-483	103	122	y	y	PROPN
cuesj-483	103	123	at	at	ADP
cuesj-483	103	124	h=1.5	h=1.5	NOUN
cuesj-483	103	125	and	and	CCONJ
cuesj-483	103	126	n	n	CCONJ
cuesj-483	103	127	=	=	SYM
cuesj-483	103	128	75	75	NUM
cuesj-483	103	129	table	table	NOUN
cuesj-483	103	130	3	3	NUM
cuesj-483	103	131	:	:	PUNCT
cuesj-483	103	132	mse	mse	NOUN
cuesj-483	103	133	values	value	NOUN
cuesj-483	103	134	between	between	ADP
cuesj-483	103	135	classical	classical	ADJ
cuesj-483	103	136	methods	method	NOUN
cuesj-483	103	137	and	and	CCONJ
cuesj-483	103	138	new	new	ADJ
cuesj-483	103	139	proposed	propose	VERB
cuesj-483	103	140	methods	method	NOUN
cuesj-483	103	141	of	of	ADP
cuesj-483	103	142	nwk	nwk	NOUN
cuesj-483	103	143	estimators	estimator	NOUN
cuesj-483	103	144	in	in	ADP
cuesj-483	103	145	simulation	simulation	NOUN
cuesj-483	103	146	data	data	PROPN
cuesj-483	103	147	h	h	PROPN
cuesj-483	103	148	n	n	PRON
cuesj-483	103	149	fixed	fix	VERB
cuesj-483	103	150	nw	nw	PROPN
cuesj-483	103	151	variable	variable	PROPN
cuesj-483	103	152	nw	nw	PROPN
cuesj-483	103	153	g	g	PROPN
cuesj-483	103	154	anw	anw	PROPN
cuesj-483	103	155	m	m	VERB
cuesj-483	104	1	anw	anw	INTJ
cuesj-483	105	1	me	i	PRON
cuesj-483	106	1	anw	anw	INTJ
cuesj-483	106	2	r	r	NOUN
cuesj-483	106	3	anw	anw	PROPN
cuesj-483	106	4	iqr	iqr	PROPN
cuesj-483	106	5	anw	anw	PROPN
cuesj-483	107	1	sd	sd	ADP
cuesj-483	107	2	anw	anw	PROPN
cuesj-483	107	3	mad	mad	ADJ
cuesj-483	107	4	anw	anw	PROPN
cuesj-483	107	5	mead	mead	NOUN
cuesj-483	107	6	0.5	0.5	NUM
cuesj-483	107	7	25	25	NUM
cuesj-483	107	8	1.1997	1.1997	NUM
cuesj-483	107	9	1.2769	1.2769	NUM
cuesj-483	107	10	1.3439	1.3439	NUM
cuesj-483	107	11	1.3116	1.3116	NUM
cuesj-483	107	12	1.7164	1.7164	NUM
cuesj-483	107	13	1.0449	1.0449	NUM
cuesj-483	107	14	1.0124	1.0124	NUM
cuesj-483	107	15	0.9336	0.9336	NUM
cuesj-483	107	16	0.9317	0.9317	NUM
cuesj-483	107	17	50	50	NUM
cuesj-483	107	18	1.5189	1.5189	NUM
cuesj-483	107	19	1.5314	1.5314	NUM
cuesj-483	107	20	1.6769	1.6769	NUM
cuesj-483	107	21	1.4909	1.4909	NUM
cuesj-483	107	22	2.2494	2.2494	NUM
cuesj-483	107	23	1.5075	1.5075	NUM
cuesj-483	107	24	1.5106	1.5106	NUM
cuesj-483	107	25	1.4193	1.4193	NUM
cuesj-483	107	26	1.3552	1.3552	NUM
cuesj-483	107	27	75	75	NUM
cuesj-483	107	28	1.3763	1.3763	NUM
cuesj-483	107	29	1.5314	1.5314	NUM
cuesj-483	107	30	1.6357	1.6357	NUM
cuesj-483	107	31	1.4530	1.4530	NUM
cuesj-483	107	32	2.1951	2.1951	NUM
cuesj-483	107	33	1.3629	1.3629	NUM
cuesj-483	107	34	1.4166	1.4166	NUM
cuesj-483	107	35	1.3108	1.3108	NUM
cuesj-483	107	36	1.2386	1.2386	NUM
cuesj-483	107	37	150	150	NUM
cuesj-483	107	38	1.3899	1.3899	NUM
cuesj-483	107	39	1.5314	1.5314	NUM
cuesj-483	107	40	1.6141	1.6141	NUM
cuesj-483	107	41	1.3753	1.3753	NUM
cuesj-483	107	42	2.3476	2.3476	NUM
cuesj-483	107	43	1.1274	1.1274	NUM
cuesj-483	107	44	1.3872	1.3872	NUM
cuesj-483	108	1	1.2582	1.2582	NUM
cuesj-483	108	2	1.1485	1.1485	NUM
cuesj-483	108	3	0.75	0.75	NUM
cuesj-483	108	4	25	25	NUM
cuesj-483	108	5	1.7391	1.7391	NUM
cuesj-483	108	6	1.5314	1.5314	NUM
cuesj-483	108	7	1.8532	1.8532	NUM
cuesj-483	108	8	1.8887	1.8887	NUM
cuesj-483	108	9	2.1838	2.1838	NUM
cuesj-483	108	10	1.2308	1.2308	NUM
cuesj-483	108	11	1.5290	1.5290	NUM
cuesj-483	108	12	1.3999	1.3999	NUM
cuesj-483	108	13	1.3796	1.3796	NUM
cuesj-483	108	14	50	50	NUM
cuesj-483	108	15	1.9968	1.9968	NUM
cuesj-483	108	16	1.5314	1.5314	NUM
cuesj-483	108	17	2.1020	2.1020	NUM
cuesj-483	108	18	1.9050	1.9050	NUM
cuesj-483	108	19	2.5395	2.5395	NUM
cuesj-483	108	20	1.9694	1.9694	NUM
cuesj-483	108	21	1.7755	1.7755	NUM
cuesj-483	108	22	1.6786	1.6786	NUM
cuesj-483	108	23	1.6309	1.6309	NUM
cuesj-483	108	24	75	75	NUM
cuesj-483	108	25	1.9562	1.9562	NUM
cuesj-483	108	26	1.5314	1.5314	NUM
cuesj-483	108	27	2.1081	2.1081	NUM
cuesj-483	108	28	1.9022	1.9022	NUM
cuesj-483	108	29	2.5044	2.5044	NUM
cuesj-483	108	30	1.8816	1.8816	NUM
cuesj-483	108	31	1.6998	1.6998	NUM
cuesj-483	108	32	1.5897	1.5897	NUM
cuesj-483	108	33	1.5259	1.5259	NUM
cuesj-483	108	34	150	150	NUM
cuesj-483	108	35	1.9938	1.9938	NUM
cuesj-483	108	36	1.5314	1.5314	NUM
cuesj-483	108	37	2.1887	2.1887	NUM
cuesj-483	108	38	1.8970	1.8970	NUM
cuesj-483	108	39	2.7280	2.7280	NUM
cuesj-483	108	40	1.6904	1.6904	NUM
cuesj-483	108	41	1.6997	1.6997	NUM
cuesj-483	108	42	1.5504	1.5504	NUM
cuesj-483	108	43	1.4423	1.4423	NUM
cuesj-483	108	44	1	1	NUM
cuesj-483	108	45	25	25	NUM
cuesj-483	108	46	2.1124	2.1124	NUM
cuesj-483	108	47	1.5314	1.5314	NUM
cuesj-483	108	48	2.1651	2.1651	NUM
cuesj-483	108	49	2.1877	2.1877	NUM
cuesj-483	108	50	2.3063	2.3063	NUM
cuesj-483	108	51	1.6398	1.6398	NUM
cuesj-483	108	52	1.6593	1.6593	NUM
cuesj-483	108	53	1.5147	1.5147	NUM
cuesj-483	108	54	1.5114	1.5114	NUM
cuesj-483	108	55	50	50	NUM
cuesj-483	108	56	2.4127	2.4127	NUM
cuesj-483	108	57	1.5314	1.5314	NUM
cuesj-483	108	58	2.4600	2.4600	NUM
cuesj-483	108	59	2.3296	2.3296	NUM
cuesj-483	108	60	2.7635	2.7635	NUM
cuesj-483	108	61	2.2906	2.2906	NUM
cuesj-483	108	62	1.9823	1.9823	NUM
cuesj-483	108	63	1.8860	1.8860	NUM
cuesj-483	108	64	1.8617	1.8617	NUM
cuesj-483	108	65	75	75	NUM
cuesj-483	108	66	2.4083	2.4083	NUM
cuesj-483	108	67	1.5314	1.5314	NUM
cuesj-483	108	68	2.4799	2.4799	NUM
cuesj-483	108	69	2.3478	2.3478	NUM
cuesj-483	108	70	2.7244	2.7244	NUM
cuesj-483	108	71	2.2515	2.2515	NUM
cuesj-483	108	72	1.9349	1.9349	NUM
cuesj-483	108	73	1.8337	1.8337	NUM
cuesj-483	108	74	1.7994	1.7994	NUM
cuesj-483	108	75	150	150	NUM
cuesj-483	108	76	2.5004	2.5004	NUM
cuesj-483	108	77	1.5314	1.5314	NUM
cuesj-483	108	78	2.6277	2.6277	NUM
cuesj-483	108	79	2.4347	2.4347	NUM
cuesj-483	108	80	2.9452	2.9452	NUM
cuesj-483	108	81	2.1524	2.1524	NUM
cuesj-483	108	82	1.9254	1.9254	NUM
cuesj-483	108	83	1.7770	1.7770	NUM
cuesj-483	108	84	1.7158	1.7158	NUM
cuesj-483	108	85	1.5	1.5	NUM
cuesj-483	108	86	25	25	NUM
cuesj-483	108	87	2.4158	2.4158	NUM
cuesj-483	108	88	1.5314	1.5314	NUM
cuesj-483	108	89	2.4393	2.4393	NUM
cuesj-483	108	90	2.4446	2.4446	NUM
cuesj-483	108	91	2.4028	2.4028	NUM
cuesj-483	108	92	2.0489	2.0489	NUM
cuesj-483	108	93	1.8624	1.8624	NUM
cuesj-483	108	94	1.7373	1.7373	NUM
cuesj-483	108	95	1.7350	1.7350	NUM
cuesj-483	108	96	50	50	NUM
cuesj-483	108	97	3.0111	3.0111	NUM
cuesj-483	108	98	1.5314	1.5314	NUM
cuesj-483	108	99	3.0178	3.0178	NUM
cuesj-483	108	100	2.9693	2.9693	NUM
cuesj-483	108	101	3.0401	3.0401	NUM
cuesj-483	108	102	2.5985	2.5985	NUM
cuesj-483	108	103	2.2131	2.2131	NUM
cuesj-483	108	104	2.1163	2.1163	NUM
cuesj-483	108	105	2.1072	2.1072	NUM
cuesj-483	108	106	75	75	NUM
cuesj-483	108	107	2.9941	2.9941	NUM
cuesj-483	108	108	1.5314	1.5314	NUM
cuesj-483	108	109	3.0051	3.0051	NUM
cuesj-483	108	110	2.9563	2.9563	NUM
cuesj-483	108	111	2.9868	2.9868	NUM
cuesj-483	108	112	2.5805	2.5805	NUM
cuesj-483	108	113	2.1996	2.1996	NUM
cuesj-483	108	114	2.1043	2.1043	NUM
cuesj-483	108	115	2.0916	2.0916	NUM
cuesj-483	108	116	150	150	NUM
cuesj-483	108	117	3.1563	3.1563	NUM
cuesj-483	108	118	1.5314	1.5314	NUM
cuesj-483	108	119	3.2067	3.2067	NUM
cuesj-483	108	120	3.1444	3.1444	NUM
cuesj-483	108	121	3.1738	3.1738	NUM
cuesj-483	108	122	2.5569	2.5569	NUM
cuesj-483	108	123	2.1742	2.1742	NUM
cuesj-483	108	124	2.0404	2.0404	NUM
cuesj-483	108	125	2.0173	2.0173	NUM
cuesj-483	108	126	dc	dc	PROPN
cuesj-483	108	127	ba	ba	PROPN
cuesj-483	108	128	dc	dc	PROPN
cuesj-483	108	129	ba	ba	PROPN
cuesj-483	108	130	blbas	blbas	PROPN
cuesj-483	108	131	and	and	CCONJ
cuesj-483	108	132	kahwachi	kahwachi	PROPN
cuesj-483	108	133	:	:	PUNCT
cuesj-483	108	134	new	new	ADJ
cuesj-483	108	135	modification	modification	NOUN
cuesj-483	108	136	of	of	ADP
cuesj-483	108	137	anwk	anwk	NOUN
cuesj-483	108	138	in	in	ADP
cuesj-483	108	139	nonparametric	nonparametric	PROPN
cuesj-483	108	140	regression	regression	NOUN
cuesj-483	108	141	37	37	NUM
cuesj-483	108	142	http://journals.cihanuniversity.edu.iq/index.php/cuesj	http://journals.cihanuniversity.edu.iq/index.php/cuesj	ADJ
cuesj-483	108	143	cuesj	cuesj	ADJ
cuesj-483	108	144	2021	2021	NUM
cuesj-483	108	145	,	,	PUNCT
cuesj-483	108	146	5	5	NUM
cuesj-483	108	147	(	(	PUNCT
cuesj-483	108	148	2	2	NUM
cuesj-483	108	149	):	):	PUNCT
cuesj-483	108	150	32	32	NUM
cuesj-483	108	151	-	-	SYM
cuesj-483	108	152	37	37	NUM
cuesj-483	108	153	3new	3new	NUM
cuesj-483	108	154	proposed	propose	VERB
cuesj-483	108	155	method	method	NOUN
cuesj-483	108	156	estimator	estimator	NOUN
cuesj-483	108	157	for	for	ADP
cuesj-483	108	158	sd	sd	NOUN
cuesj-483	108	159	was	be	AUX
cuesj-483	108	160	more	more	ADV
cuesj-483	108	161	reliable	reliable	ADJ
cuesj-483	108	162	than	than	ADP
cuesj-483	108	163	any	any	PRON
cuesj-483	108	164	of	of	ADP
cuesj-483	108	165	the	the	DET
cuesj-483	108	166	other	other	ADJ
cuesj-483	108	167	classical	classical	ADJ
cuesj-483	108	168	methods	method	NOUN
cuesj-483	108	169	for	for	ADP
cuesj-483	108	170	both	both	DET
cuesj-483	108	171	simulation	simulation	NOUN
cuesj-483	108	172	and	and	CCONJ
cuesj-483	108	173	current	current	ADJ
cuesj-483	108	174	data	datum	NOUN
cuesj-483	108	175	using	use	VERB
cuesj-483	108	176	mse	mse	NOUN
cuesj-483	108	177	criteria	criterion	NOUN
cuesj-483	108	178	.	.	PUNCT
cuesj-483	109	1	4new	4new	PROPN
cuesj-483	109	2	proposed	propose	VERB
cuesj-483	109	3	method	method	NOUN
cuesj-483	109	4	estimator	estimator	NOUN
cuesj-483	109	5	for	for	ADP
cuesj-483	109	6	iqr	iqr	PROPN
cuesj-483	109	7	was	be	AUX
cuesj-483	109	8	more	more	ADV
cuesj-483	109	9	reliable	reliable	ADJ
cuesj-483	109	10	than	than	ADP
cuesj-483	109	11	any	any	PRON
cuesj-483	109	12	of	of	ADP
cuesj-483	109	13	the	the	DET
cuesj-483	109	14	other	other	ADJ
cuesj-483	109	15	classical	classical	ADJ
cuesj-483	109	16	methods	method	NOUN
cuesj-483	109	17	for	for	ADP
cuesj-483	109	18	both	both	PRON
cuesj-483	109	19	simulation	simulation	NOUN
cuesj-483	109	20	and	and	CCONJ
cuesj-483	109	21	real	real	ADJ
cuesj-483	109	22	data	datum	NOUN
cuesj-483	109	23	based	base	VERB
cuesj-483	109	24	on	on	ADP
cuesj-483	109	25	mse	mse	NOUN
cuesj-483	109	26	criteria	criterion	NOUN
cuesj-483	109	27	.	.	PUNCT
cuesj-483	110	1	5median	5median	NUM
cuesj-483	110	2	absolute	absolute	ADJ
cuesj-483	110	3	deviation	deviation	NOUN
cuesj-483	110	4	(	(	PUNCT
cuesj-483	110	5	mead	mead	NOUN
cuesj-483	110	6	)	)	PUNCT
cuesj-483	110	7	has	have	VERB
cuesj-483	110	8	less	less	ADJ
cuesj-483	110	9	mse	mse	NOUN
cuesj-483	110	10	than	than	ADP
cuesj-483	110	11	mad	mad	ADJ
cuesj-483	110	12	,	,	PUNCT
cuesj-483	110	13	in	in	ADP
cuesj-483	110	14	turn	turn	NOUN
cuesj-483	110	15	mad	mad	ADJ
cuesj-483	110	16	is	be	AUX
cuesj-483	110	17	less	less	ADJ
cuesj-483	110	18	than	than	ADP
cuesj-483	110	19	sd	sd	NOUN
cuesj-483	110	20	,	,	PUNCT
cuesj-483	110	21	and	and	CCONJ
cuesj-483	110	22	sd	sd	NOUN
cuesj-483	110	23	is	be	AUX
cuesj-483	110	24	less	less	ADJ
cuesj-483	110	25	than	than	ADP
cuesj-483	110	26	iqr	iqr	PROPN
cuesj-483	110	27	in	in	ADP
cuesj-483	110	28	different	different	ADJ
cuesj-483	110	29	bandwidth	bandwidth	NOUN
cuesj-483	110	30	and	and	CCONJ
cuesj-483	110	31	sample	sample	NOUN
cuesj-483	110	32	size	size	NOUN
cuesj-483	110	33	in	in	ADP
cuesj-483	110	34	either	either	PRON
cuesj-483	110	35	simulation	simulation	NOUN
cuesj-483	110	36	or	or	CCONJ
cuesj-483	110	37	real	real	ADJ
cuesj-483	110	38	data	datum	NOUN
cuesj-483	110	39	.	.	PUNCT
cuesj-483	111	1	6	6	NUM
cuesj-483	111	2	in	in	ADP
cuesj-483	111	3	both	both	PRON
cuesj-483	111	4	simulation	simulation	NOUN
cuesj-483	111	5	and	and	CCONJ
cuesj-483	111	6	real	real	ADJ
cuesj-483	111	7	data	datum	NOUN
cuesj-483	111	8	,	,	PUNCT
cuesj-483	111	9	both	both	DET
cuesj-483	111	10	proposed	propose	VERB
cuesj-483	111	11	and	and	CCONJ
cuesj-483	111	12	classical	classical	ADJ
cuesj-483	111	13	methods	method	NOUN
cuesj-483	111	14	are	be	AUX
cuesj-483	111	15	improved	improve	VERB
cuesj-483	111	16	by	by	ADP
cuesj-483	111	17	reducing	reduce	VERB
cuesj-483	111	18	the	the	DET
cuesj-483	111	19	initial	initial	ADJ
cuesj-483	111	20	bandwidth	bandwidth	ADJ
cuesj-483	111	21	values	value	NOUN
cuesj-483	111	22	and	and	CCONJ
cuesj-483	111	23	sample	sample	NOUN
cuesj-483	111	24	size	size	NOUN
cuesj-483	111	25	.	.	PUNCT
cuesj-483	112	1	reerences	reerence	NOUN
cuesj-483	112	2	1	1	NUM
cuesj-483	112	3	.	.	PUNCT
cuesj-483	112	4	m.	m.	NOUN
cuesj-483	112	5	hollander	hollander	PROPN
cuesj-483	112	6	,	,	PUNCT
cuesj-483	112	7	d.	d.	PROPN
cuesj-483	112	8	a.	a.	PROPN
cuesj-483	112	9	wolfe	wolfe	PROPN
cuesj-483	112	10	and	and	CCONJ
cuesj-483	112	11	e.	e.	PROPN
cuesj-483	112	12	chicken	chicken	PROPN
cuesj-483	112	13	.	.	PUNCT
cuesj-483	113	1	nonparametric	nonparametric	ADJ
cuesj-483	113	2	statistical	statistical	ADJ
cuesj-483	113	3	methods	method	NOUN
cuesj-483	113	4	.	.	PUNCT
cuesj-483	114	1	john	john	PROPN
cuesj-483	114	2	wiley	wiley	PROPN
cuesj-483	114	3	&	&	CCONJ
cuesj-483	114	4	sons	sons	PROPN
cuesj-483	114	5	,	,	PUNCT
cuesj-483	114	6	inc	inc	PROPN
cuesj-483	114	7	.	.	PROPN
cuesj-483	114	8	,	,	PUNCT
cuesj-483	114	9	hoboken	hoboken	PROPN
cuesj-483	114	10	,	,	PUNCT
cuesj-483	114	11	new	new	PROPN
cuesj-483	114	12	jersey	jersey	PROPN
cuesj-483	114	13	,	,	PUNCT
cuesj-483	114	14	2014	2014	NUM
cuesj-483	114	15	.	.	PUNCT
cuesj-483	115	1	2	2	NUM
cuesj-483	115	2	.	.	X
cuesj-483	115	3	w.	w.	PROPN
cuesj-483	115	4	härdle	härdle	PROPN
cuesj-483	115	5	.	.	PUNCT
cuesj-483	116	1	applied	apply	VERB
cuesj-483	116	2	nonparametric	nonparametric	PROPN
cuesj-483	116	3	regression	regression	NOUN
cuesj-483	116	4	.	.	PUNCT
cuesj-483	117	1	cambridge	cambridge	PROPN
cuesj-483	117	2	university	university	PROPN
cuesj-483	117	3	press	press	PROPN
cuesj-483	117	4	,	,	PUNCT
cuesj-483	117	5	cambridge	cambridge	PROPN
cuesj-483	117	6	,	,	PUNCT
cuesj-483	117	7	england	england	PROPN
cuesj-483	117	8	,	,	PUNCT
cuesj-483	117	9	new	new	PROPN
cuesj-483	117	10	york	york	PROPN
cuesj-483	117	11	,	,	PUNCT
cuesj-483	117	12	1997	1997	NUM
cuesj-483	117	13	.	.	PUNCT
cuesj-483	118	1	3	3	X
cuesj-483	118	2	.	.	X
cuesj-483	118	3	m.	m.	NOUN
cuesj-483	118	4	memmedli	memmedli	PROPN
cuesj-483	118	5	and	and	CCONJ
cuesj-483	118	6	m.	m.	PROPN
cuesj-483	118	7	yildiz	yildiz	PROPN
cuesj-483	118	8	.	.	PUNCT
cuesj-483	119	1	comparison	comparison	NOUN
cuesj-483	119	2	study	study	NOUN
cuesj-483	119	3	on	on	ADP
cuesj-483	119	4	smoothing	smooth	VERB
cuesj-483	119	5	parameter	parameter	NOUN
cuesj-483	119	6	and	and	CCONJ
cuesj-483	119	7	sample	sample	NOUN
cuesj-483	119	8	size	size	NOUN
cuesj-483	119	9	in	in	ADP
cuesj-483	119	10	nonparametric	nonparametric	NOUN
cuesj-483	119	11	fuzzy	fuzzy	ADJ
cuesj-483	119	12	local	local	ADJ
cuesj-483	119	13	polynomial	polynomial	ADJ
cuesj-483	119	14	regression	regression	NOUN
cuesj-483	119	15	models	model	NOUN
cuesj-483	119	16	.	.	PUNCT
cuesj-483	120	1	in	in	ADP
cuesj-483	120	2	:	:	PUNCT
cuesj-483	120	3	2012	2012	NUM
cuesj-483	120	4	iv	iv	NUM
cuesj-483	120	5	international	international	ADJ
cuesj-483	120	6	conference	conference	NOUN
cuesj-483	120	7	“	"	PUNCT
cuesj-483	120	8	problems	problem	NOUN
cuesj-483	120	9	of	of	ADP
cuesj-483	120	10	cybernetics	cybernetic	NOUN
cuesj-483	120	11	and	and	CCONJ
cuesj-483	120	12	informatics	informatic	NOUN
cuesj-483	120	13	”	"	PUNCT
cuesj-483	120	14	(	(	PUNCT
cuesj-483	120	15	pci	pci	PROPN
cuesj-483	120	16	)	)	PUNCT
cuesj-483	120	17	,	,	PUNCT
cuesj-483	120	18	2012	2012	NUM
cuesj-483	120	19	.	.	PUNCT
cuesj-483	121	1	4	4	X
cuesj-483	121	2	.	.	X
cuesj-483	121	3	w.	w.	NOUN
cuesj-483	121	4	hardle	hardle	PROPN
cuesj-483	121	5	.	.	PUNCT
cuesj-483	122	1	applied	apply	VERB
cuesj-483	122	2	nonparametric	nonparametric	ADJ
cuesj-483	122	3	regression	regression	NOUN
cuesj-483	122	4	.	.	PUNCT
cuesj-483	123	1	biometrics	biometric	NOUN
cuesj-483	123	2	,	,	PUNCT
cuesj-483	123	3	vol	vol	NOUN
cuesj-483	123	4	.	.	PROPN
cuesj-483	123	5	50	50	NUM
cuesj-483	123	6	,	,	PUNCT
cuesj-483	123	7	no	no	INTJ
cuesj-483	123	8	.	.	NOUN
cuesj-483	123	9	2	2	NUM
cuesj-483	123	10	,	,	PUNCT
cuesj-483	123	11	p.	p.	NOUN
cuesj-483	123	12	592	592	NUM
cuesj-483	123	13	,	,	PUNCT
cuesj-483	123	14	1994	1994	NUM
cuesj-483	123	15	.	.	PUNCT
cuesj-483	124	1	5	5	NUM
cuesj-483	124	2	.	.	PUNCT
cuesj-483	124	3	a.	a.	NOUN
cuesj-483	124	4	christmann	christmann	PROPN
cuesj-483	124	5	and	and	CCONJ
cuesj-483	124	6	i.	i.	PROPN
cuesj-483	124	7	steinwart	steinwart	PROPN
cuesj-483	124	8	.	.	PUNCT
cuesj-483	125	1	consistency	consistency	NOUN
cuesj-483	125	2	and	and	CCONJ
cuesj-483	125	3	robustness	robustness	NOUN
cuesj-483	125	4	of	of	ADP
cuesj-483	125	5	kernel	kernel	NOUN
cuesj-483	125	6	-	-	PUNCT
cuesj-483	125	7	based	base	VERB
cuesj-483	125	8	regression	regression	NOUN
cuesj-483	125	9	in	in	ADP
cuesj-483	125	10	convex	convex	ADJ
cuesj-483	125	11	risk	risk	NOUN
cuesj-483	125	12	minimization	minimization	NOUN
cuesj-483	125	13	.	.	PUNCT
cuesj-483	126	1	bernoulli	bernoulli	PROPN
cuesj-483	126	2	,	,	PUNCT
cuesj-483	126	3	vol	vol	NOUN
cuesj-483	126	4	.	.	PROPN
cuesj-483	126	5	13	13	NUM
cuesj-483	126	6	,	,	PUNCT
cuesj-483	126	7	no	no	INTJ
cuesj-483	126	8	.	.	NOUN
cuesj-483	126	9	3	3	NUM
cuesj-483	126	10	,	,	PUNCT
cuesj-483	126	11	pp	pp	ADJ
cuesj-483	126	12	.	.	PUNCT
cuesj-483	127	1	799	799	NUM
cuesj-483	127	2	-	-	SYM
cuesj-483	127	3	819	819	NUM
cuesj-483	127	4	,	,	PUNCT
cuesj-483	127	5	2007	2007	NUM
cuesj-483	127	6	.	.	PUNCT
cuesj-483	128	1	6	6	NUM
cuesj-483	128	2	.	.	PUNCT
cuesj-483	128	3	e.	e.	PROPN
cuesj-483	128	4	a.	a.	PROPN
cuesj-483	128	5	nadaraya	nadaraya	PROPN
cuesj-483	128	6	.	.	PUNCT
cuesj-483	129	1	on	on	ADP
cuesj-483	129	2	estimating	estimate	VERB
cuesj-483	129	3	regression	regression	NOUN
cuesj-483	129	4	.	.	PUNCT
cuesj-483	130	1	theory	theory	NOUN
cuesj-483	130	2	of	of	ADP
cuesj-483	130	3	probability	probability	NOUN
cuesj-483	130	4	and	and	CCONJ
cuesj-483	130	5	its	its	PRON
cuesj-483	130	6	applications	application	NOUN
cuesj-483	130	7	,	,	PUNCT
cuesj-483	130	8	vol	vol	NOUN
cuesj-483	130	9	.	.	PROPN
cuesj-483	130	10	9	9	NUM
cuesj-483	130	11	,	,	PUNCT
cuesj-483	130	12	no	no	INTJ
cuesj-483	130	13	.	.	NOUN
cuesj-483	130	14	1	1	NUM
cuesj-483	130	15	,	,	PUNCT
cuesj-483	130	16	pp	pp	ADJ
cuesj-483	130	17	.	.	PUNCT
cuesj-483	131	1	141	141	NUM
cuesj-483	131	2	-	-	SYM
cuesj-483	131	3	142	142	NUM
cuesj-483	131	4	,	,	PUNCT
cuesj-483	131	5	1964	1964	NUM
cuesj-483	131	6	.	.	PUNCT
cuesj-483	132	1	7	7	X
cuesj-483	132	2	.	.	X
cuesj-483	132	3	g.	g.	PROPN
cuesj-483	132	4	s.	s.	PROPN
cuesj-483	132	5	watson	watson	PROPN
cuesj-483	132	6	.	.	PUNCT
cuesj-483	133	1	smooth	smooth	ADJ
cuesj-483	133	2	regression	regression	NOUN
cuesj-483	133	3	analysis	analysis	NOUN
cuesj-483	133	4	,	,	PUNCT
cuesj-483	133	5	sankhya	sankhya	VERB
cuesj-483	133	6	the	the	DET
cuesj-483	133	7	indian	indian	ADJ
cuesj-483	133	8	journal	journal	PROPN
cuesj-483	133	9	of	of	ADP
cuesj-483	133	10	statistics	statistics	PROPN
cuesj-483	133	11	series	series	PROPN
cuesj-483	133	12	a	a	PRON
cuesj-483	133	13	,	,	PUNCT
cuesj-483	133	14	vol	vol	NOUN
cuesj-483	133	15	.	.	PROPN
cuesj-483	133	16	26	26	NUM
cuesj-483	133	17	,	,	PUNCT
cuesj-483	133	18	no	no	INTJ
cuesj-483	133	19	.	.	NOUN
cuesj-483	133	20	4	4	NUM
cuesj-483	133	21	,	,	PUNCT
cuesj-483	133	22	pp	pp	ADJ
cuesj-483	133	23	.	.	PUNCT
cuesj-483	134	1	359	359	NUM
cuesj-483	134	2	-	-	SYM
cuesj-483	134	3	372	372	NUM
cuesj-483	134	4	,	,	PUNCT
cuesj-483	134	5	1964	1964	NUM
cuesj-483	134	6	.	.	PUNCT
cuesj-483	135	1	8	8	NUM
cuesj-483	135	2	.	.	X
cuesj-483	135	3	m.	m.	NOUN
cuesj-483	135	4	p.	p.	NOUN
cuesj-483	135	5	wand	wand	PROPN
cuesj-483	135	6	and	and	CCONJ
cuesj-483	135	7	m.	m.	PROPN
cuesj-483	135	8	c.	c.	PROPN
cuesj-483	135	9	jones	jones	PROPN
cuesj-483	135	10	,	,	PUNCT
cuesj-483	135	11	kernel	kernel	PROPN
cuesj-483	135	12	smoothing	smoothing	NOUN
cuesj-483	135	13	.	.	PUNCT
cuesj-483	136	1	springer	springer	PROPN
cuesj-483	136	2	,	,	PUNCT
cuesj-483	136	3	boston	boston	PROPN
cuesj-483	136	4	,	,	PUNCT
cuesj-483	136	5	ma	ma	PROPN
cuesj-483	136	6	,	,	PUNCT
cuesj-483	136	7	1995	1995	NUM
cuesj-483	136	8	.	.	PUNCT
cuesj-483	137	1	9	9	NUM
cuesj-483	137	2	.	.	PUNCT
cuesj-483	137	3	h.	h.	PROPN
cuesj-483	137	4	takeda	takeda	PROPN
cuesj-483	137	5	,	,	PUNCT
cuesj-483	137	6	s.	s.	PROPN
cuesj-483	137	7	farsiu	farsiu	PROPN
cuesj-483	137	8	and	and	CCONJ
cuesj-483	137	9	p.	p.	PROPN
cuesj-483	137	10	milanfar	milanfar	PROPN
cuesj-483	137	11	.	.	PUNCT
cuesj-483	138	1	kernel	kernel	PROPN
cuesj-483	138	2	regression	regression	PROPN
cuesj-483	138	3	for	for	ADP
cuesj-483	138	4	image	image	NOUN
cuesj-483	138	5	processing	processing	NOUN
cuesj-483	138	6	and	and	CCONJ
cuesj-483	138	7	reconstruction	reconstruction	NOUN
cuesj-483	138	8	.	.	PUNCT
cuesj-483	139	1	ieee	ieee	NOUN
cuesj-483	139	2	transactions	transaction	NOUN
cuesj-483	139	3	on	on	ADP
cuesj-483	139	4	image	image	NOUN
cuesj-483	139	5	processing	processing	NOUN
cuesj-483	139	6	,	,	PUNCT
cuesj-483	139	7	vol	vol	NOUN
cuesj-483	139	8	.	.	PROPN
cuesj-483	140	1	16	16	NUM
cuesj-483	140	2	,	,	PUNCT
cuesj-483	140	3	no	no	INTJ
cuesj-483	140	4	.	.	NOUN
cuesj-483	140	5	2	2	NUM
cuesj-483	140	6	,	,	PUNCT
cuesj-483	140	7	pp	pp	ADJ
cuesj-483	140	8	.	.	PUNCT
cuesj-483	141	1	349	349	NUM
cuesj-483	141	2	-	-	SYM
cuesj-483	141	3	366	366	NUM
cuesj-483	141	4	,	,	PUNCT
cuesj-483	141	5	2007	2007	NUM
cuesj-483	141	6	.	.	PUNCT
cuesj-483	142	1	10	10	NUM
cuesj-483	142	2	.	.	PUNCT
cuesj-483	143	1	w.	w.	PROPN
cuesj-483	143	2	l.	l.	PROPN
cuesj-483	143	3	martínez	martínez	PROPN
cuesj-483	143	4	and	and	CCONJ
cuesj-483	143	5	a.	a.	PROPN
cuesj-483	143	6	r.	r.	PROPN
cuesj-483	143	7	martínez	martínez	PROPN
cuesj-483	143	8	.	.	PUNCT
cuesj-483	144	1	computational	computational	ADJ
cuesj-483	144	2	statistics	statistic	NOUN
cuesj-483	144	3	handbook	handbook	NOUN
cuesj-483	144	4	with	with	ADP
cuesj-483	144	5	matlab	matlab	PROPN
cuesj-483	144	6	.	.	PUNCT
cuesj-483	145	1	chapman	chapman	PROPN
cuesj-483	145	2	&	&	CCONJ
cuesj-483	145	3	hall	hall	PROPN
cuesj-483	145	4	,	,	PUNCT
cuesj-483	145	5	london	london	PROPN
cuesj-483	145	6	,	,	PUNCT
cuesj-483	145	7	2008	2008	NUM
cuesj-483	145	8	.	.	PUNCT
cuesj-483	146	1	11	11	NUM
cuesj-483	146	2	.	.	PUNCT
cuesj-483	146	3	d.	d.	PROPN
cuesj-483	146	4	conn	conn	PROPN
cuesj-483	146	5	and	and	CCONJ
cuesj-483	146	6	g.	g.	PROPN
cuesj-483	146	7	li	li	PROPN
cuesj-483	146	8	.	.	PUNCT
cuesj-483	147	1	an	an	DET
cuesj-483	147	2	oracle	oracle	NOUN
cuesj-483	147	3	property	property	NOUN
cuesj-483	147	4	of	of	ADP
cuesj-483	147	5	the	the	DET
cuesj-483	147	6	nadaraya	nadaraya	PROPN
cuesj-483	147	7	-	-	PUNCT
cuesj-483	147	8	watson	watson	PROPN
cuesj-483	147	9	kernel	kernel	PROPN
cuesj-483	147	10	estimator	estimator	NOUN
cuesj-483	147	11	for	for	ADP
cuesj-483	147	12	high	high	ADJ
cuesj-483	147	13	–	–	PUNCT
cuesj-483	147	14	dimensional	dimensional	ADJ
cuesj-483	147	15	nonparametric	nonparametric	NOUN
cuesj-483	147	16	regression	regression	NOUN
cuesj-483	147	17	.	.	PUNCT
cuesj-483	148	1	scandinavian	scandinavian	ADJ
cuesj-483	148	2	journal	journal	PROPN
cuesj-483	148	3	of	of	ADP
cuesj-483	148	4	statistics	statistic	NOUN
cuesj-483	148	5	,	,	PUNCT
cuesj-483	148	6	vol	vol	NOUN
cuesj-483	148	7	.	.	PROPN
cuesj-483	148	8	46	46	NUM
cuesj-483	148	9	,	,	PUNCT
cuesj-483	148	10	no	no	INTJ
cuesj-483	148	11	.	.	NOUN
cuesj-483	148	12	3	3	NUM
cuesj-483	148	13	,	,	PUNCT
cuesj-483	148	14	pp	pp	ADJ
cuesj-483	148	15	.	.	PUNCT
cuesj-483	149	1	735	735	NUM
cuesj-483	149	2	-	-	SYM
cuesj-483	149	3	764	764	NUM
cuesj-483	149	4	,	,	PUNCT
cuesj-483	149	5	2018	2018	NUM
cuesj-483	149	6	.	.	PUNCT
cuesj-483	150	1	12	12	NUM
cuesj-483	150	2	.	.	PUNCT
cuesj-483	150	3	b.	b.	PROPN
cuesj-483	150	4	w.	w.	PROPN
cuesj-483	150	5	silverman	silverman	PROPN
cuesj-483	150	6	.	.	PUNCT
cuesj-483	151	1	density	density	NOUN
cuesj-483	151	2	estimation	estimation	NOUN
cuesj-483	151	3	for	for	ADP
cuesj-483	151	4	statistics	statistic	NOUN
cuesj-483	151	5	and	and	CCONJ
cuesj-483	151	6	data	datum	NOUN
cuesj-483	151	7	analysis	analysis	NOUN
cuesj-483	151	8	estimation	estimation	NOUN
cuesj-483	151	9	density	density	NOUN
cuesj-483	151	10	.	.	PUNCT
cuesj-483	152	1	kluwer	kluwer	NOUN
cuesj-483	152	2	academic	academic	ADJ
cuesj-483	152	3	publishers	publisher	NOUN
cuesj-483	152	4	,	,	PUNCT
cuesj-483	152	5	london	london	PROPN
cuesj-483	152	6	,	,	PUNCT
cuesj-483	152	7	1986	1986	NUM
cuesj-483	152	8	.	.	PUNCT
cuesj-483	153	1	13	13	NUM
cuesj-483	153	2	.	.	PUNCT
cuesj-483	153	3	m.	m.	PROPN
cuesj-483	153	4	hanif	hanif	PROPN
cuesj-483	153	5	,	,	PUNCT
cuesj-483	153	6	s.	s.	PROPN
cuesj-483	153	7	shahzadi	shahzadi	PROPN
cuesj-483	153	8	,	,	PUNCT
cuesj-483	153	9	u.	u.	PROPN
cuesj-483	153	10	shahzad	shahzad	PROPN
cuesj-483	153	11	and	and	CCONJ
cuesj-483	153	12	n.	n.	PROPN
cuesj-483	153	13	koyuncu	koyuncu	PROPN
cuesj-483	153	14	.	.	PUNCT
cuesj-483	154	1	on	on	ADP
cuesj-483	154	2	the	the	DET
cuesj-483	154	3	adaptive	adaptive	ADJ
cuesj-483	154	4	nadaraya	nadaraya	PROPN
cuesj-483	154	5	-	-	PUNCT
cuesj-483	154	6	watson	watson	PROPN
cuesj-483	154	7	kernel	kernel	PROPN
cuesj-483	154	8	estimator	estimator	NOUN
cuesj-483	154	9	for	for	ADP
cuesj-483	154	10	the	the	DET
cuesj-483	154	11	discontinuity	discontinuity	NOUN
cuesj-483	154	12	in	in	ADP
cuesj-483	154	13	the	the	DET
cuesj-483	154	14	presence	presence	NOUN
cuesj-483	154	15	of	of	ADP
cuesj-483	154	16	jump	jump	NOUN
cuesj-483	154	17	size	size	NOUN
cuesj-483	154	18	.	.	PUNCT
cuesj-483	155	1	süleyman	süleyman	PROPN
cuesj-483	155	2	demirel	demirel	PROPN
cuesj-483	155	3	üniversitesi	üniversitesi	PROPN
cuesj-483	155	4	fen	fen	PROPN
cuesj-483	155	5	bilimleri	bilimleri	PROPN
cuesj-483	155	6	enstitüsü	enstitüsü	PROPN
cuesj-483	155	7	dergisi	dergisi	PROPN
cuesj-483	155	8	,	,	PUNCT
cuesj-483	155	9	vol	vol	NOUN
cuesj-483	155	10	.	.	PROPN
cuesj-483	156	1	22	22	NUM
cuesj-483	156	2	,	,	PUNCT
cuesj-483	156	3	no	no	INTJ
cuesj-483	156	4	.	.	NOUN
cuesj-483	156	5	2	2	NUM
cuesj-483	156	6	,	,	PUNCT
cuesj-483	156	7	p.	p.	NOUN
cuesj-483	156	8	511	511	NUM
cuesj-483	156	9	,	,	PUNCT
cuesj-483	156	10	2018	2018	NUM
cuesj-483	156	11	.	.	PUNCT
cuesj-483	157	1	14	14	NUM
cuesj-483	157	2	.	.	PUNCT
cuesj-483	157	3	i.	i.	PROPN
cuesj-483	157	4	s.	s.	PROPN
cuesj-483	157	5	abramson	abramson	PROPN
cuesj-483	157	6	.	.	PUNCT
cuesj-483	158	1	on	on	ADP
cuesj-483	158	2	bandwidth	bandwidth	ADJ
cuesj-483	158	3	variation	variation	NOUN
cuesj-483	158	4	in	in	ADP
cuesj-483	158	5	kernel	kernel	PROPN
cuesj-483	158	6	estimates	estimate	NOUN
cuesj-483	158	7	-	-	PUNCT
cuesj-483	158	8	a	a	DET
cuesj-483	158	9	square	square	ADJ
cuesj-483	158	10	root	root	NOUN
cuesj-483	158	11	law	law	NOUN
cuesj-483	158	12	.	.	PUNCT
cuesj-483	159	1	the	the	DET
cuesj-483	159	2	annals	annal	NOUN
cuesj-483	159	3	of	of	ADP
cuesj-483	159	4	statistics	statistic	NOUN
cuesj-483	159	5	,	,	PUNCT
cuesj-483	159	6	vol	vol	NOUN
cuesj-483	159	7	.	.	PROPN
cuesj-483	159	8	10	10	NUM
cuesj-483	159	9	,	,	PUNCT
cuesj-483	159	10	no	no	INTJ
cuesj-483	159	11	.	.	NOUN
cuesj-483	159	12	4	4	NUM
cuesj-483	159	13	,	,	PUNCT
cuesj-483	159	14	pp	pp	ADJ
cuesj-483	159	15	.	.	PUNCT
cuesj-483	159	16	12171223	12171223	NUM
cuesj-483	159	17	,	,	PUNCT
cuesj-483	159	18	1982	1982	NUM
cuesj-483	159	19	.	.	PUNCT
cuesj-483	160	1	15	15	NUM
cuesj-483	160	2	.	.	PUNCT
cuesj-483	161	1	d.	d.	PROPN
cuesj-483	161	2	li	li	PROPN
cuesj-483	161	3	and	and	CCONJ
cuesj-483	161	4	r.	r.	PROPN
cuesj-483	161	5	li	li	PROPN
cuesj-483	161	6	.	.	PROPN
cuesj-483	162	1	local	local	ADJ
cuesj-483	162	2	composite	composite	ADJ
cuesj-483	162	3	quantile	quantile	ADJ
cuesj-483	162	4	regression	regression	NOUN
cuesj-483	162	5	smoothing	smooth	VERB
cuesj-483	162	6	for	for	ADP
cuesj-483	162	7	harris	harris	PROPN
cuesj-483	162	8	recurrent	recurrent	PROPN
cuesj-483	162	9	markov	markov	PROPN
cuesj-483	162	10	processes	process	NOUN
cuesj-483	162	11	.	.	PUNCT
cuesj-483	163	1	journal	journal	PROPN
cuesj-483	163	2	of	of	ADP
cuesj-483	163	3	econometrics	econometric	NOUN
cuesj-483	163	4	,	,	PUNCT
cuesj-483	163	5	vol	vol	NOUN
cuesj-483	163	6	.	.	PROPN
cuesj-483	163	7	194	194	NUM
cuesj-483	163	8	,	,	PUNCT
cuesj-483	163	9	no	no	INTJ
cuesj-483	163	10	.	.	NOUN
cuesj-483	163	11	1	1	NUM
cuesj-483	163	12	,	,	PUNCT
cuesj-483	163	13	pp	pp	ADJ
cuesj-483	163	14	.	.	PUNCT
cuesj-483	164	1	44	44	NUM
cuesj-483	164	2	-	-	SYM
cuesj-483	164	3	56	56	NUM
cuesj-483	164	4	,	,	PUNCT
cuesj-483	164	5	2016	2016	NUM
cuesj-483	164	6	.	.	PUNCT
cuesj-483	165	1	16	16	NUM
cuesj-483	165	2	.	.	PUNCT
cuesj-483	166	1	s.	s.	PROPN
cuesj-483	166	2	demir	demir	PROPN
cuesj-483	166	3	and	and	CCONJ
cuesj-483	166	4	ö.	ö.	PROPN
cuesj-483	166	5	toktamiş	toktamiş	PROPN
cuesj-483	166	6	.	.	PUNCT
cuesj-483	167	1	on	on	ADP
cuesj-483	167	2	the	the	DET
cuesj-483	167	3	adaptive	adaptive	ADJ
cuesj-483	167	4	nadaraya	nadaraya	PROPN
cuesj-483	167	5	-	-	PUNCT
cuesj-483	167	6	watson	watson	PROPN
cuesj-483	167	7	kernel	kernel	PROPN
cuesj-483	167	8	regression	regression	NOUN
cuesj-483	167	9	estimators	estimator	NOUN
cuesj-483	167	10	.	.	PUNCT
cuesj-483	168	1	hacettepe	hacettepe	ADJ
cuesj-483	168	2	journal	journal	PROPN
cuesj-483	168	3	of	of	ADP
cuesj-483	168	4	mathematics	mathematic	NOUN
cuesj-483	168	5	and	and	CCONJ
cuesj-483	168	6	statistics	statistic	NOUN
cuesj-483	168	7	,	,	PUNCT
cuesj-483	168	8	vol	vol	NOUN
cuesj-483	168	9	.	.	PROPN
cuesj-483	168	10	39	39	NUM
cuesj-483	168	11	,	,	PUNCT
cuesj-483	168	12	no	no	INTJ
cuesj-483	168	13	.	.	NOUN
cuesj-483	168	14	3	3	NUM
cuesj-483	168	15	,	,	PUNCT
cuesj-483	168	16	pp	pp	ADJ
cuesj-483	168	17	.	.	PUNCT
cuesj-483	169	1	429	429	NUM
cuesj-483	169	2	-	-	SYM
cuesj-483	169	3	437	437	NUM
cuesj-483	169	4	,	,	PUNCT
cuesj-483	169	5	2010	2010	NUM
cuesj-483	169	6	.	.	PUNCT
cuesj-483	170	1	17	17	NUM
cuesj-483	170	2	.	.	PUNCT
cuesj-483	170	3	h.	h.	PROPN
cuesj-483	170	4	a.	a.	PROPN
cuesj-483	170	5	khulood	khulood	PROPN
cuesj-483	170	6	and	and	CCONJ
cuesj-483	170	7	i.	i.	PROPN
cuesj-483	170	8	al	al	PROPN
cuesj-483	170	9	turk	turk	PROPN
cuesj-483	170	10	lutfiah	lutfiah	PROPN
cuesj-483	170	11	.	.	PUNCT
cuesj-483	171	1	modification	modification	NOUN
cuesj-483	171	2	of	of	ADP
cuesj-483	171	3	the	the	DET
cuesj-483	171	4	adaptive	adaptive	ADJ
cuesj-483	171	5	nadaraya	nadaraya	PROPN
cuesj-483	171	6	-	-	PUNCT
cuesj-483	171	7	watson	watson	PROPN
cuesj-483	171	8	kernel	kernel	PROPN
cuesj-483	171	9	regression	regression	PROPN
cuesj-483	171	10	estimator	estimator	NOUN
cuesj-483	171	11	.	.	PUNCT
cuesj-483	172	1	scientific	scientific	ADJ
cuesj-483	172	2	research	research	NOUN
cuesj-483	172	3	and	and	CCONJ
cuesj-483	172	4	essays	essay	NOUN
cuesj-483	172	5	,	,	PUNCT
cuesj-483	172	6	vol	vol	NOUN
cuesj-483	172	7	.	.	PROPN
cuesj-483	172	8	9	9	NUM
cuesj-483	172	9	,	,	PUNCT
cuesj-483	172	10	no	no	INTJ
cuesj-483	172	11	.	.	NOUN
cuesj-483	172	12	22	22	NUM
cuesj-483	172	13	,	,	PUNCT
cuesj-483	172	14	pp	pp	ADJ
cuesj-483	172	15	.	.	PUNCT
cuesj-483	173	1	966	966	NUM
cuesj-483	173	2	-	-	SYM
cuesj-483	173	3	971	971	NUM
cuesj-483	173	4	,	,	PUNCT
cuesj-483	173	5	2014	2014	NUM
cuesj-483	173	6	.	.	PUNCT
cuesj-483	174	1	18	18	NUM
cuesj-483	174	2	.	.	PUNCT
cuesj-483	175	1	t.	t.	PROPN
cuesj-483	175	2	h.	h.	PROPN
cuesj-483	175	3	ali	ali	PROPN
cuesj-483	175	4	.	.	PUNCT
cuesj-483	176	1	modification	modification	NOUN
cuesj-483	176	2	of	of	ADP
cuesj-483	176	3	the	the	DET
cuesj-483	176	4	adaptive	adaptive	ADJ
cuesj-483	176	5	nadaraya	nadaraya	PROPN
cuesj-483	176	6	-	-	PUNCT
cuesj-483	176	7	watson	watson	PROPN
cuesj-483	176	8	kernel	kernel	PROPN
cuesj-483	176	9	method	method	NOUN
cuesj-483	176	10	for	for	ADP
cuesj-483	176	11	nonparametric	nonparametric	NOUN
cuesj-483	176	12	regression	regression	NOUN
cuesj-483	176	13	(	(	PUNCT
cuesj-483	176	14	simulation	simulation	NOUN
cuesj-483	176	15	study	study	PROPN
cuesj-483	176	16	)	)	PUNCT
cuesj-483	176	17	.	.	PUNCT
cuesj-483	177	1	in	in	ADP
cuesj-483	177	2	:	:	PUNCT
cuesj-483	177	3	communications	communication	NOUN
cuesj-483	177	4	in	in	ADP
cuesj-483	177	5	statistics	statistic	NOUN
cuesj-483	177	6	-	-	PUNCT
cuesj-483	177	7	simulation	simulation	NOUN
cuesj-483	177	8	and	and	CCONJ
cuesj-483	177	9	computation	computation	NOUN
cuesj-483	177	10	.	.	PUNCT
cuesj-483	178	1	taylor	taylor	PROPN
cuesj-483	178	2	&	&	CCONJ
cuesj-483	178	3	francis	francis	PROPN
cuesj-483	178	4	group	group	PROPN
cuesj-483	178	5	,	,	PUNCT
cuesj-483	178	6	united	united	ADJ
cuesj-483	178	7	kingdom	kingdom	PROPN
cuesj-483	178	8	,	,	PUNCT
cuesj-483	178	9	pp	pp	ADJ
cuesj-483	178	10	.	.	PUNCT
cuesj-483	179	1	1	1	NUM
cuesj-483	179	2	-	-	SYM
cuesj-483	179	3	13	13	NUM
cuesj-483	179	4	,	,	PUNCT
cuesj-483	179	5	2019	2019	NUM
cuesj-483	179	6	.	.	PUNCT