id	sid	tid	token	lemma	pos
ejpam-5923	1	1	european	european	PROPN
ejpam-5923	1	2	journal	journal	PROPN
ejpam-5923	1	3	of	of	ADP
ejpam-5923	1	4	pure	pure	ADJ
ejpam-5923	1	5	and	and	CCONJ
ejpam-5923	1	6	applied	applied	ADJ
ejpam-5923	1	7	mathematics	mathematic	NOUN
ejpam-5923	1	8	2025	2025	NUM
ejpam-5923	1	9	,	,	PUNCT
ejpam-5923	1	10	vol	vol	NOUN
ejpam-5923	1	11	.	.	PROPN
ejpam-5923	1	12	18	18	NUM
ejpam-5923	1	13	,	,	PUNCT
ejpam-5923	1	14	issue	issue	NOUN
ejpam-5923	1	15	2	2	NUM
ejpam-5923	1	16	,	,	PUNCT
ejpam-5923	1	17	article	article	NOUN
ejpam-5923	1	18	number	number	NOUN
ejpam-5923	1	19	5923	5923	NUM
ejpam-5923	1	20	issn	issn	PROPN
ejpam-5923	1	21	1307	1307	NUM
ejpam-5923	1	22	-	-	SYM
ejpam-5923	1	23	5543	5543	NUM
ejpam-5923	1	24	–	–	PUNCT
ejpam-5923	1	25	ejpam.com	ejpam.com	X
ejpam-5923	1	26	published	publish	VERB
ejpam-5923	1	27	by	by	ADP
ejpam-5923	1	28	new	new	PROPN
ejpam-5923	1	29	york	york	PROPN
ejpam-5923	1	30	business	business	PROPN
ejpam-5923	1	31	global	global	PROPN
ejpam-5923	1	32	on	on	ADP
ejpam-5923	1	33	the	the	DET
ejpam-5923	1	34	generalized	generalized	ADJ
ejpam-5923	1	35	version	version	NOUN
ejpam-5923	1	36	of	of	ADP
ejpam-5923	1	37	the	the	DET
ejpam-5923	1	38	extended	extended	ADJ
ejpam-5923	1	39	standard	standard	ADJ
ejpam-5923	1	40	u	u	ADJ
ejpam-5923	1	41	-	-	ADJ
ejpam-5923	1	42	quadratic	quadratic	ADJ
ejpam-5923	1	43	distribution	distribution	NOUN
ejpam-5923	1	44	idzhar	idzhar	NOUN
ejpam-5923	1	45	a.	a.	NOUN
ejpam-5923	1	46	lakibul1,∗	lakibul1,∗	PROPN
ejpam-5923	1	47	,	,	PUNCT
ejpam-5923	1	48	daisy	daisy	NOUN
ejpam-5923	1	49	lou	lou	PROPN
ejpam-5923	1	50	l.	l.	PROPN
ejpam-5923	1	51	polestico2,3	polestico2,3	PROPN
ejpam-5923	1	52	,	,	PUNCT
ejpam-5923	2	1	arnulfo	arnulfo	PROPN
ejpam-5923	2	2	p.	p.	PROPN
ejpam-5923	3	1	supe2,3	supe2,3	PROPN
ejpam-5923	3	2	1	1	NUM
ejpam-5923	3	3	department	department	NOUN
ejpam-5923	3	4	of	of	ADP
ejpam-5923	3	5	mathematics	mathematic	NOUN
ejpam-5923	3	6	,	,	PUNCT
ejpam-5923	3	7	mindanao	mindanao	PROPN
ejpam-5923	3	8	state	state	PROPN
ejpam-5923	3	9	university	university	PROPN
ejpam-5923	3	10	sulu	sulu	PROPN
ejpam-5923	3	11	,	,	PUNCT
ejpam-5923	3	12	jolo	jolo	PROPN
ejpam-5923	3	13	,	,	PUNCT
ejpam-5923	3	14	sulu	sulu	PROPN
ejpam-5923	3	15	,	,	PUNCT
ejpam-5923	3	16	philippines	philippines	PROPN
ejpam-5923	3	17	2	2	NUM
ejpam-5923	3	18	department	department	NOUN
ejpam-5923	3	19	of	of	ADP
ejpam-5923	3	20	mathematics	mathematic	NOUN
ejpam-5923	3	21	and	and	CCONJ
ejpam-5923	3	22	statistics	statistic	NOUN
ejpam-5923	3	23	,	,	PUNCT
ejpam-5923	3	24	mindanao	mindanao	PROPN
ejpam-5923	3	25	state	state	PROPN
ejpam-5923	3	26	university	university	PROPN
ejpam-5923	3	27	iligan	iligan	PROPN
ejpam-5923	3	28	institute	institute	PROPN
ejpam-5923	3	29	of	of	ADP
ejpam-5923	3	30	technology	technology	PROPN
ejpam-5923	3	31	,	,	PUNCT
ejpam-5923	3	32	iligan	iligan	PROPN
ejpam-5923	3	33	city	city	PROPN
ejpam-5923	3	34	,	,	PUNCT
ejpam-5923	3	35	philippines	philippine	NOUN
ejpam-5923	3	36	3	3	NUM
ejpam-5923	3	37	premier	premier	PROPN
ejpam-5923	3	38	research	research	PROPN
ejpam-5923	3	39	institute	institute	PROPN
ejpam-5923	3	40	of	of	ADP
ejpam-5923	3	41	science	science	PROPN
ejpam-5923	3	42	and	and	CCONJ
ejpam-5923	3	43	mathematics	mathematic	NOUN
ejpam-5923	3	44	center	center	NOUN
ejpam-5923	3	45	for	for	ADP
ejpam-5923	3	46	computational	computational	ADJ
ejpam-5923	3	47	analytics	analytic	NOUN
ejpam-5923	3	48	and	and	CCONJ
ejpam-5923	3	49	modeling	modeling	NOUN
ejpam-5923	3	50	,	,	PUNCT
ejpam-5923	3	51	mindanao	mindanao	PROPN
ejpam-5923	3	52	state	state	PROPN
ejpam-5923	3	53	university	university	PROPN
ejpam-5923	3	54	iligan	iligan	PROPN
ejpam-5923	3	55	institute	institute	PROPN
ejpam-5923	3	56	of	of	ADP
ejpam-5923	3	57	technology	technology	PROPN
ejpam-5923	3	58	,	,	PUNCT
ejpam-5923	3	59	iligan	iligan	PROPN
ejpam-5923	3	60	city	city	PROPN
ejpam-5923	3	61	,	,	PUNCT
ejpam-5923	3	62	philippines	philippine	NOUN
ejpam-5923	3	63	abstract	abstract	ADJ
ejpam-5923	3	64	.	.	PUNCT
ejpam-5923	4	1	this	this	DET
ejpam-5923	4	2	paper	paper	NOUN
ejpam-5923	4	3	introduces	introduce	VERB
ejpam-5923	4	4	the	the	DET
ejpam-5923	4	5	generalized	generalize	VERB
ejpam-5923	4	6	extended	extend	VERB
ejpam-5923	4	7	standard	standard	ADJ
ejpam-5923	4	8	u	u	NOUN
ejpam-5923	4	9	-	-	ADJ
ejpam-5923	4	10	quadratic	quadratic	ADJ
ejpam-5923	4	11	(	(	PUNCT
ejpam-5923	4	12	gesu	gesu	NOUN
ejpam-5923	4	13	)	)	PUNCT
ejpam-5923	4	14	distribution	distribution	NOUN
ejpam-5923	4	15	,	,	PUNCT
ejpam-5923	4	16	an	an	DET
ejpam-5923	4	17	extension	extension	NOUN
ejpam-5923	4	18	of	of	ADP
ejpam-5923	4	19	the	the	DET
ejpam-5923	4	20	extended	extended	ADJ
ejpam-5923	4	21	standard	standard	ADJ
ejpam-5923	4	22	u	u	NOUN
ejpam-5923	4	23	-	-	ADJ
ejpam-5923	4	24	quadratic	quadratic	ADJ
ejpam-5923	4	25	(	(	PUNCT
ejpam-5923	4	26	esu	esu	NOUN
ejpam-5923	4	27	)	)	PUNCT
ejpam-5923	4	28	distribution	distribution	NOUN
ejpam-5923	4	29	,	,	PUNCT
ejpam-5923	4	30	developed	develop	VERB
ejpam-5923	4	31	by	by	ADP
ejpam-5923	4	32	incorporating	incorporate	VERB
ejpam-5923	4	33	an	an	DET
ejpam-5923	4	34	additional	additional	ADJ
ejpam-5923	4	35	parameter	parameter	NOUN
ejpam-5923	4	36	.	.	PUNCT
ejpam-5923	5	1	the	the	DET
ejpam-5923	5	2	gesu	gesu	PROPN
ejpam-5923	5	3	distribution	distribution	NOUN
ejpam-5923	5	4	effectively	effectively	ADV
ejpam-5923	5	5	models	model	VERB
ejpam-5923	5	6	asymmetric	asymmetric	ADJ
ejpam-5923	5	7	data	datum	NOUN
ejpam-5923	5	8	exhibiting	exhibit	VERB
ejpam-5923	5	9	bathtub	bathtub	NOUN
ejpam-5923	5	10	and	and	CCONJ
ejpam-5923	5	11	inverted	invert	VERB
ejpam-5923	5	12	bathtub	bathtub	NOUN
ejpam-5923	5	13	shapes	shape	NOUN
ejpam-5923	5	14	over	over	ADP
ejpam-5923	5	15	the	the	DET
ejpam-5923	5	16	unit	unit	NOUN
ejpam-5923	5	17	interval	interval	NOUN
ejpam-5923	5	18	[	[	X
ejpam-5923	5	19	0,1	0,1	NUM
ejpam-5923	5	20	]	]	PUNCT
ejpam-5923	5	21	.	.	PUNCT
ejpam-5923	6	1	several	several	ADJ
ejpam-5923	6	2	special	special	ADJ
ejpam-5923	6	3	cases	case	NOUN
ejpam-5923	6	4	of	of	ADP
ejpam-5923	6	5	the	the	DET
ejpam-5923	6	6	proposed	propose	VERB
ejpam-5923	6	7	distribution	distribution	NOUN
ejpam-5923	6	8	are	be	AUX
ejpam-5923	6	9	also	also	ADV
ejpam-5923	6	10	derived	derive	VERB
ejpam-5923	6	11	.	.	PUNCT
ejpam-5923	7	1	key	key	ADJ
ejpam-5923	7	2	statistical	statistical	ADJ
ejpam-5923	7	3	properties	property	NOUN
ejpam-5923	7	4	,	,	PUNCT
ejpam-5923	7	5	including	include	VERB
ejpam-5923	7	6	moments	moment	NOUN
ejpam-5923	7	7	,	,	PUNCT
ejpam-5923	7	8	the	the	DET
ejpam-5923	7	9	moment	moment	NOUN
ejpam-5923	7	10	-	-	PUNCT
ejpam-5923	7	11	generating	generate	VERB
ejpam-5923	7	12	function	function	NOUN
ejpam-5923	7	13	,	,	PUNCT
ejpam-5923	7	14	mean	mean	INTJ
ejpam-5923	7	15	,	,	PUNCT
ejpam-5923	7	16	variance	variance	NOUN
ejpam-5923	7	17	,	,	PUNCT
ejpam-5923	7	18	median	median	NOUN
ejpam-5923	7	19	,	,	PUNCT
ejpam-5923	7	20	mode	mode	NOUN
ejpam-5923	7	21	,	,	PUNCT
ejpam-5923	7	22	skewness	skewness	NOUN
ejpam-5923	7	23	,	,	PUNCT
ejpam-5923	7	24	and	and	CCONJ
ejpam-5923	7	25	kurtosis	kurtosis	NOUN
ejpam-5923	7	26	,	,	PUNCT
ejpam-5923	7	27	are	be	AUX
ejpam-5923	7	28	established	establish	VERB
ejpam-5923	7	29	,	,	PUNCT
ejpam-5923	7	30	along	along	ADP
ejpam-5923	7	31	with	with	ADP
ejpam-5923	7	32	a	a	DET
ejpam-5923	7	33	random	random	ADJ
ejpam-5923	7	34	number	number	NOUN
ejpam-5923	7	35	generation	generation	NOUN
ejpam-5923	7	36	algorithm	algorithm	NOUN
ejpam-5923	7	37	.	.	PUNCT
ejpam-5923	8	1	the	the	DET
ejpam-5923	8	2	performance	performance	NOUN
ejpam-5923	8	3	of	of	ADP
ejpam-5923	8	4	maximum	maximum	ADJ
ejpam-5923	8	5	likelihood	likelihood	NOUN
ejpam-5923	8	6	estimation	estimation	NOUN
ejpam-5923	8	7	for	for	ADP
ejpam-5923	8	8	the	the	DET
ejpam-5923	8	9	parameters	parameter	NOUN
ejpam-5923	8	10	of	of	ADP
ejpam-5923	8	11	the	the	DET
ejpam-5923	8	12	gesu	gesu	PROPN
ejpam-5923	8	13	distribution	distribution	NOUN
ejpam-5923	8	14	is	be	AUX
ejpam-5923	8	15	assessed	assess	VERB
ejpam-5923	8	16	through	through	ADP
ejpam-5923	8	17	simulation	simulation	NOUN
ejpam-5923	8	18	studies	study	NOUN
ejpam-5923	8	19	.	.	PUNCT
ejpam-5923	9	1	furthermore	furthermore	ADV
ejpam-5923	9	2	,	,	PUNCT
ejpam-5923	9	3	the	the	DET
ejpam-5923	9	4	distribution	distribution	NOUN
ejpam-5923	9	5	is	be	AUX
ejpam-5923	9	6	applied	apply	VERB
ejpam-5923	9	7	to	to	ADP
ejpam-5923	9	8	a	a	DET
ejpam-5923	9	9	real	real	ADJ
ejpam-5923	9	10	dataset	dataset	NOUN
ejpam-5923	9	11	,	,	PUNCT
ejpam-5923	9	12	demonstrating	demonstrate	VERB
ejpam-5923	9	13	a	a	DET
ejpam-5923	9	14	superior	superior	ADJ
ejpam-5923	9	15	fit	fit	NOUN
ejpam-5923	9	16	compared	compare	VERB
ejpam-5923	9	17	to	to	ADP
ejpam-5923	9	18	the	the	DET
ejpam-5923	9	19	esu	esu	NOUN
ejpam-5923	9	20	,	,	PUNCT
ejpam-5923	9	21	unit	unit	NOUN
ejpam-5923	9	22	-	-	PUNCT
ejpam-5923	9	23	rayleigh	rayleigh	PROPN
ejpam-5923	9	24	,	,	PUNCT
ejpam-5923	9	25	and	and	CCONJ
ejpam-5923	9	26	unit	unit	NOUN
ejpam-5923	9	27	-	-	PUNCT
ejpam-5923	9	28	burr	burr	PROPN
ejpam-5923	9	29	xii	xii	NOUN
ejpam-5923	9	30	distributions	distribution	NOUN
ejpam-5923	9	31	.	.	PUNCT
ejpam-5923	10	1	these	these	DET
ejpam-5923	10	2	results	result	NOUN
ejpam-5923	10	3	highlight	highlight	VERB
ejpam-5923	10	4	the	the	DET
ejpam-5923	10	5	flexibility	flexibility	NOUN
ejpam-5923	10	6	and	and	CCONJ
ejpam-5923	10	7	applicability	applicability	NOUN
ejpam-5923	10	8	of	of	ADP
ejpam-5923	10	9	the	the	DET
ejpam-5923	10	10	proposed	propose	VERB
ejpam-5923	10	11	gesu	gesu	NOUN
ejpam-5923	10	12	distribution	distribution	NOUN
ejpam-5923	10	13	in	in	ADP
ejpam-5923	10	14	modeling	model	VERB
ejpam-5923	10	15	unit	unit	NOUN
ejpam-5923	10	16	-	-	PUNCT
ejpam-5923	10	17	interval	interval	NOUN
ejpam-5923	10	18	data	datum	NOUN
ejpam-5923	10	19	.	.	PUNCT
ejpam-5923	11	1	2020	2020	NUM
ejpam-5923	11	2	mathematics	mathematics	PROPN
ejpam-5923	11	3	subject	subject	NOUN
ejpam-5923	11	4	classifications	classification	NOUN
ejpam-5923	11	5	:	:	PUNCT
ejpam-5923	11	6	60e05	60e05	NUM
ejpam-5923	11	7	,	,	PUNCT
ejpam-5923	11	8	62e10	62e10	NUM
ejpam-5923	11	9	,	,	PUNCT
ejpam-5923	11	10	65c10	65c10	NUM
ejpam-5923	11	11	key	key	ADJ
ejpam-5923	11	12	words	word	NOUN
ejpam-5923	11	13	and	and	CCONJ
ejpam-5923	11	14	phrases	phrase	NOUN
ejpam-5923	11	15	:	:	PUNCT
ejpam-5923	11	16	extended	extend	VERB
ejpam-5923	11	17	standard	standard	ADJ
ejpam-5923	11	18	u	u	ADJ
ejpam-5923	11	19	-	-	ADJ
ejpam-5923	11	20	quadratic	quadratic	ADJ
ejpam-5923	11	21	distribution	distribution	NOUN
ejpam-5923	11	22	,	,	PUNCT
ejpam-5923	11	23	kumaraswamy	kumaraswamy	ADJ
ejpam-5923	11	24	distribution	distribution	NOUN
ejpam-5923	11	25	,	,	PUNCT
ejpam-5923	11	26	generalized	generalized	ADJ
ejpam-5923	11	27	distribution	distribution	NOUN
ejpam-5923	11	28	,	,	PUNCT
ejpam-5923	11	29	cubic	cubic	ADJ
ejpam-5923	11	30	transmuted	transmuted	ADJ
ejpam-5923	11	31	uniform	uniform	ADJ
ejpam-5923	11	32	distribution	distribution	NOUN
ejpam-5923	11	33	,	,	PUNCT
ejpam-5923	11	34	bathtub	bathtub	NOUN
ejpam-5923	11	35	shape	shape	NOUN
ejpam-5923	11	36	distribution	distribution	NOUN
ejpam-5923	11	37	1	1	NUM
ejpam-5923	11	38	.	.	PUNCT
ejpam-5923	12	1	introduction	introduction	NOUN
ejpam-5923	12	2	probability	probability	NOUN
ejpam-5923	12	3	distributions	distribution	NOUN
ejpam-5923	12	4	play	play	VERB
ejpam-5923	12	5	a	a	DET
ejpam-5923	12	6	crucial	crucial	ADJ
ejpam-5923	12	7	role	role	NOUN
ejpam-5923	12	8	in	in	ADP
ejpam-5923	12	9	describing	describe	VERB
ejpam-5923	12	10	the	the	DET
ejpam-5923	12	11	behaviour	behaviour	NOUN
ejpam-5923	12	12	of	of	ADP
ejpam-5923	12	13	various	various	ADJ
ejpam-5923	12	14	phenomena	phenomenon	NOUN
ejpam-5923	12	15	.	.	PUNCT
ejpam-5923	13	1	however	however	ADV
ejpam-5923	13	2	,	,	PUNCT
ejpam-5923	13	3	each	each	DET
ejpam-5923	13	4	distribution	distribution	NOUN
ejpam-5923	13	5	has	have	VERB
ejpam-5923	13	6	inherent	inherent	ADJ
ejpam-5923	13	7	strengths	strength	NOUN
ejpam-5923	13	8	and	and	CCONJ
ejpam-5923	13	9	limitations	limitation	NOUN
ejpam-5923	13	10	in	in	ADP
ejpam-5923	13	11	modeling	model	VERB
ejpam-5923	13	12	different	different	ADJ
ejpam-5923	13	13	types	type	NOUN
ejpam-5923	13	14	of	of	ADP
ejpam-5923	13	15	data	datum	NOUN
ejpam-5923	13	16	.	.	PUNCT
ejpam-5923	14	1	incorporating	incorporate	VERB
ejpam-5923	14	2	additional	additional	ADJ
ejpam-5923	14	3	parameters	parameter	NOUN
ejpam-5923	14	4	to	to	ADP
ejpam-5923	14	5	any	any	DET
ejpam-5923	14	6	distribution	distribution	NOUN
ejpam-5923	14	7	enhances	enhance	VERB
ejpam-5923	14	8	the	the	DET
ejpam-5923	14	9	distribution	distribution	NOUN
ejpam-5923	14	10	’s	’s	PART
ejpam-5923	14	11	flexibility	flexibility	NOUN
ejpam-5923	14	12	,	,	PUNCT
ejpam-5923	14	13	allowing	allow	VERB
ejpam-5923	14	14	it	it	PRON
ejpam-5923	14	15	to	to	PART
ejpam-5923	14	16	capture	capture	VERB
ejpam-5923	14	17	more	more	ADV
ejpam-5923	14	18	complex	complex	ADJ
ejpam-5923	14	19	data	datum	NOUN
ejpam-5923	14	20	patterns.one	patterns.one	X
ejpam-5923	14	21	important	important	ADJ
ejpam-5923	14	22	class	class	NOUN
ejpam-5923	14	23	of	of	ADP
ejpam-5923	14	24	data	datum	NOUN
ejpam-5923	14	25	consists	consist	VERB
ejpam-5923	14	26	of	of	ADP
ejpam-5923	14	27	values	value	NOUN
ejpam-5923	14	28	restricted	restrict	VERB
ejpam-5923	14	29	to	to	ADP
ejpam-5923	14	30	the	the	DET
ejpam-5923	14	31	unit	unit	NOUN
ejpam-5923	14	32	interval	interval	NOUN
ejpam-5923	14	33	[	[	X
ejpam-5923	14	34	0,1	0,1	NUM
ejpam-5923	14	35	]	]	PUNCT
ejpam-5923	14	36	,	,	PUNCT
ejpam-5923	14	37	such	such	ADJ
ejpam-5923	14	38	as	as	ADP
ejpam-5923	14	39	rates	rate	NOUN
ejpam-5923	14	40	∗corresponding	∗corresponde	VERB
ejpam-5923	14	41	author	author	NOUN
ejpam-5923	14	42	.	.	PUNCT
ejpam-5923	15	1	doi	doi	NOUN
ejpam-5923	15	2	:	:	PUNCT
ejpam-5923	15	3	https://doi.org/10.29020/nybg.ejpam.v18i2.5923	https://doi.org/10.29020/nybg.ejpam.v18i2.5923	PROPN
ejpam-5923	15	4	email	email	NOUN
ejpam-5923	15	5	addresses	address	NOUN
ejpam-5923	15	6	:	:	PUNCT
ejpam-5923	15	7	idzhar.lakibul@msusulu.edu.ph	idzhar.lakibul@msusulu.edu.ph	PROPN
ejpam-5923	15	8	(	(	PUNCT
ejpam-5923	15	9	i.	i.	PROPN
ejpam-5923	15	10	a.	a.	PROPN
ejpam-5923	15	11	lakibul	lakibul	PROPN
ejpam-5923	15	12	)	)	PUNCT
ejpam-5923	15	13	,	,	PUNCT
ejpam-5923	15	14	daisylou.polestico@g.msuiit.edu.ph	daisylou.polestico@g.msuiit.edu.ph	PROPN
ejpam-5923	15	15	(	(	PUNCT
ejpam-5923	15	16	d.	d.	PROPN
ejpam-5923	15	17	l.	l.	PROPN
ejpam-5923	15	18	polestico	polestico	PROPN
ejpam-5923	15	19	)	)	PUNCT
ejpam-5923	15	20	,	,	PUNCT
ejpam-5923	15	21	arnulfo.supe@g.msuiit.edu.ph	arnulfo.supe@g.msuiit.edu.ph	PROPN
ejpam-5923	15	22	(	(	PUNCT
ejpam-5923	15	23	a.	a.	PROPN
ejpam-5923	15	24	p.	p.	PROPN
ejpam-5923	15	25	supe	supe	PROPN
ejpam-5923	15	26	)	)	PUNCT
ejpam-5923	15	27	https://www.ejpam.com	https://www.ejpam.com	NOUN
ejpam-5923	16	1	1	1	NUM
ejpam-5923	16	2	copyright	copyright	NOUN
ejpam-5923	16	3	:	:	PUNCT
ejpam-5923	16	4	©	©	PROPN
ejpam-5923	16	5	2025	2025	NUM
ejpam-5923	16	6	the	the	DET
ejpam-5923	16	7	author(s	author(s	NOUN
ejpam-5923	16	8	)	)	PUNCT
ejpam-5923	16	9	.	.	PUNCT
ejpam-5923	17	1	(	(	PUNCT
ejpam-5923	17	2	cc	cc	NOUN
ejpam-5923	17	3	by	by	ADP
ejpam-5923	17	4	-	-	PUNCT
ejpam-5923	17	5	nc	nc	PROPN
ejpam-5923	17	6	4.0	4.0	NUM
ejpam-5923	17	7	)	)	PUNCT
ejpam-5923	17	8	i.	i.	PROPN
ejpam-5923	17	9	a.	a.	PROPN
ejpam-5923	17	10	lakibul	lakibul	PROPN
ejpam-5923	17	11	,	,	PUNCT
ejpam-5923	17	12	d.	d.	PROPN
ejpam-5923	17	13	l.	l.	PROPN
ejpam-5923	17	14	polestico	polestico	PROPN
ejpam-5923	17	15	,	,	PUNCT
ejpam-5923	17	16	a.	a.	PROPN
ejpam-5923	17	17	p.	p.	NOUN
ejpam-5923	17	18	supe	supe	PROPN
ejpam-5923	17	19	/	/	SYM
ejpam-5923	17	20	eur	eur	PROPN
ejpam-5923	17	21	.	.	PUNCT
ejpam-5923	18	1	j.	j.	PROPN
ejpam-5923	18	2	pure	pure	PROPN
ejpam-5923	18	3	appl	appl	PROPN
ejpam-5923	18	4	.	.	PROPN
ejpam-5923	18	5	math	math	PROPN
ejpam-5923	18	6	,	,	PUNCT
ejpam-5923	18	7	18	18	NUM
ejpam-5923	18	8	(	(	PUNCT
ejpam-5923	18	9	2	2	NUM
ejpam-5923	18	10	)	)	PUNCT
ejpam-5923	18	11	(	(	PUNCT
ejpam-5923	18	12	2025	2025	NUM
ejpam-5923	18	13	)	)	PUNCT
ejpam-5923	18	14	,	,	PUNCT
ejpam-5923	18	15	5923	5923	NUM
ejpam-5923	18	16	2	2	NUM
ejpam-5923	18	17	of	of	ADP
ejpam-5923	18	18	21	21	NUM
ejpam-5923	18	19	and	and	CCONJ
ejpam-5923	18	20	proportions	proportion	NOUN
ejpam-5923	18	21	.	.	PUNCT
ejpam-5923	19	1	this	this	DET
ejpam-5923	19	2	type	type	NOUN
ejpam-5923	19	3	of	of	ADP
ejpam-5923	19	4	data	datum	NOUN
ejpam-5923	19	5	is	be	AUX
ejpam-5923	19	6	usually	usually	ADV
ejpam-5923	19	7	modelled	model	VERB
ejpam-5923	19	8	by	by	ADP
ejpam-5923	19	9	the	the	DET
ejpam-5923	19	10	beta	beta	ADJ
ejpam-5923	19	11	distribution	distribution	NOUN
ejpam-5923	19	12	or	or	CCONJ
ejpam-5923	19	13	kumaraswamy	kumaraswamy	NOUN
ejpam-5923	19	14	distribution[1	distribution[1	PROPN
ejpam-5923	19	15	]	]	PUNCT
ejpam-5923	19	16	.	.	PUNCT
ejpam-5923	20	1	other	other	ADJ
ejpam-5923	20	2	identified	identify	VERB
ejpam-5923	20	3	distributions	distribution	NOUN
ejpam-5923	20	4	on	on	ADP
ejpam-5923	20	5	the	the	DET
ejpam-5923	20	6	interval	interval	NOUN
ejpam-5923	20	7	[	[	X
ejpam-5923	20	8	0	0	NUM
ejpam-5923	20	9	,	,	PUNCT
ejpam-5923	20	10	1	1	NUM
ejpam-5923	20	11	]	]	PUNCT
ejpam-5923	20	12	or	or	CCONJ
ejpam-5923	20	13	(	(	PUNCT
ejpam-5923	20	14	0	0	NUM
ejpam-5923	20	15	,	,	PUNCT
ejpam-5923	20	16	1	1	NUM
ejpam-5923	20	17	)	)	PUNCT
ejpam-5923	20	18	are	be	AUX
ejpam-5923	20	19	the	the	DET
ejpam-5923	20	20	unit	unit	NOUN
ejpam-5923	20	21	lindley	lindley	NOUN
ejpam-5923	20	22	distribution	distribution	NOUN
ejpam-5923	20	23	[	[	X
ejpam-5923	20	24	2	2	NUM
ejpam-5923	20	25	]	]	PUNCT
ejpam-5923	20	26	,	,	PUNCT
ejpam-5923	20	27	unit	unit	NOUN
ejpam-5923	20	28	rayleigh	rayleigh	NOUN
ejpam-5923	20	29	distribution	distribution	NOUN
ejpam-5923	21	1	[	[	X
ejpam-5923	21	2	3	3	NUM
ejpam-5923	21	3	]	]	PUNCT
ejpam-5923	21	4	,	,	PUNCT
ejpam-5923	21	5	new	new	ADJ
ejpam-5923	21	6	unit	unit	NOUN
ejpam-5923	21	7	lindley	lindley	NOUN
ejpam-5923	21	8	distribution	distribution	NOUN
ejpam-5923	21	9	[	[	X
ejpam-5923	21	10	4	4	NUM
ejpam-5923	21	11	]	]	PUNCT
ejpam-5923	21	12	,	,	PUNCT
ejpam-5923	21	13	unit	unit	NOUN
ejpam-5923	21	14	weibull	weibull	NOUN
ejpam-5923	21	15	distribution	distribution	NOUN
ejpam-5923	22	1	[	[	X
ejpam-5923	22	2	5	5	NUM
ejpam-5923	22	3	]	]	PUNCT
ejpam-5923	22	4	,	,	PUNCT
ejpam-5923	22	5	among	among	ADP
ejpam-5923	22	6	others	other	NOUN
ejpam-5923	22	7	.	.	PUNCT
ejpam-5923	23	1	rahman	rahman	PROPN
ejpam-5923	23	2	et	et	PROPN
ejpam-5923	23	3	al	al	PROPN
ejpam-5923	23	4	.	.	PUNCT
ejpam-5923	24	1	[	[	X
ejpam-5923	24	2	6	6	NUM
ejpam-5923	24	3	]	]	PUNCT
ejpam-5923	24	4	established	establish	VERB
ejpam-5923	24	5	a	a	DET
ejpam-5923	24	6	cubic	cubic	ADJ
ejpam-5923	24	7	transmuted	transmuted	ADJ
ejpam-5923	24	8	uniform	uniform	NOUN
ejpam-5923	24	9	(	(	PUNCT
ejpam-5923	24	10	ctu	ctu	NOUN
ejpam-5923	24	11	)	)	PUNCT
ejpam-5923	24	12	distribution	distribution	NOUN
ejpam-5923	24	13	using	use	VERB
ejpam-5923	24	14	cubic	cubic	ADJ
ejpam-5923	24	15	transmuted	transmute	VERB
ejpam-5923	24	16	family	family	NOUN
ejpam-5923	24	17	,	,	PUNCT
ejpam-5923	24	18	and	and	CCONJ
ejpam-5923	24	19	they	they	PRON
ejpam-5923	24	20	applied	apply	VERB
ejpam-5923	24	21	this	this	DET
ejpam-5923	24	22	distribution	distribution	NOUN
ejpam-5923	24	23	to	to	ADP
ejpam-5923	24	24	electronic	electronic	ADJ
ejpam-5923	24	25	dataset	dataset	NOUN
ejpam-5923	24	26	and	and	CCONJ
ejpam-5923	24	27	compared	compare	VERB
ejpam-5923	24	28	with	with	ADP
ejpam-5923	24	29	the	the	DET
ejpam-5923	24	30	beta	beta	NOUN
ejpam-5923	24	31	,	,	PUNCT
ejpam-5923	24	32	kumaraswamy	kumaraswamy	NOUN
ejpam-5923	24	33	and	and	CCONJ
ejpam-5923	24	34	skew	skew	ADJ
ejpam-5923	24	35	uniform	uniform	ADJ
ejpam-5923	24	36	distribution	distribution	NOUN
ejpam-5923	24	37	.	.	PUNCT
ejpam-5923	25	1	they	they	PRON
ejpam-5923	25	2	found	find	VERB
ejpam-5923	25	3	out	out	ADP
ejpam-5923	25	4	that	that	SCONJ
ejpam-5923	25	5	the	the	DET
ejpam-5923	25	6	ctu	ctu	ADJ
ejpam-5923	25	7	distribution	distribution	NOUN
ejpam-5923	25	8	provided	provide	VERB
ejpam-5923	25	9	better	well	ADJ
ejpam-5923	25	10	fit	fit	ADJ
ejpam-5923	25	11	for	for	ADP
ejpam-5923	25	12	the	the	DET
ejpam-5923	25	13	said	say	VERB
ejpam-5923	25	14	dataset	dataset	NOUN
ejpam-5923	25	15	compared	compare	VERB
ejpam-5923	25	16	to	to	ADP
ejpam-5923	25	17	the	the	DET
ejpam-5923	25	18	said	say	VERB
ejpam-5923	25	19	distributions	distribution	NOUN
ejpam-5923	25	20	.	.	PUNCT
ejpam-5923	26	1	lakibul	lakibul	PROPN
ejpam-5923	26	2	and	and	CCONJ
ejpam-5923	26	3	tubo	tubo	VERB
ejpam-5923	27	1	[	[	X
ejpam-5923	27	2	7	7	NUM
ejpam-5923	27	3	]	]	PUNCT
ejpam-5923	27	4	proposed	propose	VERB
ejpam-5923	27	5	an	an	DET
ejpam-5923	27	6	alternative	alternative	ADJ
ejpam-5923	27	7	distribution	distribution	NOUN
ejpam-5923	27	8	to	to	ADP
ejpam-5923	27	9	beta	beta	NOUN
ejpam-5923	27	10	,	,	PUNCT
ejpam-5923	27	11	kumaraswamy	kumaraswamy	NOUN
ejpam-5923	27	12	,	,	PUNCT
ejpam-5923	27	13	and	and	CCONJ
ejpam-5923	27	14	ctu	ctu	NOUN
ejpam-5923	27	15	distributions	distribution	NOUN
ejpam-5923	27	16	to	to	PART
ejpam-5923	27	17	describe	describe	VERB
ejpam-5923	27	18	the	the	DET
ejpam-5923	27	19	behavior	behavior	NOUN
ejpam-5923	27	20	of	of	ADP
ejpam-5923	27	21	the	the	DET
ejpam-5923	27	22	data	datum	NOUN
ejpam-5923	27	23	that	that	PRON
ejpam-5923	27	24	has	have	AUX
ejpam-5923	27	25	bathtub	bathtub	PROPN
ejpam-5923	27	26	,	,	PUNCT
ejpam-5923	27	27	constant	constant	ADJ
ejpam-5923	27	28	or	or	CCONJ
ejpam-5923	27	29	inverted	inverted	ADJ
ejpam-5923	27	30	bathtub	bathtub	PROPN
ejpam-5923	27	31	behavior	behavior	NOUN
ejpam-5923	27	32	,	,	PUNCT
ejpam-5923	27	33	and	and	CCONJ
ejpam-5923	27	34	this	this	DET
ejpam-5923	27	35	distribution	distribution	NOUN
ejpam-5923	27	36	is	be	AUX
ejpam-5923	27	37	called	call	VERB
ejpam-5923	27	38	the	the	DET
ejpam-5923	27	39	extended	extended	ADJ
ejpam-5923	27	40	standard	standard	ADJ
ejpam-5923	27	41	uquadratic	uquadratic	ADJ
ejpam-5923	27	42	distribution	distribution	NOUN
ejpam-5923	27	43	.	.	PUNCT
ejpam-5923	28	1	a	a	DET
ejpam-5923	28	2	random	random	ADJ
ejpam-5923	28	3	variable	variable	NOUN
ejpam-5923	28	4	x	x	PUNCT
ejpam-5923	28	5	is	be	AUX
ejpam-5923	28	6	said	say	VERB
ejpam-5923	28	7	to	to	PART
ejpam-5923	28	8	have	have	VERB
ejpam-5923	28	9	an	an	DET
ejpam-5923	28	10	extended	extended	ADJ
ejpam-5923	28	11	standard	standard	ADJ
ejpam-5923	28	12	u	u	ADJ
ejpam-5923	28	13	-	-	ADJ
ejpam-5923	28	14	quadratic	quadratic	ADJ
ejpam-5923	28	15	distribution	distribution	NOUN
ejpam-5923	28	16	denoted	denote	VERB
ejpam-5923	28	17	by	by	ADP
ejpam-5923	28	18	”	"	PUNCT
ejpam-5923	28	19	esu	esu	NOUN
ejpam-5923	28	20	”	"	PUNCT
ejpam-5923	28	21	if	if	SCONJ
ejpam-5923	28	22	the	the	DET
ejpam-5923	28	23	probability	probability	NOUN
ejpam-5923	28	24	density	density	NOUN
ejpam-5923	28	25	function	function	NOUN
ejpam-5923	28	26	(	(	PUNCT
ejpam-5923	28	27	pdf	pdf	NOUN
ejpam-5923	28	28	)	)	PUNCT
ejpam-5923	28	29	of	of	ADP
ejpam-5923	28	30	t	t	PROPN
ejpam-5923	28	31	is	be	AUX
ejpam-5923	28	32	given	give	VERB
ejpam-5923	28	33	by	by	ADP
ejpam-5923	28	34	f(x	f(x	PROPN
ejpam-5923	28	35	)	)	PUNCT
ejpam-5923	28	36	=	=	SYM
ejpam-5923	29	1	1−	1−	NUM
ejpam-5923	29	2	λ+	λ+	PUNCT
ejpam-5923	29	3	3λ(2t−	3λ(2t−	NUM
ejpam-5923	29	4	1)2	1)2	NUM
ejpam-5923	29	5	,	,	PUNCT
ejpam-5923	29	6	t	t	PROPN
ejpam-5923	29	7	∈	∈	PROPN
ejpam-5923	30	1	[	[	X
ejpam-5923	30	2	0	0	NUM
ejpam-5923	30	3	,	,	PUNCT
ejpam-5923	30	4	1	1	NUM
ejpam-5923	30	5	]	]	PUNCT
ejpam-5923	30	6	,	,	PUNCT
ejpam-5923	30	7	(	(	PUNCT
ejpam-5923	30	8	1	1	X
ejpam-5923	30	9	)	)	PUNCT
ejpam-5923	30	10	where	where	SCONJ
ejpam-5923	30	11	λ	λ	PROPN
ejpam-5923	30	12	∈	∈	PROPN
ejpam-5923	31	1	[	[	X
ejpam-5923	31	2	−0.5	−0.5	PROPN
ejpam-5923	31	3	,	,	PUNCT
ejpam-5923	31	4	1	1	NUM
ejpam-5923	31	5	]	]	PUNCT
ejpam-5923	31	6	.	.	PUNCT
ejpam-5923	32	1	it	it	PRON
ejpam-5923	32	2	was	be	AUX
ejpam-5923	32	3	observed	observe	VERB
ejpam-5923	32	4	that	that	SCONJ
ejpam-5923	32	5	the	the	DET
ejpam-5923	32	6	pdf	pdf	NOUN
ejpam-5923	32	7	of	of	ADP
ejpam-5923	32	8	this	this	DET
ejpam-5923	32	9	distribution	distribution	NOUN
ejpam-5923	32	10	can	can	AUX
ejpam-5923	32	11	produce	produce	VERB
ejpam-5923	32	12	three	three	NUM
ejpam-5923	32	13	different	different	ADJ
ejpam-5923	32	14	types	type	NOUN
ejpam-5923	32	15	of	of	ADP
ejpam-5923	32	16	shape	shape	NOUN
ejpam-5923	32	17	,	,	PUNCT
ejpam-5923	32	18	namely	namely	ADV
ejpam-5923	32	19	the	the	DET
ejpam-5923	32	20	inverted	inverted	ADJ
ejpam-5923	32	21	bathtub	bathtub	NOUN
ejpam-5923	32	22	for	for	ADP
ejpam-5923	32	23	λ	λ	PROPN
ejpam-5923	32	24	∈	∈	PROPN
ejpam-5923	33	1	[	[	X
ejpam-5923	33	2	−0.5	−0.5	PROPN
ejpam-5923	33	3	,	,	PUNCT
ejpam-5923	33	4	0	0	NUM
ejpam-5923	33	5	)	)	PUNCT
ejpam-5923	33	6	,	,	PUNCT
ejpam-5923	33	7	constant	constant	ADJ
ejpam-5923	33	8	for	for	ADP
ejpam-5923	33	9	λ	λ	X
ejpam-5923	33	10	=	=	SYM
ejpam-5923	33	11	0	0	NUM
ejpam-5923	33	12	and	and	CCONJ
ejpam-5923	33	13	bathtub	bathtub	VERB
ejpam-5923	33	14	for	for	ADP
ejpam-5923	33	15	λ	λ	PROPN
ejpam-5923	33	16	∈	∈	PROPN
ejpam-5923	33	17	(	(	PUNCT
ejpam-5923	33	18	0	0	NUM
ejpam-5923	33	19	,	,	PUNCT
ejpam-5923	33	20	1	1	NUM
ejpam-5923	33	21	]	]	PUNCT
ejpam-5923	33	22	.	.	PUNCT
ejpam-5923	34	1	in	in	ADP
ejpam-5923	34	2	addition	addition	NOUN
ejpam-5923	34	3	,	,	PUNCT
ejpam-5923	34	4	some	some	DET
ejpam-5923	34	5	properties	property	NOUN
ejpam-5923	34	6	of	of	ADP
ejpam-5923	34	7	this	this	DET
ejpam-5923	34	8	distribution	distribution	NOUN
ejpam-5923	34	9	such	such	ADJ
ejpam-5923	34	10	as	as	ADP
ejpam-5923	34	11	the	the	DET
ejpam-5923	34	12	mean	mean	ADJ
ejpam-5923	34	13	,	,	PUNCT
ejpam-5923	34	14	variance	variance	NOUN
ejpam-5923	34	15	,	,	PUNCT
ejpam-5923	34	16	moments	moment	NOUN
ejpam-5923	34	17	,	,	PUNCT
ejpam-5923	34	18	and	and	CCONJ
ejpam-5923	34	19	other	other	ADJ
ejpam-5923	34	20	properties	property	NOUN
ejpam-5923	34	21	can	can	AUX
ejpam-5923	34	22	be	be	AUX
ejpam-5923	34	23	found	find	VERB
ejpam-5923	34	24	in	in	ADP
ejpam-5923	34	25	the	the	DET
ejpam-5923	34	26	paper	paper	NOUN
ejpam-5923	34	27	of	of	ADP
ejpam-5923	34	28	lakibul	lakibul	PROPN
ejpam-5923	34	29	and	and	CCONJ
ejpam-5923	34	30	tubo	tubo	ADJ
ejpam-5923	34	31	[	[	X
ejpam-5923	34	32	8	8	NUM
ejpam-5923	34	33	]	]	PUNCT
ejpam-5923	34	34	.	.	PUNCT
ejpam-5923	35	1	also	also	ADV
ejpam-5923	35	2	,	,	PUNCT
ejpam-5923	35	3	the	the	DET
ejpam-5923	35	4	bivariate	bivariate	ADJ
ejpam-5923	35	5	version	version	NOUN
ejpam-5923	35	6	of	of	ADP
ejpam-5923	35	7	the	the	DET
ejpam-5923	35	8	esu	esu	NOUN
ejpam-5923	35	9	distribution	distribution	NOUN
ejpam-5923	35	10	is	be	AUX
ejpam-5923	35	11	written	write	VERB
ejpam-5923	35	12	in	in	ADP
ejpam-5923	35	13	the	the	DET
ejpam-5923	35	14	paper	paper	NOUN
ejpam-5923	35	15	of	of	ADP
ejpam-5923	35	16	lakibul	lakibul	PROPN
ejpam-5923	35	17	,	,	PUNCT
ejpam-5923	35	18	polestico	polestico	NOUN
ejpam-5923	35	19	and	and	CCONJ
ejpam-5923	35	20	supe	supe	PROPN
ejpam-5923	36	1	[	[	X
ejpam-5923	36	2	9	9	NUM
ejpam-5923	36	3	]	]	PUNCT
ejpam-5923	36	4	.	.	PUNCT
ejpam-5923	37	1	however	however	ADV
ejpam-5923	37	2	,	,	PUNCT
ejpam-5923	37	3	the	the	DET
ejpam-5923	37	4	esu	esu	NOUN
ejpam-5923	37	5	distribution	distribution	NOUN
ejpam-5923	37	6	is	be	AUX
ejpam-5923	37	7	symmetric	symmetric	ADJ
ejpam-5923	37	8	at	at	ADP
ejpam-5923	37	9	1	1	NUM
ejpam-5923	37	10	2	2	NUM
ejpam-5923	37	11	.	.	PUNCT
ejpam-5923	38	1	thus	thus	ADV
ejpam-5923	38	2	,	,	PUNCT
ejpam-5923	38	3	there	there	PRON
ejpam-5923	38	4	is	be	VERB
ejpam-5923	38	5	a	a	DET
ejpam-5923	38	6	need	need	NOUN
ejpam-5923	38	7	to	to	PART
ejpam-5923	38	8	generalize	generalize	VERB
ejpam-5923	38	9	this	this	DET
ejpam-5923	38	10	distribution	distribution	NOUN
ejpam-5923	38	11	by	by	ADP
ejpam-5923	38	12	incorporating	incorporate	VERB
ejpam-5923	38	13	an	an	DET
ejpam-5923	38	14	additional	additional	ADJ
ejpam-5923	38	15	parameter	parameter	NOUN
ejpam-5923	38	16	to	to	PART
ejpam-5923	38	17	account	account	VERB
ejpam-5923	38	18	for	for	ADP
ejpam-5923	38	19	the	the	DET
ejpam-5923	38	20	asymmetric	asymmetric	ADJ
ejpam-5923	38	21	behavior	behavior	NOUN
ejpam-5923	38	22	of	of	ADP
ejpam-5923	38	23	the	the	DET
ejpam-5923	38	24	data	datum	NOUN
ejpam-5923	38	25	.	.	PUNCT
ejpam-5923	39	1	in	in	ADP
ejpam-5923	39	2	this	this	DET
ejpam-5923	39	3	paper	paper	NOUN
ejpam-5923	39	4	,	,	PUNCT
ejpam-5923	39	5	we	we	PRON
ejpam-5923	39	6	will	will	AUX
ejpam-5923	39	7	expand	expand	VERB
ejpam-5923	39	8	the	the	DET
ejpam-5923	39	9	extended	extended	ADJ
ejpam-5923	39	10	standard	standard	ADJ
ejpam-5923	39	11	u	u	ADJ
ejpam-5923	39	12	-	-	ADJ
ejpam-5923	39	13	quadratic	quadratic	ADJ
ejpam-5923	39	14	distribution	distribution	NOUN
ejpam-5923	39	15	into	into	ADP
ejpam-5923	39	16	a	a	DET
ejpam-5923	39	17	generalized	generalize	VERB
ejpam-5923	39	18	extended	extend	VERB
ejpam-5923	39	19	standard	standard	ADJ
ejpam-5923	39	20	u	u	ADJ
ejpam-5923	39	21	-	-	ADJ
ejpam-5923	39	22	quadratic	quadratic	ADJ
ejpam-5923	39	23	distribution	distribution	NOUN
ejpam-5923	39	24	by	by	ADP
ejpam-5923	39	25	incorporating	incorporate	VERB
ejpam-5923	39	26	an	an	DET
ejpam-5923	39	27	additional	additional	ADJ
ejpam-5923	39	28	parameter	parameter	NOUN
ejpam-5923	39	29	to	to	ADP
ejpam-5923	39	30	the	the	DET
ejpam-5923	39	31	distribution	distribution	NOUN
ejpam-5923	39	32	.	.	PUNCT
ejpam-5923	40	1	we	we	PRON
ejpam-5923	40	2	will	will	AUX
ejpam-5923	40	3	also	also	ADV
ejpam-5923	40	4	derive	derive	VERB
ejpam-5923	40	5	some	some	DET
ejpam-5923	40	6	properties	property	NOUN
ejpam-5923	40	7	of	of	ADP
ejpam-5923	40	8	the	the	DET
ejpam-5923	40	9	proposed	propose	VERB
ejpam-5923	40	10	distribution	distribution	NOUN
ejpam-5923	40	11	such	such	ADJ
ejpam-5923	40	12	as	as	ADP
ejpam-5923	40	13	the	the	DET
ejpam-5923	40	14	mean	mean	ADJ
ejpam-5923	40	15	,	,	PUNCT
ejpam-5923	40	16	variance	variance	NOUN
ejpam-5923	40	17	,	,	PUNCT
ejpam-5923	40	18	skewness	skewness	NOUN
ejpam-5923	40	19	,	,	PUNCT
ejpam-5923	40	20	kurtosis	kurtosis	NOUN
ejpam-5923	40	21	,	,	PUNCT
ejpam-5923	40	22	median	median	ADJ
ejpam-5923	40	23	,	,	PUNCT
ejpam-5923	40	24	mode	mode	NOUN
ejpam-5923	40	25	,	,	PUNCT
ejpam-5923	40	26	rth	rth	NOUN
ejpam-5923	40	27	moments	moment	NOUN
ejpam-5923	40	28	and	and	CCONJ
ejpam-5923	40	29	moment	moment	NOUN
ejpam-5923	40	30	generating	generate	VERB
ejpam-5923	40	31	function	function	NOUN
ejpam-5923	40	32	.	.	PUNCT
ejpam-5923	41	1	the	the	DET
ejpam-5923	41	2	applicability	applicability	NOUN
ejpam-5923	41	3	and	and	CCONJ
ejpam-5923	41	4	usefulness	usefulness	NOUN
ejpam-5923	41	5	of	of	ADP
ejpam-5923	41	6	the	the	DET
ejpam-5923	41	7	proposed	propose	VERB
ejpam-5923	41	8	distribution	distribution	NOUN
ejpam-5923	41	9	is	be	AUX
ejpam-5923	41	10	investigated	investigate	VERB
ejpam-5923	41	11	by	by	ADP
ejpam-5923	41	12	applying	apply	VERB
ejpam-5923	41	13	it	it	PRON
ejpam-5923	41	14	on	on	ADP
ejpam-5923	41	15	the	the	DET
ejpam-5923	41	16	tensile	tensile	NOUN
ejpam-5923	41	17	strength	strength	NOUN
ejpam-5923	41	18	of	of	ADP
ejpam-5923	41	19	polyester	polyester	NOUN
ejpam-5923	41	20	fibers	fiber	NOUN
ejpam-5923	41	21	dataset	dataset	VERB
ejpam-5923	41	22	.	.	PUNCT
ejpam-5923	42	1	the	the	DET
ejpam-5923	42	2	rest	rest	NOUN
ejpam-5923	42	3	of	of	ADP
ejpam-5923	42	4	the	the	DET
ejpam-5923	42	5	paper	paper	NOUN
ejpam-5923	42	6	is	be	AUX
ejpam-5923	42	7	arranged	arrange	VERB
ejpam-5923	42	8	as	as	SCONJ
ejpam-5923	42	9	follows	follow	VERB
ejpam-5923	42	10	:	:	PUNCT
ejpam-5923	42	11	section	section	NOUN
ejpam-5923	42	12	2	2	NUM
ejpam-5923	42	13	presents	present	VERB
ejpam-5923	42	14	the	the	DET
ejpam-5923	42	15	construction	construction	NOUN
ejpam-5923	42	16	of	of	ADP
ejpam-5923	42	17	the	the	DET
ejpam-5923	42	18	generalized	generalize	VERB
ejpam-5923	42	19	extended	extend	VERB
ejpam-5923	42	20	standard	standard	ADJ
ejpam-5923	42	21	u	u	NOUN
ejpam-5923	42	22	-	-	ADJ
ejpam-5923	42	23	quadratic	quadratic	ADJ
ejpam-5923	42	24	(	(	PUNCT
ejpam-5923	42	25	gesu	gesu	NOUN
ejpam-5923	42	26	)	)	PUNCT
ejpam-5923	42	27	distribution	distribution	NOUN
ejpam-5923	42	28	.	.	PUNCT
ejpam-5923	43	1	section	section	NOUN
ejpam-5923	43	2	3	3	NUM
ejpam-5923	43	3	provides	provide	VERB
ejpam-5923	43	4	derivations	derivation	NOUN
ejpam-5923	43	5	of	of	ADP
ejpam-5923	43	6	some	some	DET
ejpam-5923	43	7	properties	property	NOUN
ejpam-5923	43	8	of	of	ADP
ejpam-5923	43	9	the	the	DET
ejpam-5923	43	10	proposed	propose	VERB
ejpam-5923	43	11	gesu	gesu	PROPN
ejpam-5923	43	12	distribution	distribution	NOUN
ejpam-5923	43	13	.	.	PUNCT
ejpam-5923	44	1	section	section	NOUN
ejpam-5923	44	2	4	4	NUM
ejpam-5923	44	3	discusses	discuss	VERB
ejpam-5923	44	4	the	the	DET
ejpam-5923	44	5	maximum	maximum	ADJ
ejpam-5923	44	6	likelihood	likelihood	NOUN
ejpam-5923	44	7	estimation	estimation	NOUN
ejpam-5923	44	8	for	for	ADP
ejpam-5923	44	9	estimating	estimate	VERB
ejpam-5923	44	10	the	the	DET
ejpam-5923	44	11	parameters	parameter	NOUN
ejpam-5923	44	12	of	of	ADP
ejpam-5923	44	13	the	the	DET
ejpam-5923	44	14	proposed	propose	VERB
ejpam-5923	44	15	generalized	generalized	ADJ
ejpam-5923	44	16	distribution	distribution	NOUN
ejpam-5923	44	17	.	.	PUNCT
ejpam-5923	45	1	section	section	NOUN
ejpam-5923	45	2	5	5	NUM
ejpam-5923	45	3	deals	deal	NOUN
ejpam-5923	45	4	with	with	ADP
ejpam-5923	45	5	the	the	DET
ejpam-5923	45	6	random	random	ADJ
ejpam-5923	45	7	number	number	NOUN
ejpam-5923	45	8	generation	generation	NOUN
ejpam-5923	45	9	of	of	ADP
ejpam-5923	45	10	the	the	DET
ejpam-5923	45	11	proposed	propose	VERB
ejpam-5923	45	12	generalized	generalized	ADJ
ejpam-5923	45	13	distribution	distribution	NOUN
ejpam-5923	45	14	.	.	PUNCT
ejpam-5923	46	1	section	section	NOUN
ejpam-5923	46	2	6	6	NUM
ejpam-5923	46	3	presents	present	VERB
ejpam-5923	46	4	the	the	DET
ejpam-5923	46	5	simulation	simulation	NOUN
ejpam-5923	46	6	results	result	VERB
ejpam-5923	46	7	for	for	ADP
ejpam-5923	46	8	assessing	assess	VERB
ejpam-5923	46	9	the	the	DET
ejpam-5923	46	10	behavior	behavior	NOUN
ejpam-5923	46	11	of	of	ADP
ejpam-5923	46	12	the	the	DET
ejpam-5923	46	13	maximum	maximum	ADJ
ejpam-5923	46	14	likelihood	likelihood	NOUN
ejpam-5923	46	15	estimate	estimate	NOUN
ejpam-5923	46	16	of	of	ADP
ejpam-5923	46	17	the	the	DET
ejpam-5923	46	18	proposed	propose	VERB
ejpam-5923	46	19	generalized	generalized	ADJ
ejpam-5923	46	20	distribution	distribution	NOUN
ejpam-5923	46	21	’s	’s	PART
ejpam-5923	46	22	parameter	parameter	NOUN
ejpam-5923	46	23	.	.	PUNCT
ejpam-5923	47	1	application	application	NOUN
ejpam-5923	47	2	of	of	ADP
ejpam-5923	47	3	the	the	DET
ejpam-5923	47	4	proposed	propose	VERB
ejpam-5923	47	5	distribution	distribution	NOUN
ejpam-5923	47	6	is	be	AUX
ejpam-5923	47	7	presented	present	VERB
ejpam-5923	47	8	in	in	ADP
ejpam-5923	47	9	section	section	NOUN
ejpam-5923	47	10	7	7	NUM
ejpam-5923	47	11	.	.	PUNCT
ejpam-5923	47	12	section	section	NOUN
ejpam-5923	47	13	8	8	NUM
ejpam-5923	47	14	gives	give	VERB
ejpam-5923	47	15	some	some	DET
ejpam-5923	47	16	concluding	conclude	VERB
ejpam-5923	47	17	remarks	remark	NOUN
ejpam-5923	47	18	about	about	ADP
ejpam-5923	47	19	the	the	DET
ejpam-5923	47	20	paper	paper	NOUN
ejpam-5923	47	21	and	and	CCONJ
ejpam-5923	47	22	recommendations	recommendation	NOUN
ejpam-5923	47	23	for	for	ADP
ejpam-5923	47	24	future	future	ADJ
ejpam-5923	47	25	studies	study	NOUN
ejpam-5923	47	26	.	.	PUNCT
ejpam-5923	48	1	i.	i.	PROPN
ejpam-5923	48	2	a.	a.	PROPN
ejpam-5923	48	3	lakibul	lakibul	PROPN
ejpam-5923	48	4	,	,	PUNCT
ejpam-5923	48	5	d.	d.	PROPN
ejpam-5923	48	6	l.	l.	PROPN
ejpam-5923	48	7	polestico	polestico	PROPN
ejpam-5923	48	8	,	,	PUNCT
ejpam-5923	48	9	a.	a.	PROPN
ejpam-5923	48	10	p.	p.	NOUN
ejpam-5923	48	11	supe	supe	PROPN
ejpam-5923	48	12	/	/	SYM
ejpam-5923	48	13	eur	eur	PROPN
ejpam-5923	48	14	.	.	PUNCT
ejpam-5923	49	1	j.	j.	PROPN
ejpam-5923	49	2	pure	pure	PROPN
ejpam-5923	49	3	appl	appl	PROPN
ejpam-5923	49	4	.	.	PROPN
ejpam-5923	49	5	math	math	PROPN
ejpam-5923	49	6	,	,	PUNCT
ejpam-5923	49	7	18	18	NUM
ejpam-5923	49	8	(	(	PUNCT
ejpam-5923	49	9	2	2	NUM
ejpam-5923	49	10	)	)	PUNCT
ejpam-5923	49	11	(	(	PUNCT
ejpam-5923	49	12	2025	2025	NUM
ejpam-5923	49	13	)	)	PUNCT
ejpam-5923	49	14	,	,	PUNCT
ejpam-5923	49	15	5923	5923	NUM
ejpam-5923	49	16	3	3	NUM
ejpam-5923	49	17	of	of	ADP
ejpam-5923	49	18	21	21	NUM
ejpam-5923	49	19	2	2	NUM
ejpam-5923	49	20	.	.	PUNCT
ejpam-5923	50	1	the	the	DET
ejpam-5923	50	2	generalized	generalize	VERB
ejpam-5923	50	3	extended	extend	VERB
ejpam-5923	50	4	standard	standard	ADJ
ejpam-5923	50	5	u	u	ADJ
ejpam-5923	50	6	-	-	ADJ
ejpam-5923	50	7	quadratic	quadratic	ADJ
ejpam-5923	50	8	distribution	distribution	NOUN
ejpam-5923	50	9	developing	develop	VERB
ejpam-5923	50	10	new	new	ADJ
ejpam-5923	50	11	models	model	NOUN
ejpam-5923	50	12	is	be	AUX
ejpam-5923	50	13	essential	essential	ADJ
ejpam-5923	50	14	for	for	ADP
ejpam-5923	50	15	improving	improve	VERB
ejpam-5923	50	16	accuracy	accuracy	NOUN
ejpam-5923	50	17	,	,	PUNCT
ejpam-5923	50	18	efficiency	efficiency	NOUN
ejpam-5923	50	19	,	,	PUNCT
ejpam-5923	50	20	and	and	CCONJ
ejpam-5923	50	21	robustness	robustness	NOUN
ejpam-5923	50	22	by	by	ADP
ejpam-5923	50	23	capturing	capture	VERB
ejpam-5923	50	24	complex	complex	ADJ
ejpam-5923	50	25	data	datum	NOUN
ejpam-5923	50	26	patterns	pattern	NOUN
ejpam-5923	50	27	that	that	SCONJ
ejpam-5923	50	28	standard	standard	ADJ
ejpam-5923	50	29	models	model	NOUN
ejpam-5923	50	30	may	may	AUX
ejpam-5923	50	31	overlook	overlook	VERB
ejpam-5923	50	32	.	.	PUNCT
ejpam-5923	51	1	in	in	ADP
ejpam-5923	51	2	addition	addition	NOUN
ejpam-5923	51	3	,	,	PUNCT
ejpam-5923	51	4	specialized	specialized	ADJ
ejpam-5923	51	5	models	model	NOUN
ejpam-5923	51	6	are	be	AUX
ejpam-5923	51	7	crucial	crucial	ADJ
ejpam-5923	51	8	for	for	ADP
ejpam-5923	51	9	systems	system	NOUN
ejpam-5923	51	10	with	with	ADP
ejpam-5923	51	11	unique	unique	ADJ
ejpam-5923	51	12	data	datum	NOUN
ejpam-5923	51	13	structures	structure	NOUN
ejpam-5923	51	14	,	,	PUNCT
ejpam-5923	51	15	ensuring	ensure	VERB
ejpam-5923	51	16	better	well	ADJ
ejpam-5923	51	17	analysis	analysis	NOUN
ejpam-5923	51	18	and	and	CCONJ
ejpam-5923	51	19	decision	decision	NOUN
ejpam-5923	51	20	-	-	PUNCT
ejpam-5923	51	21	making	making	NOUN
ejpam-5923	51	22	.	.	PUNCT
ejpam-5923	52	1	this	this	DET
ejpam-5923	52	2	section	section	NOUN
ejpam-5923	52	3	presents	present	VERB
ejpam-5923	52	4	the	the	DET
ejpam-5923	52	5	derivation	derivation	NOUN
ejpam-5923	52	6	of	of	ADP
ejpam-5923	52	7	the	the	DET
ejpam-5923	52	8	new	new	ADJ
ejpam-5923	52	9	generalized	generalized	ADJ
ejpam-5923	52	10	distribution	distribution	NOUN
ejpam-5923	52	11	with	with	ADP
ejpam-5923	52	12	support	support	NOUN
ejpam-5923	52	13	on	on	ADP
ejpam-5923	52	14	[	[	X
ejpam-5923	52	15	0	0	NUM
ejpam-5923	52	16	,	,	PUNCT
ejpam-5923	52	17	1	1	NUM
ejpam-5923	52	18	]	]	PUNCT
ejpam-5923	52	19	.	.	PUNCT
ejpam-5923	53	1	the	the	DET
ejpam-5923	53	2	extended	extend	VERB
ejpam-5923	53	3	standard	standard	ADJ
ejpam-5923	53	4	u	u	NOUN
ejpam-5923	53	5	-	-	ADJ
ejpam-5923	53	6	quadratic	quadratic	ADJ
ejpam-5923	53	7	(	(	PUNCT
ejpam-5923	53	8	esu	esu	NOUN
ejpam-5923	53	9	)	)	PUNCT
ejpam-5923	53	10	distribution	distribution	NOUN
ejpam-5923	53	11	,	,	PUNCT
ejpam-5923	53	12	while	while	SCONJ
ejpam-5923	53	13	useful	useful	ADJ
ejpam-5923	53	14	for	for	ADP
ejpam-5923	53	15	modeling	model	VERB
ejpam-5923	53	16	certain	certain	ADJ
ejpam-5923	53	17	forms	form	NOUN
ejpam-5923	53	18	of	of	ADP
ejpam-5923	53	19	data	datum	NOUN
ejpam-5923	53	20	within	within	ADP
ejpam-5923	53	21	the	the	DET
ejpam-5923	53	22	unit	unit	NOUN
ejpam-5923	53	23	interval	interval	NOUN
ejpam-5923	53	24	[	[	X
ejpam-5923	53	25	0	0	NUM
ejpam-5923	53	26	,	,	PUNCT
ejpam-5923	53	27	1	1	NUM
ejpam-5923	53	28	]	]	PUNCT
ejpam-5923	53	29	or	or	CCONJ
ejpam-5923	53	30	(	(	PUNCT
ejpam-5923	53	31	0	0	NUM
ejpam-5923	53	32	,	,	PUNCT
ejpam-5923	53	33	1	1	NUM
ejpam-5923	53	34	)	)	PUNCT
ejpam-5923	53	35	,	,	PUNCT
ejpam-5923	53	36	is	be	AUX
ejpam-5923	53	37	limited	limit	VERB
ejpam-5923	53	38	in	in	ADP
ejpam-5923	53	39	its	its	PRON
ejpam-5923	53	40	ability	ability	NOUN
ejpam-5923	53	41	to	to	PART
ejpam-5923	53	42	handle	handle	VERB
ejpam-5923	53	43	asymmetric	asymmetric	ADJ
ejpam-5923	53	44	data	datum	NOUN
ejpam-5923	53	45	or	or	CCONJ
ejpam-5923	53	46	data	datum	NOUN
ejpam-5923	53	47	exhibiting	exhibit	VERB
ejpam-5923	53	48	more	more	ADJ
ejpam-5923	53	49	complex	complex	ADJ
ejpam-5923	53	50	shapes	shape	NOUN
ejpam-5923	53	51	such	such	ADJ
ejpam-5923	53	52	as	as	ADP
ejpam-5923	53	53	the	the	DET
ejpam-5923	53	54	bathtub	bathtub	NOUN
ejpam-5923	53	55	and	and	CCONJ
ejpam-5923	53	56	inverted	invert	VERB
ejpam-5923	53	57	bathtub	bathtub	NOUN
ejpam-5923	53	58	curves	curve	NOUN
ejpam-5923	53	59	.	.	PUNCT
ejpam-5923	54	1	these	these	DET
ejpam-5923	54	2	shapes	shape	NOUN
ejpam-5923	54	3	are	be	AUX
ejpam-5923	54	4	commonly	commonly	ADV
ejpam-5923	54	5	observed	observe	VERB
ejpam-5923	54	6	in	in	ADP
ejpam-5923	54	7	a	a	DET
ejpam-5923	54	8	range	range	NOUN
ejpam-5923	54	9	of	of	ADP
ejpam-5923	54	10	practical	practical	ADJ
ejpam-5923	54	11	fields	field	NOUN
ejpam-5923	54	12	,	,	PUNCT
ejpam-5923	54	13	including	include	VERB
ejpam-5923	54	14	economics	economic	NOUN
ejpam-5923	54	15	,	,	PUNCT
ejpam-5923	54	16	engineering	engineering	NOUN
ejpam-5923	54	17	,	,	PUNCT
ejpam-5923	54	18	biological	biological	ADJ
ejpam-5923	54	19	studies	study	NOUN
ejpam-5923	54	20	,	,	PUNCT
ejpam-5923	54	21	and	and	CCONJ
ejpam-5923	54	22	reliability	reliability	NOUN
ejpam-5923	54	23	analysis	analysis	NOUN
ejpam-5923	54	24	,	,	PUNCT
ejpam-5923	54	25	where	where	SCONJ
ejpam-5923	54	26	data	datum	NOUN
ejpam-5923	54	27	often	often	ADV
ejpam-5923	54	28	display	display	VERB
ejpam-5923	54	29	significant	significant	ADJ
ejpam-5923	54	30	skewness	skewness	NOUN
ejpam-5923	54	31	or	or	CCONJ
ejpam-5923	54	32	asymmetric	asymmetric	ADJ
ejpam-5923	54	33	behavior	behavior	NOUN
ejpam-5923	54	34	.	.	PUNCT
ejpam-5923	55	1	in	in	ADP
ejpam-5923	55	2	particular	particular	ADJ
ejpam-5923	55	3	,	,	PUNCT
ejpam-5923	55	4	many	many	ADJ
ejpam-5923	55	5	real	real	ADJ
ejpam-5923	55	6	-	-	PUNCT
ejpam-5923	55	7	world	world	NOUN
ejpam-5923	55	8	phenomena	phenomenon	NOUN
ejpam-5923	55	9	,	,	PUNCT
ejpam-5923	55	10	such	such	ADJ
ejpam-5923	55	11	as	as	ADP
ejpam-5923	55	12	survival	survival	NOUN
ejpam-5923	55	13	data	datum	NOUN
ejpam-5923	55	14	,	,	PUNCT
ejpam-5923	55	15	failure	failure	NOUN
ejpam-5923	55	16	rates	rate	NOUN
ejpam-5923	55	17	,	,	PUNCT
ejpam-5923	55	18	and	and	CCONJ
ejpam-5923	55	19	certain	certain	ADJ
ejpam-5923	55	20	types	type	NOUN
ejpam-5923	55	21	of	of	ADP
ejpam-5923	55	22	financial	financial	ADJ
ejpam-5923	55	23	data	datum	NOUN
ejpam-5923	55	24	,	,	PUNCT
ejpam-5923	55	25	do	do	AUX
ejpam-5923	55	26	not	not	PART
ejpam-5923	55	27	adhere	adhere	VERB
ejpam-5923	55	28	to	to	ADP
ejpam-5923	55	29	the	the	DET
ejpam-5923	55	30	symmetrical	symmetrical	ADJ
ejpam-5923	55	31	distributions	distribution	NOUN
ejpam-5923	55	32	assumed	assume	VERB
ejpam-5923	55	33	by	by	ADP
ejpam-5923	55	34	many	many	ADJ
ejpam-5923	55	35	traditional	traditional	ADJ
ejpam-5923	55	36	models	model	NOUN
ejpam-5923	55	37	.	.	PUNCT
ejpam-5923	56	1	this	this	PRON
ejpam-5923	56	2	motivates	motivate	VERB
ejpam-5923	56	3	the	the	DET
ejpam-5923	56	4	development	development	NOUN
ejpam-5923	56	5	of	of	ADP
ejpam-5923	56	6	a	a	DET
ejpam-5923	56	7	more	more	ADV
ejpam-5923	56	8	flexible	flexible	ADJ
ejpam-5923	56	9	distribution	distribution	NOUN
ejpam-5923	56	10	capable	capable	ADJ
ejpam-5923	56	11	of	of	ADP
ejpam-5923	56	12	modeling	model	VERB
ejpam-5923	56	13	such	such	ADJ
ejpam-5923	56	14	asymmetries	asymmetry	NOUN
ejpam-5923	56	15	and	and	CCONJ
ejpam-5923	56	16	complex	complex	ADJ
ejpam-5923	56	17	data	datum	NOUN
ejpam-5923	56	18	behaviors	behavior	NOUN
ejpam-5923	56	19	.	.	PUNCT
ejpam-5923	57	1	to	to	PART
ejpam-5923	57	2	address	address	VERB
ejpam-5923	57	3	this	this	DET
ejpam-5923	57	4	limitation	limitation	NOUN
ejpam-5923	57	5	,	,	PUNCT
ejpam-5923	57	6	we	we	PRON
ejpam-5923	57	7	propose	propose	VERB
ejpam-5923	57	8	the	the	DET
ejpam-5923	57	9	generalized	generalize	VERB
ejpam-5923	57	10	extended	extend	VERB
ejpam-5923	57	11	standard	standard	ADJ
ejpam-5923	57	12	u	u	NOUN
ejpam-5923	57	13	-	-	ADJ
ejpam-5923	57	14	quadratic	quadratic	ADJ
ejpam-5923	57	15	(	(	PUNCT
ejpam-5923	57	16	gesu	gesu	NOUN
ejpam-5923	57	17	)	)	PUNCT
ejpam-5923	57	18	distribution	distribution	NOUN
ejpam-5923	57	19	,	,	PUNCT
ejpam-5923	57	20	an	an	DET
ejpam-5923	57	21	extension	extension	NOUN
ejpam-5923	57	22	of	of	ADP
ejpam-5923	57	23	the	the	DET
ejpam-5923	57	24	esu	esu	NOUN
ejpam-5923	57	25	distribution	distribution	NOUN
ejpam-5923	57	26	that	that	PRON
ejpam-5923	57	27	incorporates	incorporate	VERB
ejpam-5923	57	28	an	an	DET
ejpam-5923	57	29	additional	additional	ADJ
ejpam-5923	57	30	parameter	parameter	NOUN
ejpam-5923	57	31	to	to	PART
ejpam-5923	57	32	provide	provide	VERB
ejpam-5923	57	33	greater	great	ADJ
ejpam-5923	57	34	flexibility	flexibility	NOUN
ejpam-5923	57	35	.	.	PUNCT
ejpam-5923	58	1	to	to	PART
ejpam-5923	58	2	start	start	VERB
ejpam-5923	58	3	with	with	ADP
ejpam-5923	58	4	,	,	PUNCT
ejpam-5923	58	5	let	let	VERB
ejpam-5923	58	6	us	we	PRON
ejpam-5923	58	7	consider	consider	VERB
ejpam-5923	58	8	the	the	DET
ejpam-5923	58	9	pdf	pdf	NOUN
ejpam-5923	58	10	of	of	ADP
ejpam-5923	58	11	the	the	DET
ejpam-5923	58	12	esu	esu	NOUN
ejpam-5923	58	13	distribution	distribution	NOUN
ejpam-5923	58	14	given	give	VERB
ejpam-5923	58	15	in	in	ADP
ejpam-5923	58	16	equation	equation	NOUN
ejpam-5923	58	17	(	(	PUNCT
ejpam-5923	58	18	1	1	NUM
ejpam-5923	58	19	)	)	PUNCT
ejpam-5923	58	20	,	,	PUNCT
ejpam-5923	58	21	which	which	PRON
ejpam-5923	58	22	can	can	AUX
ejpam-5923	58	23	be	be	AUX
ejpam-5923	58	24	rewritten	rewrite	VERB
ejpam-5923	58	25	as	as	ADP
ejpam-5923	58	26	f(t	f(t	NOUN
ejpam-5923	58	27	)	)	PUNCT
ejpam-5923	59	1	=	=	SYM
ejpam-5923	59	2	1−	1−	NUM
ejpam-5923	59	3	λ+	λ+	PUNCT
ejpam-5923	59	4	12λ	12λ	NUM
ejpam-5923	59	5	(	(	PUNCT
ejpam-5923	59	6	t−	t−	PROPN
ejpam-5923	59	7	1	1	NUM
ejpam-5923	59	8	2	2	NUM
ejpam-5923	59	9	)	)	SYM
ejpam-5923	59	10	2	2	NUM
ejpam-5923	59	11	=(	=(	NOUN
ejpam-5923	59	12	1−	1−	NUM
ejpam-5923	59	13	λ)f1(t	λ)f1(t	PROPN
ejpam-5923	59	14	)	)	PUNCT
ejpam-5923	59	15	+	+	CCONJ
ejpam-5923	59	16	λf2(t	λf2(t	PROPN
ejpam-5923	59	17	)	)	PUNCT
ejpam-5923	59	18	,	,	PUNCT
ejpam-5923	59	19	(	(	PUNCT
ejpam-5923	59	20	2	2	X
ejpam-5923	59	21	)	)	PUNCT
ejpam-5923	59	22	where	where	SCONJ
ejpam-5923	59	23	f1(t	f1(t	VERB
ejpam-5923	59	24	)	)	PUNCT
ejpam-5923	59	25	=	=	SYM
ejpam-5923	59	26	1	1	NUM
ejpam-5923	59	27	and	and	CCONJ
ejpam-5923	59	28	f2(t	f2(t	NUM
ejpam-5923	59	29	)	)	PUNCT
ejpam-5923	59	30	=	=	SYM
ejpam-5923	59	31	12	12	NUM
ejpam-5923	59	32	(	(	PUNCT
ejpam-5923	59	33	t−	t−	PROPN
ejpam-5923	59	34	1	1	NUM
ejpam-5923	59	35	2	2	NUM
ejpam-5923	59	36	)	)	PUNCT
ejpam-5923	59	37	2	2	NUM
ejpam-5923	59	38	,	,	PUNCT
ejpam-5923	59	39	t	t	PROPN
ejpam-5923	59	40	∈	∈	PROPN
ejpam-5923	60	1	[	[	X
ejpam-5923	60	2	0	0	NUM
ejpam-5923	60	3	,	,	PUNCT
ejpam-5923	60	4	1	1	NUM
ejpam-5923	60	5	]	]	PUNCT
ejpam-5923	60	6	and	and	CCONJ
ejpam-5923	60	7	λ	λ	X
ejpam-5923	60	8	∈	∈	PROPN
ejpam-5923	60	9	[	[	X
ejpam-5923	60	10	−0.5	−0.5	PROPN
ejpam-5923	60	11	,	,	PUNCT
ejpam-5923	60	12	1	1	NUM
ejpam-5923	60	13	]	]	PUNCT
ejpam-5923	60	14	.	.	PUNCT
ejpam-5923	61	1	to	to	PART
ejpam-5923	61	2	generalize	generalize	VERB
ejpam-5923	61	3	the	the	DET
ejpam-5923	61	4	esu	esu	NOUN
ejpam-5923	61	5	distribution	distribution	NOUN
ejpam-5923	61	6	,	,	PUNCT
ejpam-5923	61	7	we	we	PRON
ejpam-5923	61	8	incorporate	incorporate	VERB
ejpam-5923	61	9	an	an	DET
ejpam-5923	61	10	additional	additional	ADJ
ejpam-5923	61	11	parameter	parameter	NOUN
ejpam-5923	61	12	a	a	PRON
ejpam-5923	61	13	into	into	ADP
ejpam-5923	61	14	its	its	PRON
ejpam-5923	61	15	pdf	pdf	NOUN
ejpam-5923	61	16	so	so	SCONJ
ejpam-5923	61	17	that	that	SCONJ
ejpam-5923	61	18	the	the	DET
ejpam-5923	61	19	esu	esu	NOUN
ejpam-5923	61	20	distribution	distribution	NOUN
ejpam-5923	61	21	becomes	become	VERB
ejpam-5923	61	22	a	a	DET
ejpam-5923	61	23	special	special	ADJ
ejpam-5923	61	24	case	case	NOUN
ejpam-5923	61	25	of	of	ADP
ejpam-5923	61	26	it	it	PRON
ejpam-5923	61	27	.	.	PUNCT
ejpam-5923	62	1	specifically	specifically	ADV
ejpam-5923	62	2	,	,	PUNCT
ejpam-5923	62	3	find	find	VERB
ejpam-5923	62	4	a	a	DET
ejpam-5923	62	5	particular	particular	ADJ
ejpam-5923	62	6	form	form	NOUN
ejpam-5923	62	7	for	for	ADP
ejpam-5923	62	8	f2(t	f2(t	NOUN
ejpam-5923	62	9	)	)	PUNCT
ejpam-5923	62	10	in	in	ADP
ejpam-5923	62	11	equation	equation	NOUN
ejpam-5923	62	12	(	(	PUNCT
ejpam-5923	62	13	2	2	NUM
ejpam-5923	62	14	)	)	PUNCT
ejpam-5923	62	15	.	.	PUNCT
ejpam-5923	63	1	consider	consider	VERB
ejpam-5923	63	2	a	a	DET
ejpam-5923	63	3	function	function	NOUN
ejpam-5923	63	4	of	of	ADP
ejpam-5923	63	5	the	the	DET
ejpam-5923	63	6	form	form	NOUN
ejpam-5923	63	7	f∗(t	f∗(t	NOUN
ejpam-5923	63	8	)	)	PUNCT
ejpam-5923	64	1	=	=	SYM
ejpam-5923	64	2	c	c	X
ejpam-5923	64	3	(	(	PUNCT
ejpam-5923	64	4	t−	t−	PROPN
ejpam-5923	64	5	a)2	a)2	PROPN
ejpam-5923	64	6	,	,	PUNCT
ejpam-5923	64	7	(	(	PUNCT
ejpam-5923	64	8	3	3	X
ejpam-5923	64	9	)	)	PUNCT
ejpam-5923	64	10	where	where	SCONJ
ejpam-5923	64	11	t	t	PROPN
ejpam-5923	64	12	∈	∈	PROPN
ejpam-5923	65	1	[	[	X
ejpam-5923	65	2	0	0	NUM
ejpam-5923	65	3	,	,	PUNCT
ejpam-5923	65	4	1	1	NUM
ejpam-5923	65	5	]	]	PUNCT
ejpam-5923	65	6	,	,	PUNCT
ejpam-5923	65	7	a	a	DET
ejpam-5923	65	8	∈	∈	NOUN
ejpam-5923	66	1	[	[	X
ejpam-5923	66	2	0	0	NUM
ejpam-5923	66	3	,	,	PUNCT
ejpam-5923	66	4	1	1	NUM
ejpam-5923	66	5	]	]	PUNCT
ejpam-5923	66	6	,	,	PUNCT
ejpam-5923	66	7	c	c	PROPN
ejpam-5923	66	8	is	be	AUX
ejpam-5923	66	9	a	a	DET
ejpam-5923	66	10	constant	constant	ADJ
ejpam-5923	66	11	.	.	PUNCT
ejpam-5923	67	1	now	now	ADV
ejpam-5923	67	2	,	,	PUNCT
ejpam-5923	67	3	recall	recall	VERB
ejpam-5923	67	4	that	that	SCONJ
ejpam-5923	67	5	,	,	PUNCT
ejpam-5923	67	6	for	for	ADP
ejpam-5923	67	7	any	any	DET
ejpam-5923	67	8	function	function	NOUN
ejpam-5923	67	9	f	f	PROPN
ejpam-5923	67	10	,	,	PUNCT
ejpam-5923	67	11	f	f	PROPN
ejpam-5923	67	12	is	be	AUX
ejpam-5923	67	13	said	say	VERB
ejpam-5923	67	14	to	to	PART
ejpam-5923	67	15	be	be	AUX
ejpam-5923	67	16	a	a	DET
ejpam-5923	67	17	probability	probability	NOUN
ejpam-5923	67	18	distribution	distribution	NOUN
ejpam-5923	67	19	function	function	NOUN
ejpam-5923	67	20	if	if	SCONJ
ejpam-5923	67	21	it	it	PRON
ejpam-5923	67	22	satisfies	satisfy	VERB
ejpam-5923	67	23	the	the	DET
ejpam-5923	67	24	following	follow	VERB
ejpam-5923	67	25	conditions	condition	NOUN
ejpam-5923	67	26	:	:	PUNCT
ejpam-5923	67	27	(	(	PUNCT
ejpam-5923	67	28	i.	i.	NOUN
ejpam-5923	67	29	)	)	PUNCT
ejpam-5923	67	30	f(t	f(t	PROPN
ejpam-5923	67	31	)	)	PUNCT
ejpam-5923	67	32	≥	≥	NOUN
ejpam-5923	67	33	0	0	NUM
ejpam-5923	67	34	;	;	PUNCT
ejpam-5923	67	35	and	and	CCONJ
ejpam-5923	67	36	(	(	PUNCT
ejpam-5923	67	37	ii	ii	NOUN
ejpam-5923	67	38	.	.	PUNCT
ejpam-5923	67	39	)	)	PUNCT
ejpam-5923	68	1	∫	∫	PROPN
ejpam-5923	68	2	f(t)dt	f(t)dt	PROPN
ejpam-5923	68	3	=	=	SYM
ejpam-5923	68	4	1	1	X
ejpam-5923	68	5	.	.	PUNCT
ejpam-5923	68	6	let	let	VERB
ejpam-5923	68	7	us	we	PRON
ejpam-5923	68	8	first	first	ADV
ejpam-5923	68	9	solve	solve	VERB
ejpam-5923	68	10	the	the	DET
ejpam-5923	68	11	constant	constant	ADJ
ejpam-5923	68	12	c	c	NOUN
ejpam-5923	68	13	for	for	ADP
ejpam-5923	68	14	f∗(t	f∗(t	NOUN
ejpam-5923	68	15	)	)	PUNCT
ejpam-5923	68	16	using	use	VERB
ejpam-5923	68	17	(	(	PUNCT
ejpam-5923	68	18	ii	ii	NOUN
ejpam-5923	68	19	.	.	PUNCT
ejpam-5923	68	20	)	)	PUNCT
ejpam-5923	68	21	,	,	PUNCT
ejpam-5923	68	22	that	that	SCONJ
ejpam-5923	68	23	is,∫	is,∫	VERB
ejpam-5923	68	24	1	1	NUM
ejpam-5923	68	25	0	0	NUM
ejpam-5923	68	26	f∗(t)dt	f∗(t)dt	NOUN
ejpam-5923	68	27	=	=	SYM
ejpam-5923	68	28	1	1	NUM
ejpam-5923	68	29	i.	i.	NOUN
ejpam-5923	68	30	a.	a.	PROPN
ejpam-5923	68	31	lakibul	lakibul	PROPN
ejpam-5923	68	32	,	,	PUNCT
ejpam-5923	68	33	d.	d.	PROPN
ejpam-5923	68	34	l.	l.	PROPN
ejpam-5923	68	35	polestico	polestico	PROPN
ejpam-5923	68	36	,	,	PUNCT
ejpam-5923	68	37	a.	a.	PROPN
ejpam-5923	68	38	p.	p.	NOUN
ejpam-5923	68	39	supe	supe	PROPN
ejpam-5923	68	40	/	/	SYM
ejpam-5923	68	41	eur	eur	PROPN
ejpam-5923	68	42	.	.	PUNCT
ejpam-5923	69	1	j.	j.	PROPN
ejpam-5923	69	2	pure	pure	PROPN
ejpam-5923	69	3	appl	appl	PROPN
ejpam-5923	69	4	.	.	PROPN
ejpam-5923	69	5	math	math	PROPN
ejpam-5923	69	6	,	,	PUNCT
ejpam-5923	69	7	18	18	NUM
ejpam-5923	69	8	(	(	PUNCT
ejpam-5923	69	9	2	2	NUM
ejpam-5923	69	10	)	)	PUNCT
ejpam-5923	69	11	(	(	PUNCT
ejpam-5923	69	12	2025	2025	NUM
ejpam-5923	69	13	)	)	PUNCT
ejpam-5923	69	14	,	,	PUNCT
ejpam-5923	69	15	5923	5923	NUM
ejpam-5923	69	16	4	4	NUM
ejpam-5923	69	17	of	of	ADP
ejpam-5923	69	18	21∫	21∫	NUM
ejpam-5923	70	1	1	1	NUM
ejpam-5923	70	2	0	0	NUM
ejpam-5923	70	3	c	c	NOUN
ejpam-5923	70	4	(	(	PUNCT
ejpam-5923	70	5	t−	t−	PROPN
ejpam-5923	70	6	a)2	a)2	NOUN
ejpam-5923	70	7	dt	dt	NOUN
ejpam-5923	71	1	=	=	SYM
ejpam-5923	71	2	1	1	NUM
ejpam-5923	71	3	c	c	NOUN
ejpam-5923	71	4	=	=	SYM
ejpam-5923	71	5	3	3	NUM
ejpam-5923	71	6	(	(	PUNCT
ejpam-5923	71	7	1−	1−	NUM
ejpam-5923	71	8	a)3	a)3	ADJ
ejpam-5923	71	9	+	+	NUM
ejpam-5923	71	10	a3	a3	NOUN
ejpam-5923	71	11	.	.	PUNCT
ejpam-5923	72	1	now	now	ADV
ejpam-5923	72	2	,	,	PUNCT
ejpam-5923	72	3	f∗(t	f∗(t	NOUN
ejpam-5923	72	4	)	)	PUNCT
ejpam-5923	72	5	becomes	become	VERB
ejpam-5923	72	6	f∗(t	f∗(t	NOUN
ejpam-5923	72	7	)	)	PUNCT
ejpam-5923	72	8	=	=	SYM
ejpam-5923	72	9	3	3	NUM
ejpam-5923	72	10	(	(	PUNCT
ejpam-5923	72	11	1−	1−	NUM
ejpam-5923	72	12	a)3	a)3	ADJ
ejpam-5923	72	13	+	+	NUM
ejpam-5923	72	14	a3	a3	NOUN
ejpam-5923	72	15	(	(	PUNCT
ejpam-5923	72	16	t−	t−	PROPN
ejpam-5923	72	17	a)2	a)2	PROPN
ejpam-5923	72	18	.	.	PUNCT
ejpam-5923	73	1	(	(	PUNCT
ejpam-5923	73	2	4	4	X
ejpam-5923	73	3	)	)	PUNCT
ejpam-5923	73	4	observe	observe	VERB
ejpam-5923	73	5	that	that	SCONJ
ejpam-5923	73	6	f∗(t	f∗(t	NOUN
ejpam-5923	73	7	)	)	PUNCT
ejpam-5923	73	8	is	be	AUX
ejpam-5923	73	9	a	a	DET
ejpam-5923	73	10	non	non	ADJ
ejpam-5923	73	11	-	-	ADJ
ejpam-5923	73	12	negative	negative	ADJ
ejpam-5923	73	13	function	function	NOUN
ejpam-5923	73	14	(	(	PUNCT
ejpam-5923	73	15	f∗(t	f∗(t	PROPN
ejpam-5923	73	16	)	)	PUNCT
ejpam-5923	73	17	≥	≥	NOUN
ejpam-5923	73	18	0	0	NUM
ejpam-5923	73	19	)	)	PUNCT
ejpam-5923	73	20	since	since	SCONJ
ejpam-5923	73	21	for	for	ADP
ejpam-5923	73	22	a	a	DET
ejpam-5923	73	23	∈	∈	PROPN
ejpam-5923	74	1	[	[	X
ejpam-5923	74	2	0	0	NUM
ejpam-5923	74	3	,	,	PUNCT
ejpam-5923	74	4	1	1	NUM
ejpam-5923	74	5	]	]	PUNCT
ejpam-5923	74	6	,	,	PUNCT
ejpam-5923	74	7	t	t	PROPN
ejpam-5923	74	8	∈	∈	PROPN
ejpam-5923	75	1	[	[	X
ejpam-5923	75	2	0	0	NUM
ejpam-5923	75	3	,	,	PUNCT
ejpam-5923	75	4	1	1	NUM
ejpam-5923	75	5	]	]	PUNCT
ejpam-5923	75	6	,	,	PUNCT
ejpam-5923	75	7	the	the	DET
ejpam-5923	75	8	expression	expression	NOUN
ejpam-5923	75	9	(	(	PUNCT
ejpam-5923	75	10	t−	t−	PROPN
ejpam-5923	75	11	a)2	a)2	PROPN
ejpam-5923	75	12	≥	≥	NOUN
ejpam-5923	75	13	0	0	NUM
ejpam-5923	75	14	and	and	CCONJ
ejpam-5923	75	15	3	3	NUM
ejpam-5923	75	16	(	(	PUNCT
ejpam-5923	75	17	1−a)3+(a)3	1−a)3+(a)3	NUM
ejpam-5923	75	18	>	>	SYM
ejpam-5923	75	19	0	0	NUM
ejpam-5923	75	20	.	.	PUNCT
ejpam-5923	76	1	thus	thus	ADV
ejpam-5923	76	2	,	,	PUNCT
ejpam-5923	76	3	f∗(t	f∗(t	NOUN
ejpam-5923	76	4	)	)	PUNCT
ejpam-5923	76	5	is	be	AUX
ejpam-5923	76	6	a	a	DET
ejpam-5923	76	7	pdf	pdf	NOUN
ejpam-5923	76	8	.	.	PUNCT
ejpam-5923	77	1	substituting	substitute	VERB
ejpam-5923	77	2	f∗(t	f∗(t	NOUN
ejpam-5923	77	3	)	)	PUNCT
ejpam-5923	77	4	into	into	ADP
ejpam-5923	77	5	equation	equation	NOUN
ejpam-5923	77	6	(	(	PUNCT
ejpam-5923	77	7	2	2	NUM
ejpam-5923	77	8	)	)	PUNCT
ejpam-5923	77	9	for	for	ADP
ejpam-5923	77	10	f2(t	f2(t	PROPN
ejpam-5923	77	11	)	)	PUNCT
ejpam-5923	77	12	,	,	PUNCT
ejpam-5923	77	13	we	we	PRON
ejpam-5923	77	14	get	get	VERB
ejpam-5923	77	15	f(t	f(t	NOUN
ejpam-5923	77	16	)	)	PUNCT
ejpam-5923	77	17	=	=	SYM
ejpam-5923	78	1	1−	1−	NUM
ejpam-5923	78	2	λ+	λ+	PUNCT
ejpam-5923	78	3	3λ	3λ	NUM
ejpam-5923	78	4	(	(	PUNCT
ejpam-5923	78	5	1−	1−	NUM
ejpam-5923	78	6	a)3	a)3	ADJ
ejpam-5923	78	7	+	+	NUM
ejpam-5923	78	8	a3	a3	NOUN
ejpam-5923	78	9	(	(	PUNCT
ejpam-5923	78	10	t−	t−	PROPN
ejpam-5923	78	11	a)2	a)2	PROPN
ejpam-5923	78	12	.	.	PUNCT
ejpam-5923	79	1	(	(	PUNCT
ejpam-5923	79	2	5	5	NUM
ejpam-5923	79	3	)	)	PUNCT
ejpam-5923	79	4	next	next	ADV
ejpam-5923	79	5	,	,	PUNCT
ejpam-5923	79	6	to	to	PART
ejpam-5923	79	7	determine	determine	VERB
ejpam-5923	79	8	the	the	DET
ejpam-5923	79	9	values	value	NOUN
ejpam-5923	79	10	for	for	ADP
ejpam-5923	79	11	λ	λ	NOUN
ejpam-5923	79	12	,	,	PUNCT
ejpam-5923	79	13	note	note	VERB
ejpam-5923	79	14	that	that	SCONJ
ejpam-5923	79	15	from	from	ADP
ejpam-5923	79	16	the	the	DET
ejpam-5923	79	17	esu	esu	NOUN
ejpam-5923	79	18	distribution	distribution	NOUN
ejpam-5923	79	19	the	the	DET
ejpam-5923	79	20	λ	λ	NOUN
ejpam-5923	79	21	should	should	AUX
ejpam-5923	79	22	be	be	AUX
ejpam-5923	79	23	between	between	ADP
ejpam-5923	79	24	−0.5	−0.5	PROPN
ejpam-5923	79	25	and	and	CCONJ
ejpam-5923	79	26	1	1	NUM
ejpam-5923	79	27	inclusive	inclusive	NOUN
ejpam-5923	79	28	,	,	PUNCT
ejpam-5923	79	29	that	that	ADV
ejpam-5923	79	30	is	is	ADV
ejpam-5923	79	31	,	,	PUNCT
ejpam-5923	79	32	λ	λ	PROPN
ejpam-5923	79	33	∈	∈	PROPN
ejpam-5923	80	1	[	[	X
ejpam-5923	80	2	−0.5	−0.5	PROPN
ejpam-5923	80	3	,	,	PUNCT
ejpam-5923	80	4	1	1	NUM
ejpam-5923	80	5	]	]	PUNCT
ejpam-5923	80	6	.	.	PUNCT
ejpam-5923	81	1	now	now	ADV
ejpam-5923	81	2	,	,	PUNCT
ejpam-5923	81	3	consider	consider	VERB
ejpam-5923	81	4	the	the	DET
ejpam-5923	81	5	non	non	ADJ
ejpam-5923	81	6	-	-	NOUN
ejpam-5923	81	7	negativity	negativity	NOUN
ejpam-5923	81	8	of	of	ADP
ejpam-5923	81	9	f(t	f(t	NOUN
ejpam-5923	81	10	)	)	PUNCT
ejpam-5923	81	11	that	that	PRON
ejpam-5923	81	12	is	be	AUX
ejpam-5923	81	13	,	,	PUNCT
ejpam-5923	81	14	1−	1−	NUM
ejpam-5923	81	15	λ+	λ+	PUNCT
ejpam-5923	81	16	3λ(t−	3λ(t−	NUM
ejpam-5923	81	17	a)2	a)2	NOUN
ejpam-5923	81	18	(	(	PUNCT
ejpam-5923	81	19	1−	1−	NUM
ejpam-5923	81	20	a)3	a)3	ADJ
ejpam-5923	81	21	+	+	NUM
ejpam-5923	81	22	a3	a3	NOUN
ejpam-5923	81	23	≥	≥	NOUN
ejpam-5923	81	24	0	0	NUM
ejpam-5923	81	25	.	.	PUNCT
ejpam-5923	82	1	for	for	ADP
ejpam-5923	82	2	t	t	NOUN
ejpam-5923	82	3	=	=	SYM
ejpam-5923	82	4	0	0	NUM
ejpam-5923	82	5	we	we	PRON
ejpam-5923	82	6	have	have	VERB
ejpam-5923	82	7	λ	λ	X
ejpam-5923	82	8	[	[	PUNCT
ejpam-5923	82	9	3a2	3a2	NUM
ejpam-5923	82	10	−	−	NOUN
ejpam-5923	82	11	(	(	PUNCT
ejpam-5923	82	12	1−	1−	NUM
ejpam-5923	82	13	a)3	a)3	ADJ
ejpam-5923	82	14	−	−	PROPN
ejpam-5923	82	15	a3	a3	NOUN
ejpam-5923	82	16	(	(	PUNCT
ejpam-5923	82	17	1−	1−	NUM
ejpam-5923	82	18	a)3	a)3	ADJ
ejpam-5923	82	19	+	+	NUM
ejpam-5923	82	20	a3	a3	NOUN
ejpam-5923	82	21	]	]	PUNCT
ejpam-5923	82	22	≥	≥	X
ejpam-5923	82	23	−1	−1	NOUN
ejpam-5923	82	24	.	.	PUNCT
ejpam-5923	83	1	for	for	ADP
ejpam-5923	83	2	3a2	3a2	NUM
ejpam-5923	83	3	−	−	PROPN
ejpam-5923	83	4	(	(	PUNCT
ejpam-5923	83	5	1−	1−	NUM
ejpam-5923	83	6	a)3	a)3	ADJ
ejpam-5923	83	7	−	−	PROPN
ejpam-5923	83	8	a3	a3	NOUN
ejpam-5923	83	9	̸=	̸=	PROPN
ejpam-5923	83	10	0	0	NUM
ejpam-5923	83	11	,	,	PUNCT
ejpam-5923	83	12	and	and	CCONJ
ejpam-5923	83	13	3a2	3a2	NUM
ejpam-5923	83	14	(	(	PUNCT
ejpam-5923	83	15	1−	1−	NUM
ejpam-5923	83	16	a)3	a)3	ADJ
ejpam-5923	83	17	+	+	NUM
ejpam-5923	83	18	a3	a3	NOUN
ejpam-5923	83	19	−	−	NOUN
ejpam-5923	83	20	1	1	NUM
ejpam-5923	83	21	>	>	X
ejpam-5923	83	22	0	0	NUM
ejpam-5923	83	23	,	,	PUNCT
ejpam-5923	83	24	we	we	PRON
ejpam-5923	83	25	have	have	VERB
ejpam-5923	83	26	λ	λ	PROPN
ejpam-5923	83	27	≥	≥	PRON
ejpam-5923	83	28	−	−	PROPN
ejpam-5923	83	29	(	(	PUNCT
ejpam-5923	83	30	1−	1−	NUM
ejpam-5923	83	31	a)3	a)3	ADJ
ejpam-5923	83	32	+	+	NUM
ejpam-5923	83	33	a3	a3	VERB
ejpam-5923	83	34	3a2	3a2	NUM
ejpam-5923	83	35	−	−	PROPN
ejpam-5923	83	36	(	(	PUNCT
ejpam-5923	83	37	1−	1−	NUM
ejpam-5923	83	38	a)3	a)3	ADJ
ejpam-5923	83	39	−	−	PROPN
ejpam-5923	83	40	a3	a3	NOUN
ejpam-5923	83	41	,	,	PUNCT
ejpam-5923	83	42	and	and	CCONJ
ejpam-5923	83	43	for	for	ADP
ejpam-5923	83	44	3a2	3a2	NUM
ejpam-5923	83	45	(	(	PUNCT
ejpam-5923	83	46	1−	1−	NUM
ejpam-5923	83	47	a)3	a)3	ADJ
ejpam-5923	83	48	+	+	NUM
ejpam-5923	83	49	a3	a3	NOUN
ejpam-5923	83	50	−	−	NOUN
ejpam-5923	83	51	1	1	NUM
ejpam-5923	83	52	<	<	X
ejpam-5923	83	53	0	0	NUM
ejpam-5923	83	54	,	,	PUNCT
ejpam-5923	83	55	we	we	PRON
ejpam-5923	83	56	have	have	VERB
ejpam-5923	83	57	λ	λ	NOUN
ejpam-5923	83	58	≤	≤	NUM
ejpam-5923	83	59	(	(	PUNCT
ejpam-5923	83	60	1−	1−	NUM
ejpam-5923	83	61	a)3	a)3	ADJ
ejpam-5923	83	62	+	+	NUM
ejpam-5923	83	63	a3	a3	VERB
ejpam-5923	83	64	3a2	3a2	NUM
ejpam-5923	83	65	−	−	PROPN
ejpam-5923	83	66	(	(	PUNCT
ejpam-5923	83	67	1−	1−	NUM
ejpam-5923	83	68	a)3	a)3	ADJ
ejpam-5923	83	69	−	−	PROPN
ejpam-5923	83	70	a3	a3	NOUN
ejpam-5923	83	71	.	.	PUNCT
ejpam-5923	84	1	the	the	DET
ejpam-5923	84	2	relations	relation	NOUN
ejpam-5923	84	3	above	above	ADV
ejpam-5923	84	4	imply	imply	VERB
ejpam-5923	84	5	that	that	SCONJ
ejpam-5923	84	6	λ	λ	PROPN
ejpam-5923	84	7	∈	∈	PROPN
ejpam-5923	84	8	[	[	PUNCT
ejpam-5923	84	9	−	−	PROPN
ejpam-5923	84	10	(	(	PUNCT
ejpam-5923	84	11	1−	1−	NUM
ejpam-5923	84	12	a)3	a)3	ADJ
ejpam-5923	84	13	+	+	NUM
ejpam-5923	84	14	a3	a3	VERB
ejpam-5923	84	15	3a2	3a2	NUM
ejpam-5923	84	16	−	−	PROPN
ejpam-5923	84	17	(	(	PUNCT
ejpam-5923	84	18	1−	1−	NUM
ejpam-5923	84	19	a)3	a)3	ADJ
ejpam-5923	84	20	−	−	PROPN
ejpam-5923	84	21	a3	a3	NOUN
ejpam-5923	84	22	,	,	PUNCT
ejpam-5923	84	23	(	(	PUNCT
ejpam-5923	84	24	1−	1−	NUM
ejpam-5923	84	25	a)3	a)3	ADJ
ejpam-5923	84	26	+	+	NUM
ejpam-5923	84	27	a3	a3	VERB
ejpam-5923	84	28	3a2	3a2	NUM
ejpam-5923	84	29	−	−	PROPN
ejpam-5923	84	30	(	(	PUNCT
ejpam-5923	84	31	1−	1−	NUM
ejpam-5923	84	32	a)3	a)3	ADJ
ejpam-5923	84	33	−	−	PROPN
ejpam-5923	84	34	a3	a3	NOUN
ejpam-5923	84	35	]	]	PUNCT
ejpam-5923	84	36	.	.	PUNCT
ejpam-5923	85	1	for	for	ADP
ejpam-5923	85	2	t	t	NOUN
ejpam-5923	85	3	=	=	SYM
ejpam-5923	85	4	1	1	NUM
ejpam-5923	85	5	we	we	PRON
ejpam-5923	85	6	have	have	VERB
ejpam-5923	85	7	λ	λ	X
ejpam-5923	85	8	[	[	PUNCT
ejpam-5923	85	9	3(1−	3(1−	NUM
ejpam-5923	85	10	a)2	a)2	NOUN
ejpam-5923	85	11	−	−	PROPN
ejpam-5923	85	12	(	(	PUNCT
ejpam-5923	85	13	1−	1−	NUM
ejpam-5923	85	14	a)3	a)3	ADJ
ejpam-5923	85	15	−	−	PROPN
ejpam-5923	85	16	a3	a3	NOUN
ejpam-5923	85	17	(	(	PUNCT
ejpam-5923	85	18	1−	1−	NUM
ejpam-5923	85	19	a)3	a)3	ADJ
ejpam-5923	85	20	+	+	NUM
ejpam-5923	85	21	a3	a3	NOUN
ejpam-5923	85	22	]	]	PUNCT
ejpam-5923	85	23	≥	≥	X
ejpam-5923	85	24	−1	−1	NOUN
ejpam-5923	85	25	.	.	PUNCT
ejpam-5923	86	1	i.	i.	PROPN
ejpam-5923	86	2	a.	a.	PROPN
ejpam-5923	86	3	lakibul	lakibul	PROPN
ejpam-5923	86	4	,	,	PUNCT
ejpam-5923	86	5	d.	d.	PROPN
ejpam-5923	86	6	l.	l.	PROPN
ejpam-5923	86	7	polestico	polestico	PROPN
ejpam-5923	86	8	,	,	PUNCT
ejpam-5923	86	9	a.	a.	PROPN
ejpam-5923	86	10	p.	p.	NOUN
ejpam-5923	86	11	supe	supe	PROPN
ejpam-5923	86	12	/	/	SYM
ejpam-5923	86	13	eur	eur	PROPN
ejpam-5923	86	14	.	.	PUNCT
ejpam-5923	87	1	j.	j.	PROPN
ejpam-5923	87	2	pure	pure	PROPN
ejpam-5923	87	3	appl	appl	PROPN
ejpam-5923	87	4	.	.	PROPN
ejpam-5923	87	5	math	math	PROPN
ejpam-5923	87	6	,	,	PUNCT
ejpam-5923	87	7	18	18	NUM
ejpam-5923	87	8	(	(	PUNCT
ejpam-5923	87	9	2	2	NUM
ejpam-5923	87	10	)	)	PUNCT
ejpam-5923	87	11	(	(	PUNCT
ejpam-5923	87	12	2025	2025	NUM
ejpam-5923	87	13	)	)	PUNCT
ejpam-5923	87	14	,	,	PUNCT
ejpam-5923	87	15	5923	5923	NUM
ejpam-5923	87	16	5	5	NUM
ejpam-5923	87	17	of	of	ADP
ejpam-5923	87	18	21	21	NUM
ejpam-5923	87	19	for	for	ADP
ejpam-5923	87	20	3(1−	3(1−	NUM
ejpam-5923	87	21	a)2	a)2	PROPN
ejpam-5923	87	22	−	−	PROPN
ejpam-5923	87	23	(	(	PUNCT
ejpam-5923	87	24	1−	1−	NUM
ejpam-5923	87	25	a)3	a)3	ADJ
ejpam-5923	87	26	−	−	PROPN
ejpam-5923	87	27	a3	a3	NOUN
ejpam-5923	87	28	̸=	̸=	PROPN
ejpam-5923	87	29	0	0	NUM
ejpam-5923	87	30	and	and	CCONJ
ejpam-5923	87	31	3(1−	3(1−	NUM
ejpam-5923	87	32	a)2	a)2	PROPN
ejpam-5923	87	33	(	(	PUNCT
ejpam-5923	87	34	1−	1−	NUM
ejpam-5923	87	35	a)3	a)3	ADJ
ejpam-5923	87	36	+	+	NUM
ejpam-5923	87	37	a3	a3	NOUN
ejpam-5923	87	38	−	−	NOUN
ejpam-5923	87	39	1	1	NUM
ejpam-5923	87	40	>	>	SYM
ejpam-5923	87	41	0	0	NUM
ejpam-5923	88	1	we	we	PRON
ejpam-5923	88	2	have	have	VERB
ejpam-5923	88	3	λ	λ	PROPN
ejpam-5923	88	4	≥	≥	PRON
ejpam-5923	88	5	−	−	PROPN
ejpam-5923	88	6	(	(	PUNCT
ejpam-5923	88	7	1−	1−	NUM
ejpam-5923	88	8	a)3	a)3	ADJ
ejpam-5923	88	9	+	+	NUM
ejpam-5923	88	10	a3	a3	VERB
ejpam-5923	88	11	3(1−	3(1−	NUM
ejpam-5923	88	12	a)2	a)2	PROPN
ejpam-5923	88	13	−	−	PROPN
ejpam-5923	88	14	(	(	PUNCT
ejpam-5923	88	15	1−	1−	NUM
ejpam-5923	88	16	a)3	a)3	ADJ
ejpam-5923	88	17	−	−	PROPN
ejpam-5923	88	18	a3	a3	NOUN
ejpam-5923	88	19	,	,	PUNCT
ejpam-5923	88	20	and	and	CCONJ
ejpam-5923	88	21	for	for	ADP
ejpam-5923	88	22	3(1−	3(1−	NUM
ejpam-5923	88	23	a)2	a)2	PROPN
ejpam-5923	88	24	(	(	PUNCT
ejpam-5923	88	25	1−	1−	NUM
ejpam-5923	88	26	a)3	a)3	ADJ
ejpam-5923	88	27	+	+	NUM
ejpam-5923	88	28	a3	a3	NOUN
ejpam-5923	88	29	−	−	NOUN
ejpam-5923	88	30	1	1	NUM
ejpam-5923	88	31	<	<	X
ejpam-5923	88	32	0	0	NUM
ejpam-5923	89	1	we	we	PRON
ejpam-5923	89	2	have	have	VERB
ejpam-5923	89	3	λ	λ	NOUN
ejpam-5923	89	4	≤	≤	NUM
ejpam-5923	89	5	(	(	PUNCT
ejpam-5923	89	6	1−	1−	NUM
ejpam-5923	89	7	a)3	a)3	ADJ
ejpam-5923	89	8	+	+	NUM
ejpam-5923	89	9	a3	a3	VERB
ejpam-5923	89	10	3(1−	3(1−	NUM
ejpam-5923	89	11	a)2	a)2	PROPN
ejpam-5923	89	12	−	−	PROPN
ejpam-5923	89	13	(	(	PUNCT
ejpam-5923	89	14	1−	1−	NUM
ejpam-5923	89	15	a)3	a)3	ADJ
ejpam-5923	89	16	−	−	PROPN
ejpam-5923	89	17	a3	a3	NOUN
ejpam-5923	89	18	.	.	PUNCT
ejpam-5923	90	1	these	these	PRON
ejpam-5923	90	2	imply	imply	VERB
ejpam-5923	90	3	that	that	SCONJ
ejpam-5923	90	4	λ	λ	PROPN
ejpam-5923	90	5	∈	∈	PROPN
ejpam-5923	90	6	[	[	PUNCT
ejpam-5923	90	7	−	−	PROPN
ejpam-5923	90	8	(	(	PUNCT
ejpam-5923	90	9	1−	1−	NUM
ejpam-5923	90	10	a)3	a)3	ADJ
ejpam-5923	90	11	+	+	NUM
ejpam-5923	90	12	a3	a3	VERB
ejpam-5923	90	13	3(1−	3(1−	NUM
ejpam-5923	90	14	a)2	a)2	PROPN
ejpam-5923	90	15	−	−	PROPN
ejpam-5923	90	16	(	(	PUNCT
ejpam-5923	90	17	1−	1−	NUM
ejpam-5923	90	18	a)3	a)3	ADJ
ejpam-5923	90	19	−	−	PROPN
ejpam-5923	90	20	a3	a3	NOUN
ejpam-5923	90	21	,	,	PUNCT
ejpam-5923	90	22	(	(	PUNCT
ejpam-5923	90	23	1−	1−	NUM
ejpam-5923	90	24	a)3	a)3	ADJ
ejpam-5923	90	25	+	+	NUM
ejpam-5923	90	26	a3	a3	VERB
ejpam-5923	90	27	3(1−	3(1−	NUM
ejpam-5923	90	28	a)2	a)2	PROPN
ejpam-5923	90	29	−	−	PROPN
ejpam-5923	90	30	(	(	PUNCT
ejpam-5923	90	31	1−	1−	NUM
ejpam-5923	90	32	a)3	a)3	ADJ
ejpam-5923	90	33	−	−	PROPN
ejpam-5923	90	34	a3	a3	NOUN
ejpam-5923	90	35	]	]	PUNCT
ejpam-5923	90	36	.	.	PUNCT
ejpam-5923	91	1	note	note	VERB
ejpam-5923	91	2	that	that	SCONJ
ejpam-5923	91	3	we	we	PRON
ejpam-5923	91	4	have	have	VERB
ejpam-5923	91	5			PRON
ejpam-5923	91	6	(	(	PUNCT
ejpam-5923	91	7	1−	1−	NUM
ejpam-5923	91	8	a)2	a)2	PROPN
ejpam-5923	91	9	>	>	X
ejpam-5923	91	10	a2	a2	PROPN
ejpam-5923	91	11	if	if	SCONJ
ejpam-5923	91	12	a	a	DET
ejpam-5923	91	13	<	<	X
ejpam-5923	91	14	1	1	NUM
ejpam-5923	91	15	2	2	NUM
ejpam-5923	91	16	(	(	PUNCT
ejpam-5923	91	17	1−	1−	NUM
ejpam-5923	91	18	a)2	a)2	NOUN
ejpam-5923	91	19	=	=	SYM
ejpam-5923	91	20	a2	a2	PROPN
ejpam-5923	91	21	if	if	SCONJ
ejpam-5923	91	22	a	a	DET
ejpam-5923	91	23	=	=	SYM
ejpam-5923	91	24	1	1	NUM
ejpam-5923	91	25	2	2	NUM
ejpam-5923	91	26	(	(	PUNCT
ejpam-5923	91	27	1−	1−	NUM
ejpam-5923	91	28	a)2	a)2	PROPN
ejpam-5923	91	29	<	<	X
ejpam-5923	91	30	a2	a2	PROPN
ejpam-5923	91	31	if	if	SCONJ
ejpam-5923	91	32	a	a	DET
ejpam-5923	91	33	>	>	X
ejpam-5923	91	34	1	1	NUM
ejpam-5923	91	35	2	2	NUM
ejpam-5923	91	36	.	.	PUNCT
ejpam-5923	92	1	by	by	ADP
ejpam-5923	92	2	taking	take	VERB
ejpam-5923	92	3	the	the	DET
ejpam-5923	92	4	union	union	NOUN
ejpam-5923	92	5	of	of	ADP
ejpam-5923	92	6	the	the	DET
ejpam-5923	92	7	possible	possible	ADJ
ejpam-5923	92	8	values	value	NOUN
ejpam-5923	92	9	of	of	ADP
ejpam-5923	92	10	λ	λ	PROPN
ejpam-5923	92	11	for	for	ADP
ejpam-5923	92	12	t	t	NOUN
ejpam-5923	92	13	=	=	SYM
ejpam-5923	92	14	0	0	NUM
ejpam-5923	92	15	and	and	CCONJ
ejpam-5923	92	16	t	t	X
ejpam-5923	92	17	=	=	SYM
ejpam-5923	92	18	1	1	NUM
ejpam-5923	92	19	,	,	PUNCT
ejpam-5923	92	20	we	we	PRON
ejpam-5923	92	21	have	have	VERB
ejpam-5923	92	22	λ	λ	X
ejpam-5923	92	23	∈	∈	PRON
ejpam-5923	92	24			X
ejpam-5923	92	25	[	[	PUNCT
ejpam-5923	92	26	−	−	X
ejpam-5923	92	27	(	(	PUNCT
ejpam-5923	92	28	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	92	29	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	92	30	,	,	PUNCT
ejpam-5923	92	31	(	(	PUNCT
ejpam-5923	92	32	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	92	33	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	92	34	]	]	PUNCT
ejpam-5923	92	35	,	,	PUNCT
ejpam-5923	92	36	if	if	SCONJ
ejpam-5923	92	37	a	a	DET
ejpam-5923	92	38	∈	∈	NOUN
ejpam-5923	93	1	[	[	X
ejpam-5923	93	2	0	0	NUM
ejpam-5923	93	3	,	,	PUNCT
ejpam-5923	93	4	0.5	0.5	NUM
ejpam-5923	93	5	]	]	PUNCT
ejpam-5923	93	6	[	[	PUNCT
ejpam-5923	93	7	−	−	X
ejpam-5923	93	8	(	(	PUNCT
ejpam-5923	93	9	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	93	10	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	93	11	,	,	PUNCT
ejpam-5923	93	12	(	(	PUNCT
ejpam-5923	93	13	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	93	14	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NOUN
ejpam-5923	93	15	]	]	PUNCT
ejpam-5923	93	16	,	,	PUNCT
ejpam-5923	93	17	if	if	SCONJ
ejpam-5923	93	18	a	a	DET
ejpam-5923	93	19	∈	∈	NOUN
ejpam-5923	93	20	[	[	X
ejpam-5923	93	21	0.5	0.5	NUM
ejpam-5923	93	22	,	,	PUNCT
ejpam-5923	93	23	1	1	NUM
ejpam-5923	93	24	]	]	PUNCT
ejpam-5923	93	25	.	.	PUNCT
ejpam-5923	94	1	now	now	ADV
ejpam-5923	94	2	,	,	PUNCT
ejpam-5923	94	3	combining	combine	VERB
ejpam-5923	94	4	or	or	CCONJ
ejpam-5923	94	5	taking	take	VERB
ejpam-5923	94	6	the	the	DET
ejpam-5923	94	7	intersection	intersection	NOUN
ejpam-5923	94	8	of	of	ADP
ejpam-5923	94	9	the	the	DET
ejpam-5923	94	10	possible	possible	ADJ
ejpam-5923	94	11	values	value	NOUN
ejpam-5923	94	12	of	of	ADP
ejpam-5923	94	13	λ	λ	PROPN
ejpam-5923	94	14	∈	∈	PROPN
ejpam-5923	95	1	[	[	X
ejpam-5923	95	2	−0.5	−0.5	PROPN
ejpam-5923	95	3	,	,	PUNCT
ejpam-5923	95	4	1	1	NUM
ejpam-5923	95	5	]	]	PUNCT
ejpam-5923	95	6	and	and	CCONJ
ejpam-5923	95	7	λ	λ	PART
ejpam-5923	95	8	∈	∈	PROPN
ejpam-5923	95	9			X
ejpam-5923	95	10	[	[	PUNCT
ejpam-5923	95	11	−	−	X
ejpam-5923	95	12	(	(	PUNCT
ejpam-5923	95	13	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	95	14	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	95	15	,	,	PUNCT
ejpam-5923	95	16	(	(	PUNCT
ejpam-5923	95	17	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	95	18	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	95	19	]	]	PUNCT
ejpam-5923	95	20	,	,	PUNCT
ejpam-5923	95	21	if	if	SCONJ
ejpam-5923	95	22	a	a	DET
ejpam-5923	95	23	∈	∈	NOUN
ejpam-5923	96	1	[	[	X
ejpam-5923	96	2	0	0	NUM
ejpam-5923	96	3	,	,	PUNCT
ejpam-5923	96	4	0.5	0.5	NUM
ejpam-5923	96	5	]	]	PUNCT
ejpam-5923	96	6	[	[	PUNCT
ejpam-5923	96	7	−	−	X
ejpam-5923	96	8	(	(	PUNCT
ejpam-5923	96	9	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	96	10	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	96	11	,	,	PUNCT
ejpam-5923	96	12	(	(	PUNCT
ejpam-5923	96	13	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	96	14	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NOUN
ejpam-5923	96	15	]	]	PUNCT
ejpam-5923	96	16	,	,	PUNCT
ejpam-5923	96	17	if	if	SCONJ
ejpam-5923	96	18	a	a	DET
ejpam-5923	96	19	∈	∈	NOUN
ejpam-5923	96	20	[	[	X
ejpam-5923	96	21	0.5	0.5	NUM
ejpam-5923	96	22	,	,	PUNCT
ejpam-5923	96	23	1	1	NUM
ejpam-5923	96	24	]	]	PUNCT
ejpam-5923	96	25	,	,	PUNCT
ejpam-5923	96	26	we	we	PRON
ejpam-5923	96	27	have	have	VERB
ejpam-5923	96	28	λ	λ	X
ejpam-5923	96	29	∈	∈	PRON
ejpam-5923	96	30			X
ejpam-5923	96	31	[	[	PUNCT
ejpam-5923	96	32	−	−	X
ejpam-5923	96	33	(	(	PUNCT
ejpam-5923	96	34	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	96	35	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	96	36	,	,	PUNCT
ejpam-5923	96	37	1	1	NUM
ejpam-5923	96	38	]	]	PUNCT
ejpam-5923	96	39	,	,	PUNCT
ejpam-5923	96	40	if	if	SCONJ
ejpam-5923	96	41	a	a	DET
ejpam-5923	96	42	∈	∈	NOUN
ejpam-5923	97	1	[	[	X
ejpam-5923	97	2	0	0	NUM
ejpam-5923	97	3	,	,	PUNCT
ejpam-5923	97	4	0.5	0.5	NUM
ejpam-5923	97	5	]	]	PUNCT
ejpam-5923	97	6	[	[	PUNCT
ejpam-5923	97	7	−	−	X
ejpam-5923	97	8	(	(	PUNCT
ejpam-5923	97	9	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	97	10	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	97	11	,	,	PUNCT
ejpam-5923	97	12	1	1	NUM
ejpam-5923	97	13	]	]	PUNCT
ejpam-5923	97	14	,	,	PUNCT
ejpam-5923	97	15	if	if	SCONJ
ejpam-5923	97	16	a	a	DET
ejpam-5923	97	17	∈	∈	NOUN
ejpam-5923	97	18	[	[	X
ejpam-5923	97	19	0.5	0.5	NUM
ejpam-5923	97	20	,	,	PUNCT
ejpam-5923	97	21	1	1	NUM
ejpam-5923	97	22	]	]	PUNCT
ejpam-5923	97	23	since	since	SCONJ
ejpam-5923	97	24	−	−	PROPN
ejpam-5923	97	25	(	(	PUNCT
ejpam-5923	97	26	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	97	27	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	97	28	≥	≥	NOUN
ejpam-5923	97	29	−1	−1	NOUN
ejpam-5923	97	30	2	2	NUM
ejpam-5923	97	31	for	for	ADP
ejpam-5923	97	32	a	a	DET
ejpam-5923	97	33	∈	∈	PROPN
ejpam-5923	98	1	[	[	X
ejpam-5923	98	2	0	0	NUM
ejpam-5923	98	3	,	,	PUNCT
ejpam-5923	98	4	0.5	0.5	NUM
ejpam-5923	98	5	]	]	PUNCT
ejpam-5923	98	6	,	,	PUNCT
ejpam-5923	98	7	and	and	CCONJ
ejpam-5923	98	8	−	−	PROPN
ejpam-5923	98	9	(	(	PUNCT
ejpam-5923	98	10	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	98	11	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	98	12	≥	≥	NOUN
ejpam-5923	98	13	−1	−1	NOUN
ejpam-5923	98	14	2	2	NUM
ejpam-5923	98	15	for	for	ADP
ejpam-5923	98	16	a	a	DET
ejpam-5923	98	17	∈	∈	PROPN
ejpam-5923	99	1	[	[	X
ejpam-5923	99	2	0.5	0.5	NUM
ejpam-5923	99	3	,	,	PUNCT
ejpam-5923	99	4	1	1	NUM
ejpam-5923	99	5	]	]	PUNCT
ejpam-5923	99	6	.	.	PUNCT
ejpam-5923	100	1	i.	i.	PROPN
ejpam-5923	100	2	a.	a.	PROPN
ejpam-5923	100	3	lakibul	lakibul	PROPN
ejpam-5923	100	4	,	,	PUNCT
ejpam-5923	100	5	d.	d.	PROPN
ejpam-5923	100	6	l.	l.	PROPN
ejpam-5923	100	7	polestico	polestico	PROPN
ejpam-5923	100	8	,	,	PUNCT
ejpam-5923	100	9	a.	a.	PROPN
ejpam-5923	100	10	p.	p.	NOUN
ejpam-5923	100	11	supe	supe	PROPN
ejpam-5923	100	12	/	/	SYM
ejpam-5923	100	13	eur	eur	PROPN
ejpam-5923	100	14	.	.	PUNCT
ejpam-5923	101	1	j.	j.	PROPN
ejpam-5923	101	2	pure	pure	PROPN
ejpam-5923	101	3	appl	appl	PROPN
ejpam-5923	101	4	.	.	PROPN
ejpam-5923	101	5	math	math	PROPN
ejpam-5923	101	6	,	,	PUNCT
ejpam-5923	101	7	18	18	NUM
ejpam-5923	101	8	(	(	PUNCT
ejpam-5923	101	9	2	2	NUM
ejpam-5923	101	10	)	)	PUNCT
ejpam-5923	101	11	(	(	PUNCT
ejpam-5923	101	12	2025	2025	NUM
ejpam-5923	101	13	)	)	PUNCT
ejpam-5923	101	14	,	,	PUNCT
ejpam-5923	101	15	5923	5923	NUM
ejpam-5923	101	16	6	6	NUM
ejpam-5923	101	17	of	of	ADP
ejpam-5923	101	18	21	21	NUM
ejpam-5923	101	19	definition	definition	NOUN
ejpam-5923	101	20	1	1	NUM
ejpam-5923	101	21	.	.	PUNCT
ejpam-5923	102	1	a	a	DET
ejpam-5923	102	2	random	random	ADJ
ejpam-5923	102	3	variable	variable	NOUN
ejpam-5923	102	4	t	t	PROPN
ejpam-5923	102	5	is	be	AUX
ejpam-5923	102	6	said	say	VERB
ejpam-5923	102	7	to	to	PART
ejpam-5923	102	8	have	have	VERB
ejpam-5923	102	9	a	a	DET
ejpam-5923	102	10	generalized	generalize	VERB
ejpam-5923	102	11	extended	extend	VERB
ejpam-5923	102	12	standard	standard	ADJ
ejpam-5923	102	13	uquadratic	uquadratic	ADJ
ejpam-5923	102	14	(	(	PUNCT
ejpam-5923	102	15	gesu	gesu	PROPN
ejpam-5923	102	16	)	)	PUNCT
ejpam-5923	102	17	distribution	distribution	NOUN
ejpam-5923	102	18	if	if	SCONJ
ejpam-5923	102	19	its	its	PRON
ejpam-5923	102	20	pdf	pdf	NOUN
ejpam-5923	102	21	is	be	AUX
ejpam-5923	102	22	given	give	VERB
ejpam-5923	102	23	by	by	ADP
ejpam-5923	102	24	f(t	f(t	NOUN
ejpam-5923	102	25	)	)	PUNCT
ejpam-5923	102	26	=	=	SYM
ejpam-5923	102	27	1−	1−	NUM
ejpam-5923	102	28	λ+	λ+	PUNCT
ejpam-5923	102	29	3λ	3λ	NUM
ejpam-5923	102	30	(	(	PUNCT
ejpam-5923	102	31	1−	1−	NUM
ejpam-5923	102	32	a)3	a)3	ADJ
ejpam-5923	102	33	+	+	NUM
ejpam-5923	102	34	a3	a3	NOUN
ejpam-5923	102	35	(	(	PUNCT
ejpam-5923	102	36	t−	t−	PROPN
ejpam-5923	102	37	a)2	a)2	PROPN
ejpam-5923	102	38	,	,	PUNCT
ejpam-5923	102	39	t	t	PROPN
ejpam-5923	102	40	∈	∈	PROPN
ejpam-5923	103	1	[	[	X
ejpam-5923	103	2	0	0	NUM
ejpam-5923	103	3	,	,	PUNCT
ejpam-5923	103	4	1	1	NUM
ejpam-5923	103	5	]	]	PUNCT
ejpam-5923	103	6	,	,	PUNCT
ejpam-5923	103	7	(	(	PUNCT
ejpam-5923	103	8	6	6	NUM
ejpam-5923	103	9	)	)	PUNCT
ejpam-5923	103	10	where	where	SCONJ
ejpam-5923	103	11	a	a	DET
ejpam-5923	103	12	∈	∈	NOUN
ejpam-5923	103	13	[	[	X
ejpam-5923	103	14	0	0	NUM
ejpam-5923	103	15	,	,	PUNCT
ejpam-5923	103	16	1	1	NUM
ejpam-5923	103	17	]	]	PUNCT
ejpam-5923	103	18	and	and	CCONJ
ejpam-5923	103	19	λ	λ	PART
ejpam-5923	103	20	∈	∈	PROPN
ejpam-5923	103	21			X
ejpam-5923	103	22	[	[	PUNCT
ejpam-5923	103	23	−	−	X
ejpam-5923	103	24	(	(	PUNCT
ejpam-5923	103	25	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	103	26	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	103	27	,	,	PUNCT
ejpam-5923	103	28	1	1	NUM
ejpam-5923	103	29	]	]	PUNCT
ejpam-5923	103	30	,	,	PUNCT
ejpam-5923	103	31	if	if	SCONJ
ejpam-5923	103	32	a	a	DET
ejpam-5923	103	33	∈	∈	NOUN
ejpam-5923	103	34	[	[	X
ejpam-5923	103	35	0	0	NUM
ejpam-5923	103	36	,	,	PUNCT
ejpam-5923	103	37	0.5	0.5	NUM
ejpam-5923	103	38	]	]	PUNCT
ejpam-5923	103	39	[	[	PUNCT
ejpam-5923	103	40	−	−	X
ejpam-5923	103	41	(	(	PUNCT
ejpam-5923	103	42	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	103	43	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	103	44	,	,	PUNCT
ejpam-5923	103	45	1	1	NUM
ejpam-5923	103	46	]	]	PUNCT
ejpam-5923	103	47	,	,	PUNCT
ejpam-5923	103	48	if	if	SCONJ
ejpam-5923	103	49	a	a	DET
ejpam-5923	103	50	∈	∈	NOUN
ejpam-5923	103	51	[	[	X
ejpam-5923	103	52	0.5	0.5	NUM
ejpam-5923	103	53	,	,	PUNCT
ejpam-5923	103	54	1	1	NUM
ejpam-5923	103	55	]	]	PUNCT
ejpam-5923	103	56	.	.	PUNCT
ejpam-5923	103	57	theorem	theorem	NOUN
ejpam-5923	103	58	1	1	X
ejpam-5923	103	59	.	.	PUNCT
ejpam-5923	104	1	let	let	VERB
ejpam-5923	104	2	t	t	NOUN
ejpam-5923	104	3	be	be	AUX
ejpam-5923	104	4	a	a	DET
ejpam-5923	104	5	random	random	ADJ
ejpam-5923	104	6	variable	variable	NOUN
ejpam-5923	104	7	that	that	PRON
ejpam-5923	104	8	follows	follow	VERB
ejpam-5923	104	9	a	a	DET
ejpam-5923	104	10	gesu	gesu	NOUN
ejpam-5923	104	11	distribution	distribution	NOUN
ejpam-5923	104	12	,	,	PUNCT
ejpam-5923	104	13	then	then	ADV
ejpam-5923	104	14	the	the	DET
ejpam-5923	104	15	cumulative	cumulative	ADJ
ejpam-5923	104	16	distribution	distribution	NOUN
ejpam-5923	104	17	function	function	NOUN
ejpam-5923	104	18	of	of	ADP
ejpam-5923	104	19	t	t	PROPN
ejpam-5923	104	20	is	be	AUX
ejpam-5923	104	21	given	give	VERB
ejpam-5923	104	22	by	by	ADP
ejpam-5923	104	23	f	f	PROPN
ejpam-5923	104	24	(	(	PUNCT
ejpam-5923	104	25	t	t	PROPN
ejpam-5923	104	26	)	)	PUNCT
ejpam-5923	104	27	=	=	PUNCT
ejpam-5923	104	28	(	(	PUNCT
ejpam-5923	105	1	1−	1−	NUM
ejpam-5923	105	2	λ)t+	λ)t+	NUM
ejpam-5923	105	3	λ	λ	NOUN
ejpam-5923	105	4	[	[	PUNCT
ejpam-5923	105	5	(	(	PUNCT
ejpam-5923	105	6	t−	t−	ADP
ejpam-5923	105	7	a)3	a)3	ADJ
ejpam-5923	105	8	+	+	NUM
ejpam-5923	105	9	a3	a3	NOUN
ejpam-5923	105	10	]	]	PUNCT
ejpam-5923	105	11	(	(	PUNCT
ejpam-5923	105	12	1−	1−	NUM
ejpam-5923	105	13	a)3	a)3	ADJ
ejpam-5923	105	14	+	+	NUM
ejpam-5923	105	15	a3	a3	NOUN
ejpam-5923	105	16	,	,	PUNCT
ejpam-5923	105	17	(	(	PUNCT
ejpam-5923	105	18	7	7	X
ejpam-5923	105	19	)	)	PUNCT
ejpam-5923	105	20	where	where	SCONJ
ejpam-5923	105	21	t	t	PROPN
ejpam-5923	105	22	∈	∈	PROPN
ejpam-5923	106	1	[	[	X
ejpam-5923	106	2	0	0	NUM
ejpam-5923	106	3	,	,	PUNCT
ejpam-5923	106	4	1	1	NUM
ejpam-5923	106	5	]	]	PUNCT
ejpam-5923	106	6	,	,	PUNCT
ejpam-5923	106	7	a	a	DET
ejpam-5923	106	8	∈	∈	NOUN
ejpam-5923	107	1	[	[	X
ejpam-5923	107	2	0	0	NUM
ejpam-5923	107	3	,	,	PUNCT
ejpam-5923	107	4	1	1	NUM
ejpam-5923	107	5	]	]	PUNCT
ejpam-5923	107	6	and	and	CCONJ
ejpam-5923	107	7	λ	λ	PART
ejpam-5923	107	8	∈	∈	PROPN
ejpam-5923	107	9			X
ejpam-5923	107	10	[	[	PUNCT
ejpam-5923	107	11	−	−	X
ejpam-5923	107	12	(	(	PUNCT
ejpam-5923	107	13	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	107	14	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	107	15	,	,	PUNCT
ejpam-5923	107	16	1	1	NUM
ejpam-5923	107	17	]	]	PUNCT
ejpam-5923	107	18	,	,	PUNCT
ejpam-5923	107	19	if	if	SCONJ
ejpam-5923	107	20	a	a	DET
ejpam-5923	107	21	∈	∈	NOUN
ejpam-5923	108	1	[	[	X
ejpam-5923	108	2	0	0	NUM
ejpam-5923	108	3	,	,	PUNCT
ejpam-5923	108	4	0.5	0.5	NUM
ejpam-5923	108	5	]	]	PUNCT
ejpam-5923	108	6	[	[	PUNCT
ejpam-5923	108	7	−	−	X
ejpam-5923	108	8	(	(	PUNCT
ejpam-5923	108	9	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	108	10	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	108	11	,	,	PUNCT
ejpam-5923	108	12	1	1	NUM
ejpam-5923	108	13	]	]	PUNCT
ejpam-5923	108	14	,	,	PUNCT
ejpam-5923	108	15	if	if	SCONJ
ejpam-5923	108	16	a	a	DET
ejpam-5923	108	17	∈	∈	NOUN
ejpam-5923	108	18	[	[	X
ejpam-5923	108	19	0.5	0.5	NUM
ejpam-5923	108	20	,	,	PUNCT
ejpam-5923	108	21	1	1	NUM
ejpam-5923	108	22	]	]	PUNCT
ejpam-5923	108	23	.	.	PUNCT
ejpam-5923	109	1	proof	proof	NOUN
ejpam-5923	109	2	.	.	PUNCT
ejpam-5923	110	1	let	let	VERB
ejpam-5923	110	2	t	t	NOUN
ejpam-5923	110	3	be	be	AUX
ejpam-5923	110	4	a	a	DET
ejpam-5923	110	5	random	random	ADJ
ejpam-5923	110	6	variable	variable	NOUN
ejpam-5923	110	7	that	that	PRON
ejpam-5923	110	8	follows	follow	VERB
ejpam-5923	110	9	a	a	DET
ejpam-5923	110	10	gesu	gesu	NOUN
ejpam-5923	110	11	distribution	distribution	NOUN
ejpam-5923	110	12	with	with	ADP
ejpam-5923	110	13	parameters	parameter	NOUN
ejpam-5923	110	14	a	a	DET
ejpam-5923	110	15	∈	∈	NOUN
ejpam-5923	111	1	[	[	X
ejpam-5923	111	2	0	0	NUM
ejpam-5923	111	3	,	,	PUNCT
ejpam-5923	111	4	1	1	NUM
ejpam-5923	111	5	]	]	PUNCT
ejpam-5923	111	6	and	and	CCONJ
ejpam-5923	111	7	λ	λ	PART
ejpam-5923	111	8	∈	∈	PROPN
ejpam-5923	111	9			X
ejpam-5923	111	10	[	[	PUNCT
ejpam-5923	111	11	−	−	X
ejpam-5923	111	12	(	(	PUNCT
ejpam-5923	111	13	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	111	14	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	111	15	,	,	PUNCT
ejpam-5923	111	16	1	1	NUM
ejpam-5923	111	17	]	]	PUNCT
ejpam-5923	111	18	,	,	PUNCT
ejpam-5923	112	1	if	if	SCONJ
ejpam-5923	112	2	a	a	DET
ejpam-5923	112	3	∈	∈	NOUN
ejpam-5923	113	1	[	[	X
ejpam-5923	113	2	0	0	NUM
ejpam-5923	113	3	,	,	PUNCT
ejpam-5923	113	4	0.5	0.5	NUM
ejpam-5923	113	5	]	]	PUNCT
ejpam-5923	113	6	[	[	PUNCT
ejpam-5923	113	7	−	−	X
ejpam-5923	113	8	(	(	PUNCT
ejpam-5923	113	9	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	113	10	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	113	11	,	,	PUNCT
ejpam-5923	113	12	1	1	NUM
ejpam-5923	113	13	]	]	PUNCT
ejpam-5923	113	14	,	,	PUNCT
ejpam-5923	113	15	if	if	SCONJ
ejpam-5923	113	16	a	a	DET
ejpam-5923	113	17	∈	∈	NOUN
ejpam-5923	113	18	[	[	X
ejpam-5923	113	19	0.5	0.5	NUM
ejpam-5923	113	20	,	,	PUNCT
ejpam-5923	113	21	1	1	NUM
ejpam-5923	113	22	]	]	PUNCT
ejpam-5923	113	23	.	.	PUNCT
ejpam-5923	114	1	the	the	DET
ejpam-5923	114	2	cumulative	cumulative	ADJ
ejpam-5923	114	3	distribution	distribution	NOUN
ejpam-5923	114	4	function	function	NOUN
ejpam-5923	114	5	of	of	ADP
ejpam-5923	114	6	t	t	PROPN
ejpam-5923	114	7	is	be	AUX
ejpam-5923	114	8	computed	compute	VERB
ejpam-5923	114	9	as	as	ADP
ejpam-5923	114	10	f	f	PROPN
ejpam-5923	114	11	(	(	PUNCT
ejpam-5923	114	12	t	t	PROPN
ejpam-5923	114	13	)	)	PUNCT
ejpam-5923	114	14	=	=	SYM
ejpam-5923	115	1	∫	∫	PROPN
ejpam-5923	115	2	t	t	PROPN
ejpam-5923	115	3	0	0	NUM
ejpam-5923	115	4	(	(	PUNCT
ejpam-5923	115	5	1−	1−	NUM
ejpam-5923	115	6	λ+	λ+	PUNCT
ejpam-5923	115	7	3λ	3λ	NUM
ejpam-5923	115	8	(	(	PUNCT
ejpam-5923	115	9	1−	1−	NUM
ejpam-5923	115	10	a)3	a)3	ADJ
ejpam-5923	115	11	+	+	NUM
ejpam-5923	115	12	a3	a3	NOUN
ejpam-5923	115	13	(	(	PUNCT
ejpam-5923	115	14	u−	u−	PROPN
ejpam-5923	115	15	a)2	a)2	PROPN
ejpam-5923	115	16	)	)	PUNCT
ejpam-5923	115	17	du	du	PROPN
ejpam-5923	115	18	=(	=(	PROPN
ejpam-5923	115	19	1−	1−	NUM
ejpam-5923	115	20	λ	λ	PROPN
ejpam-5923	115	21	)	)	PUNCT
ejpam-5923	115	22	∫	∫	PROPN
ejpam-5923	116	1	t	t	NOUN
ejpam-5923	116	2	0	0	NUM
ejpam-5923	116	3	du+	du+	NOUN
ejpam-5923	116	4	3λ	3λ	NUM
ejpam-5923	116	5	(	(	PUNCT
ejpam-5923	116	6	1−	1−	NUM
ejpam-5923	116	7	a)3	a)3	ADJ
ejpam-5923	116	8	+	+	CCONJ
ejpam-5923	116	9	(	(	PUNCT
ejpam-5923	116	10	a)3	a)3	ADJ
ejpam-5923	116	11	∫	∫	PROPN
ejpam-5923	116	12	t	t	NOUN
ejpam-5923	116	13	0	0	NUM
ejpam-5923	117	1	(	(	PUNCT
ejpam-5923	117	2	u−	u−	PROPN
ejpam-5923	117	3	a)bdu	a)bdu	PROPN
ejpam-5923	117	4	=(	=(	NOUN
ejpam-5923	117	5	1−	1−	NUM
ejpam-5923	117	6	λ	λ	NOUN
ejpam-5923	117	7	)	)	PUNCT
ejpam-5923	117	8	t+	t+	X
ejpam-5923	118	1	λ	λ	X
ejpam-5923	118	2	[	[	PUNCT
ejpam-5923	118	3	(	(	PUNCT
ejpam-5923	118	4	t−	t−	ADP
ejpam-5923	118	5	a)3	a)3	ADJ
ejpam-5923	118	6	+	+	NUM
ejpam-5923	118	7	a3	a3	NOUN
ejpam-5923	118	8	]	]	PUNCT
ejpam-5923	118	9	(	(	PUNCT
ejpam-5923	118	10	1−	1−	NUM
ejpam-5923	118	11	a)3	a)3	ADJ
ejpam-5923	118	12	+	+	CCONJ
ejpam-5923	118	13	(	(	PUNCT
ejpam-5923	118	14	a)3	a)3	ADJ
ejpam-5923	118	15	.	.	PUNCT
ejpam-5923	119	1	i.	i.	PROPN
ejpam-5923	119	2	a.	a.	PROPN
ejpam-5923	119	3	lakibul	lakibul	PROPN
ejpam-5923	119	4	,	,	PUNCT
ejpam-5923	119	5	d.	d.	PROPN
ejpam-5923	119	6	l.	l.	PROPN
ejpam-5923	119	7	polestico	polestico	PROPN
ejpam-5923	119	8	,	,	PUNCT
ejpam-5923	119	9	a.	a.	PROPN
ejpam-5923	119	10	p.	p.	NOUN
ejpam-5923	119	11	supe	supe	PROPN
ejpam-5923	119	12	/	/	SYM
ejpam-5923	119	13	eur	eur	PROPN
ejpam-5923	119	14	.	.	PUNCT
ejpam-5923	120	1	j.	j.	PROPN
ejpam-5923	120	2	pure	pure	PROPN
ejpam-5923	120	3	appl	appl	PROPN
ejpam-5923	120	4	.	.	PROPN
ejpam-5923	120	5	math	math	PROPN
ejpam-5923	120	6	,	,	PUNCT
ejpam-5923	120	7	18	18	NUM
ejpam-5923	120	8	(	(	PUNCT
ejpam-5923	120	9	2	2	NUM
ejpam-5923	120	10	)	)	PUNCT
ejpam-5923	120	11	(	(	PUNCT
ejpam-5923	120	12	2025	2025	NUM
ejpam-5923	120	13	)	)	PUNCT
ejpam-5923	120	14	,	,	PUNCT
ejpam-5923	120	15	5923	5923	NUM
ejpam-5923	120	16	7	7	NUM
ejpam-5923	120	17	of	of	ADP
ejpam-5923	120	18	21	21	NUM
ejpam-5923	120	19	2.1	2.1	NUM
ejpam-5923	120	20	.	.	PUNCT
ejpam-5923	121	1	special	special	ADJ
ejpam-5923	121	2	cases	case	NOUN
ejpam-5923	121	3	of	of	ADP
ejpam-5923	121	4	the	the	DET
ejpam-5923	121	5	gesu	gesu	PROPN
ejpam-5923	121	6	distribution	distribution	NOUN
ejpam-5923	121	7	here	here	ADV
ejpam-5923	122	1	,	,	PUNCT
ejpam-5923	122	2	we	we	PRON
ejpam-5923	122	3	construct	construct	VERB
ejpam-5923	122	4	some	some	DET
ejpam-5923	122	5	special	special	ADJ
ejpam-5923	122	6	cases	case	NOUN
ejpam-5923	122	7	of	of	ADP
ejpam-5923	122	8	the	the	DET
ejpam-5923	122	9	gesu	gesu	PROPN
ejpam-5923	122	10	distribution	distribution	NOUN
ejpam-5923	122	11	based	base	VERB
ejpam-5923	122	12	on	on	ADP
ejpam-5923	122	13	the	the	DET
ejpam-5923	122	14	values	value	NOUN
ejpam-5923	122	15	of	of	ADP
ejpam-5923	122	16	a	a	PRON
ejpam-5923	122	17	and	and	CCONJ
ejpam-5923	122	18	name	name	VERB
ejpam-5923	122	19	these	these	DET
ejpam-5923	122	20	cases	case	NOUN
ejpam-5923	122	21	in	in	ADP
ejpam-5923	122	22	accordance	accordance	NOUN
ejpam-5923	122	23	with	with	ADP
ejpam-5923	122	24	table	table	NOUN
ejpam-5923	122	25	1	1	NUM
ejpam-5923	122	26	.	.	PUNCT
ejpam-5923	122	27	table	table	NOUN
ejpam-5923	122	28	1	1	NUM
ejpam-5923	122	29	:	:	PUNCT
ejpam-5923	122	30	special	special	ADJ
ejpam-5923	122	31	cases	case	NOUN
ejpam-5923	122	32	of	of	ADP
ejpam-5923	122	33	the	the	DET
ejpam-5923	122	34	generalized	generalize	VERB
ejpam-5923	122	35	extended	extend	VERB
ejpam-5923	122	36	standard	standard	ADJ
ejpam-5923	122	37	u	u	ADJ
ejpam-5923	122	38	-	-	ADJ
ejpam-5923	122	39	quadratic	quadratic	ADJ
ejpam-5923	122	40	distribution	distribution	NOUN
ejpam-5923	122	41	no	no	DET
ejpam-5923	122	42	name	name	NOUN
ejpam-5923	122	43	a	a	DET
ejpam-5923	122	44	support	support	NOUN
ejpam-5923	122	45	of	of	ADP
ejpam-5923	122	46	λ	λ	PROPN
ejpam-5923	122	47	0	0	NUM
ejpam-5923	122	48	special	special	ADJ
ejpam-5923	122	49	esu	esu	NOUN
ejpam-5923	122	50	(	(	PUNCT
ejpam-5923	122	51	spesu	spesu	NOUN
ejpam-5923	122	52	)	)	PUNCT
ejpam-5923	122	53	distribution	distribution	NOUN
ejpam-5923	122	54	0.0	0.0	NUM
ejpam-5923	122	55	λ	λ	NOUN
ejpam-5923	122	56	∈	∈	PROPN
ejpam-5923	123	1	[	[	X
ejpam-5923	123	2	−0.5	−0.5	PROPN
ejpam-5923	123	3	,	,	PUNCT
ejpam-5923	123	4	1	1	NUM
ejpam-5923	123	5	]	]	SYM
ejpam-5923	123	6	1	1	NUM
ejpam-5923	123	7	esu	esu	NOUN
ejpam-5923	123	8	type	type	NOUN
ejpam-5923	123	9	-	-	PUNCT
ejpam-5923	123	10	i	i	PRON
ejpam-5923	123	11	distribution	distribution	NOUN
ejpam-5923	123	12	0.1	0.1	NUM
ejpam-5923	123	13	λ	λ	X
ejpam-5923	123	14	∈	∈	PROPN
ejpam-5923	124	1	[	[	X
ejpam-5923	124	2	−	−	PROPN
ejpam-5923	124	3	73	73	NUM
ejpam-5923	124	4	170	170	NUM
ejpam-5923	124	5	,	,	PUNCT
ejpam-5923	124	6	1	1	NUM
ejpam-5923	124	7	]	]	SYM
ejpam-5923	124	8	2	2	NUM
ejpam-5923	124	9	esu	esu	NOUN
ejpam-5923	124	10	type	type	NOUN
ejpam-5923	124	11	-	-	PUNCT
ejpam-5923	124	12	ii	ii	NOUN
ejpam-5923	124	13	distribution	distribution	NOUN
ejpam-5923	124	14	0.2	0.2	NUM
ejpam-5923	124	15	λ	λ	NOUN
ejpam-5923	124	16	∈	∈	PROPN
ejpam-5923	125	1	[	[	X
ejpam-5923	125	2	−	−	PROPN
ejpam-5923	125	3	52	52	NUM
ejpam-5923	125	4	140	140	NUM
ejpam-5923	125	5	,	,	PUNCT
ejpam-5923	125	6	1	1	NUM
ejpam-5923	125	7	]	]	SYM
ejpam-5923	125	8	3	3	NUM
ejpam-5923	125	9	esu	esu	NOUN
ejpam-5923	125	10	type	type	NOUN
ejpam-5923	125	11	-	-	PUNCT
ejpam-5923	125	12	iii	iii	NOUN
ejpam-5923	125	13	distribution	distribution	NOUN
ejpam-5923	125	14	0.3	0.3	NUM
ejpam-5923	125	15	λ	λ	NOUN
ejpam-5923	125	16	∈	∈	PROPN
ejpam-5923	126	1	[	[	X
ejpam-5923	126	2	−	−	PROPN
ejpam-5923	126	3	37	37	NUM
ejpam-5923	126	4	110	110	NUM
ejpam-5923	126	5	,	,	PUNCT
ejpam-5923	126	6	1	1	X
ejpam-5923	126	7	]	]	SYM
ejpam-5923	126	8	4	4	NUM
ejpam-5923	126	9	esu	esu	NOUN
ejpam-5923	126	10	type	type	NOUN
ejpam-5923	126	11	-	-	PUNCT
ejpam-5923	126	12	iv	iv	NOUN
ejpam-5923	126	13	distribution	distribution	NOUN
ejpam-5923	126	14	0.4	0.4	NUM
ejpam-5923	126	15	λ	λ	SYM
ejpam-5923	126	16	∈	∈	PROPN
ejpam-5923	127	1	[	[	X
ejpam-5923	127	2	−28	−28	PROPN
ejpam-5923	127	3	80	80	NUM
ejpam-5923	127	4	,	,	PUNCT
ejpam-5923	127	5	1	1	NUM
ejpam-5923	127	6	]	]	SYM
ejpam-5923	127	7	5	5	NUM
ejpam-5923	127	8	esu	esu	NOUN
ejpam-5923	127	9	type	type	NOUN
ejpam-5923	127	10	-	-	PUNCT
ejpam-5923	127	11	v	v	NOUN
ejpam-5923	127	12	(	(	PUNCT
ejpam-5923	127	13	esu	esu	NOUN
ejpam-5923	127	14	distribution	distribution	NOUN
ejpam-5923	127	15	)	)	PUNCT
ejpam-5923	127	16	0.5	0.5	NUM
ejpam-5923	127	17	λ	λ	NOUN
ejpam-5923	127	18	∈	∈	PROPN
ejpam-5923	128	1	[	[	X
ejpam-5923	128	2	−0.5	−0.5	PROPN
ejpam-5923	128	3	,	,	PUNCT
ejpam-5923	128	4	1	1	NUM
ejpam-5923	128	5	]	]	SYM
ejpam-5923	128	6	6	6	NUM
ejpam-5923	128	7	esu	esu	NOUN
ejpam-5923	128	8	type	type	NOUN
ejpam-5923	128	9	-	-	PUNCT
ejpam-5923	128	10	vi	vi	NOUN
ejpam-5923	128	11	distribution	distribution	NOUN
ejpam-5923	128	12	0.6	0.6	NUM
ejpam-5923	128	13	λ	λ	X
ejpam-5923	128	14	∈	∈	PROPN
ejpam-5923	129	1	[	[	X
ejpam-5923	129	2	−28	−28	PROPN
ejpam-5923	129	3	80	80	NUM
ejpam-5923	129	4	,	,	PUNCT
ejpam-5923	129	5	1	1	NUM
ejpam-5923	129	6	]	]	SYM
ejpam-5923	129	7	7	7	NUM
ejpam-5923	129	8	esu	esu	NOUN
ejpam-5923	129	9	type	type	NOUN
ejpam-5923	129	10	-	-	PUNCT
ejpam-5923	129	11	vii	vii	NOUN
ejpam-5923	129	12	distribution	distribution	NOUN
ejpam-5923	129	13	0.7	0.7	NUM
ejpam-5923	129	14	λ	λ	NOUN
ejpam-5923	129	15	∈	∈	PROPN
ejpam-5923	130	1	[	[	X
ejpam-5923	130	2	−	−	PROPN
ejpam-5923	130	3	37	37	NUM
ejpam-5923	130	4	110	110	NUM
ejpam-5923	130	5	,	,	PUNCT
ejpam-5923	130	6	1	1	NUM
ejpam-5923	130	7	]	]	SYM
ejpam-5923	130	8	8	8	NUM
ejpam-5923	130	9	esu	esu	NOUN
ejpam-5923	130	10	type	type	NOUN
ejpam-5923	130	11	-	-	PUNCT
ejpam-5923	130	12	viii	viii	NOUN
ejpam-5923	130	13	distribution	distribution	NOUN
ejpam-5923	130	14	0.8	0.8	NUM
ejpam-5923	130	15	λ	λ	NOUN
ejpam-5923	130	16	∈	∈	PROPN
ejpam-5923	131	1	[	[	X
ejpam-5923	131	2	−	−	PROPN
ejpam-5923	131	3	52	52	NUM
ejpam-5923	131	4	140	140	NUM
ejpam-5923	131	5	,	,	PUNCT
ejpam-5923	131	6	1	1	NUM
ejpam-5923	131	7	]	]	SYM
ejpam-5923	131	8	9	9	NUM
ejpam-5923	131	9	esu	esu	NOUN
ejpam-5923	131	10	type	type	NOUN
ejpam-5923	131	11	-	-	PUNCT
ejpam-5923	131	12	ix	ix	ADV
ejpam-5923	131	13	distribution	distribution	NOUN
ejpam-5923	131	14	0.9	0.9	NUM
ejpam-5923	131	15	λ	λ	NOUN
ejpam-5923	131	16	∈	∈	PROPN
ejpam-5923	132	1	[	[	X
ejpam-5923	132	2	−	−	PROPN
ejpam-5923	132	3	73	73	NUM
ejpam-5923	132	4	170	170	NUM
ejpam-5923	132	5	,	,	PUNCT
ejpam-5923	132	6	1	1	NUM
ejpam-5923	132	7	]	]	SYM
ejpam-5923	132	8	10	10	NUM
ejpam-5923	132	9	esu	esu	NOUN
ejpam-5923	132	10	type	type	NOUN
ejpam-5923	132	11	-	-	PUNCT
ejpam-5923	132	12	x	x	NOUN
ejpam-5923	132	13	distribution	distribution	NOUN
ejpam-5923	132	14	1.0	1.0	NUM
ejpam-5923	132	15	λ	λ	NOUN
ejpam-5923	132	16	∈	∈	PROPN
ejpam-5923	133	1	[	[	X
ejpam-5923	133	2	−0.5	−0.5	PROPN
ejpam-5923	133	3	,	,	PUNCT
ejpam-5923	133	4	1	1	NUM
ejpam-5923	133	5	]	]	PUNCT
ejpam-5923	133	6	(	(	PUNCT
ejpam-5923	133	7	a	a	NOUN
ejpam-5923	133	8	)	)	PUNCT
ejpam-5923	133	9	(	(	PUNCT
ejpam-5923	133	10	b	b	X
ejpam-5923	133	11	)	)	PUNCT
ejpam-5923	133	12	figure	figure	NOUN
ejpam-5923	133	13	1	1	NUM
ejpam-5923	133	14	:	:	PUNCT
ejpam-5923	133	15	pdf	pdf	NOUN
ejpam-5923	133	16	plots	plot	NOUN
ejpam-5923	133	17	of	of	ADP
ejpam-5923	133	18	the	the	DET
ejpam-5923	133	19	distributions	distribution	NOUN
ejpam-5923	133	20	:	:	PUNCT
ejpam-5923	133	21	(	(	PUNCT
ejpam-5923	133	22	a	a	X
ejpam-5923	133	23	)	)	PUNCT
ejpam-5923	133	24	gesu	gesu	NOUN
ejpam-5923	133	25	distribution	distribution	NOUN
ejpam-5923	133	26	for	for	ADP
ejpam-5923	133	27	λ	λ	NOUN
ejpam-5923	133	28	=	=	SYM
ejpam-5923	133	29	1	1	NUM
ejpam-5923	133	30	and	and	CCONJ
ejpam-5923	133	31	varying	vary	VERB
ejpam-5923	133	32	values	value	NOUN
ejpam-5923	133	33	of	of	ADP
ejpam-5923	133	34	a	a	PRON
ejpam-5923	133	35	;	;	PUNCT
ejpam-5923	133	36	and	and	CCONJ
ejpam-5923	133	37	(	(	PUNCT
ejpam-5923	133	38	b	b	X
ejpam-5923	133	39	)	)	PUNCT
ejpam-5923	133	40	spesu	spesu	ADJ
ejpam-5923	133	41	distribution	distribution	NOUN
ejpam-5923	133	42	for	for	ADP
ejpam-5923	133	43	varying	vary	VERB
ejpam-5923	133	44	values	value	NOUN
ejpam-5923	133	45	of	of	ADP
ejpam-5923	133	46	λ	λ	PROPN
ejpam-5923	133	47	.	.	PUNCT
ejpam-5923	133	48	figure	figure	PROPN
ejpam-5923	133	49	1a	1a	PROPN
ejpam-5923	133	50	shows	show	VERB
ejpam-5923	133	51	the	the	DET
ejpam-5923	133	52	pdfs	pdfs	NOUN
ejpam-5923	133	53	of	of	ADP
ejpam-5923	133	54	gesu	gesu	PROPN
ejpam-5923	133	55	distribution	distribution	NOUN
ejpam-5923	133	56	types	type	NOUN
ejpam-5923	133	57	for	for	ADP
ejpam-5923	133	58	a	a	DET
ejpam-5923	133	59	fixed	fix	VERB
ejpam-5923	133	60	value	value	NOUN
ejpam-5923	133	61	of	of	ADP
ejpam-5923	133	62	λ	λ	PROPN
ejpam-5923	133	63	and	and	CCONJ
ejpam-5923	133	64	varying	vary	VERB
ejpam-5923	133	65	a.	a.	NOUN
ejpam-5923	133	66	it	it	PRON
ejpam-5923	133	67	is	be	AUX
ejpam-5923	133	68	important	important	ADJ
ejpam-5923	133	69	to	to	PART
ejpam-5923	133	70	note	note	VERB
ejpam-5923	133	71	that	that	SCONJ
ejpam-5923	133	72	for	for	ADP
ejpam-5923	133	73	a	a	DET
ejpam-5923	133	74	=	=	SYM
ejpam-5923	133	75	0.5	0.5	NUM
ejpam-5923	133	76	and	and	CCONJ
ejpam-5923	133	77	λ	λ	X
ejpam-5923	133	78	=	=	NOUN
ejpam-5923	133	79	1	1	NUM
ejpam-5923	133	80	,	,	PUNCT
ejpam-5923	133	81	the	the	DET
ejpam-5923	133	82	behavior	behavior	NOUN
ejpam-5923	133	83	of	of	ADP
ejpam-5923	133	84	the	the	DET
ejpam-5923	133	85	distribution	distribution	NOUN
ejpam-5923	133	86	follows	follow	VERB
ejpam-5923	133	87	a	a	DET
ejpam-5923	133	88	symmetric	symmetric	ADJ
ejpam-5923	133	89	bathtub	bathtub	NOUN
ejpam-5923	133	90	shape	shape	NOUN
ejpam-5923	133	91	where	where	SCONJ
ejpam-5923	133	92	the	the	DET
ejpam-5923	133	93	minimum	minimum	ADJ
ejpam-5923	133	94	point	point	NOUN
ejpam-5923	133	95	is	be	AUX
ejpam-5923	133	96	equal	equal	ADJ
ejpam-5923	133	97	to	to	ADP
ejpam-5923	133	98	0	0	NUM
ejpam-5923	133	99	.	.	PUNCT
ejpam-5923	134	1	as	as	SCONJ
ejpam-5923	134	2	we	we	PRON
ejpam-5923	134	3	change	change	VERB
ejpam-5923	134	4	the	the	DET
ejpam-5923	134	5	values	value	NOUN
ejpam-5923	134	6	of	of	ADP
ejpam-5923	134	7	a	a	PRON
ejpam-5923	134	8	from	from	ADP
ejpam-5923	134	9	0	0	NUM
ejpam-5923	134	10	to	to	ADP
ejpam-5923	134	11	1	1	NUM
ejpam-5923	134	12	,	,	PUNCT
ejpam-5923	134	13	we	we	PRON
ejpam-5923	134	14	observe	observe	VERB
ejpam-5923	134	15	the	the	DET
ejpam-5923	134	16	following	follow	VERB
ejpam-5923	134	17	behaviors	behavior	NOUN
ejpam-5923	134	18	:	:	PUNCT
ejpam-5923	134	19	(	(	PUNCT
ejpam-5923	134	20	i	i	NOUN
ejpam-5923	134	21	)	)	PUNCT
ejpam-5923	134	22	increasing	increase	VERB
ejpam-5923	134	23	for	for	ADP
ejpam-5923	134	24	a	a	DET
ejpam-5923	134	25	=	=	SYM
ejpam-5923	134	26	0	0	NUM
ejpam-5923	134	27	;	;	PUNCT
ejpam-5923	134	28	(	(	PUNCT
ejpam-5923	134	29	ii	ii	NOUN
ejpam-5923	134	30	)	)	PUNCT
ejpam-5923	134	31	asymmetric	asymmetric	NOUN
ejpam-5923	134	32	to	to	ADP
ejpam-5923	134	33	the	the	DET
ejpam-5923	134	34	right	right	NOUN
ejpam-5923	134	35	for	for	ADP
ejpam-5923	134	36	a	a	DET
ejpam-5923	134	37	∈	∈	PROPN
ejpam-5923	134	38	(	(	PUNCT
ejpam-5923	134	39	0	0	NUM
ejpam-5923	134	40	,	,	PUNCT
ejpam-5923	134	41	0.5	0.5	NUM
ejpam-5923	134	42	)	)	PUNCT
ejpam-5923	134	43	;	;	PUNCT
ejpam-5923	134	44	(	(	PUNCT
ejpam-5923	134	45	iii	iii	X
ejpam-5923	134	46	)	)	PUNCT
ejpam-5923	134	47	asymmetric	asymmetric	NOUN
ejpam-5923	134	48	to	to	ADP
ejpam-5923	134	49	the	the	DET
ejpam-5923	134	50	left	left	NOUN
ejpam-5923	134	51	for	for	ADP
ejpam-5923	134	52	a	a	DET
ejpam-5923	134	53	∈	∈	NOUN
ejpam-5923	134	54	(	(	PUNCT
ejpam-5923	134	55	0.5	0.5	NUM
ejpam-5923	134	56	,	,	PUNCT
ejpam-5923	134	57	1	1	NUM
ejpam-5923	134	58	)	)	PUNCT
ejpam-5923	134	59	;	;	PUNCT
ejpam-5923	134	60	and	and	CCONJ
ejpam-5923	134	61	(	(	PUNCT
ejpam-5923	134	62	iv	iv	X
ejpam-5923	134	63	)	)	PUNCT
ejpam-5923	134	64	decreasing	decrease	VERB
ejpam-5923	134	65	for	for	ADP
ejpam-5923	134	66	a	a	PRON
ejpam-5923	134	67	=	=	SYM
ejpam-5923	134	68	1	1	X
ejpam-5923	134	69	.	.	PUNCT
ejpam-5923	134	70	figure	figure	NOUN
ejpam-5923	134	71	1b	1b	PROPN
ejpam-5923	134	72	shows	show	VERB
ejpam-5923	134	73	the	the	DET
ejpam-5923	134	74	different	different	ADJ
ejpam-5923	134	75	shapes	shape	NOUN
ejpam-5923	134	76	of	of	ADP
ejpam-5923	134	77	the	the	DET
ejpam-5923	134	78	pdf	pdf	NOUN
ejpam-5923	134	79	of	of	ADP
ejpam-5923	134	80	the	the	DET
ejpam-5923	134	81	special	special	ADJ
ejpam-5923	134	82	esu	esu	NOUN
ejpam-5923	134	83	distribution	distribution	NOUN
ejpam-5923	134	84	for	for	ADP
ejpam-5923	134	85	varying	vary	VERB
ejpam-5923	134	86	values	value	NOUN
ejpam-5923	134	87	of	of	ADP
ejpam-5923	134	88	λ	λ	PROPN
ejpam-5923	134	89	.	.	PUNCT
ejpam-5923	135	1	as	as	SCONJ
ejpam-5923	135	2	we	we	PRON
ejpam-5923	135	3	increase	increase	VERB
ejpam-5923	135	4	the	the	DET
ejpam-5923	135	5	values	value	NOUN
ejpam-5923	135	6	of	of	ADP
ejpam-5923	135	7	λ	λ	PROPN
ejpam-5923	135	8	from	from	ADP
ejpam-5923	135	9	−0.5	−0.5	NUM
ejpam-5923	135	10	to	to	PART
ejpam-5923	135	11	1	1	NUM
ejpam-5923	135	12	,	,	PUNCT
ejpam-5923	135	13	it	it	PRON
ejpam-5923	135	14	is	be	AUX
ejpam-5923	135	15	observed	observe	VERB
ejpam-5923	135	16	that	that	SCONJ
ejpam-5923	135	17	the	the	DET
ejpam-5923	135	18	behavior	behavior	NOUN
ejpam-5923	135	19	of	of	ADP
ejpam-5923	135	20	the	the	DET
ejpam-5923	135	21	pdf	pdf	NOUN
ejpam-5923	135	22	forms	form	VERB
ejpam-5923	135	23	a	a	DET
ejpam-5923	135	24	decreasing	decrease	VERB
ejpam-5923	135	25	behavior	behavior	NOUN
ejpam-5923	135	26	for	for	ADP
ejpam-5923	135	27	λ	λ	PROPN
ejpam-5923	135	28	∈	∈	PROPN
ejpam-5923	136	1	[	[	X
ejpam-5923	136	2	−0.5	−0.5	PROPN
ejpam-5923	136	3	,	,	PUNCT
ejpam-5923	136	4	0	0	NUM
ejpam-5923	136	5	)	)	PUNCT
ejpam-5923	136	6	,	,	PUNCT
ejpam-5923	136	7	constant	constant	ADJ
ejpam-5923	136	8	for	for	ADP
ejpam-5923	136	9	λ	λ	X
ejpam-5923	136	10	=	=	SYM
ejpam-5923	136	11	0	0	PUNCT
ejpam-5923	136	12	and	and	CCONJ
ejpam-5923	136	13	increasing	increase	VERB
ejpam-5923	136	14	for	for	ADP
ejpam-5923	136	15	λ	λ	PROPN
ejpam-5923	136	16	∈	∈	PROPN
ejpam-5923	136	17	(	(	PUNCT
ejpam-5923	136	18	0	0	NUM
ejpam-5923	136	19	,	,	PUNCT
ejpam-5923	136	20	1	1	NUM
ejpam-5923	136	21	]	]	PUNCT
ejpam-5923	136	22	.	.	PUNCT
ejpam-5923	137	1	i.	i.	PROPN
ejpam-5923	137	2	a.	a.	PROPN
ejpam-5923	137	3	lakibul	lakibul	PROPN
ejpam-5923	137	4	,	,	PUNCT
ejpam-5923	137	5	d.	d.	PROPN
ejpam-5923	137	6	l.	l.	PROPN
ejpam-5923	137	7	polestico	polestico	PROPN
ejpam-5923	137	8	,	,	PUNCT
ejpam-5923	137	9	a.	a.	PROPN
ejpam-5923	137	10	p.	p.	NOUN
ejpam-5923	137	11	supe	supe	PROPN
ejpam-5923	137	12	/	/	SYM
ejpam-5923	137	13	eur	eur	PROPN
ejpam-5923	137	14	.	.	PUNCT
ejpam-5923	138	1	j.	j.	PROPN
ejpam-5923	138	2	pure	pure	PROPN
ejpam-5923	138	3	appl	appl	PROPN
ejpam-5923	138	4	.	.	PROPN
ejpam-5923	138	5	math	math	PROPN
ejpam-5923	138	6	,	,	PUNCT
ejpam-5923	138	7	18	18	NUM
ejpam-5923	138	8	(	(	PUNCT
ejpam-5923	138	9	2	2	NUM
ejpam-5923	138	10	)	)	PUNCT
ejpam-5923	138	11	(	(	PUNCT
ejpam-5923	138	12	2025	2025	NUM
ejpam-5923	138	13	)	)	PUNCT
ejpam-5923	138	14	,	,	PUNCT
ejpam-5923	138	15	5923	5923	NUM
ejpam-5923	138	16	8	8	NUM
ejpam-5923	138	17	of	of	ADP
ejpam-5923	138	18	21	21	NUM
ejpam-5923	138	19	(	(	PUNCT
ejpam-5923	138	20	a	a	NOUN
ejpam-5923	138	21	)	)	PUNCT
ejpam-5923	138	22	(	(	PUNCT
ejpam-5923	138	23	b	b	X
ejpam-5923	138	24	)	)	PUNCT
ejpam-5923	138	25	figure	figure	NOUN
ejpam-5923	138	26	2	2	NUM
ejpam-5923	138	27	:	:	PUNCT
ejpam-5923	138	28	pdf	pdf	NOUN
ejpam-5923	138	29	plots	plot	NOUN
ejpam-5923	138	30	of	of	ADP
ejpam-5923	138	31	the	the	DET
ejpam-5923	138	32	distributions	distribution	NOUN
ejpam-5923	138	33	for	for	ADP
ejpam-5923	138	34	varying	vary	VERB
ejpam-5923	138	35	values	value	NOUN
ejpam-5923	138	36	of	of	ADP
ejpam-5923	138	37	λ	λ	NOUN
ejpam-5923	138	38	:	:	PUNCT
ejpam-5923	138	39	(	(	PUNCT
ejpam-5923	138	40	a	a	X
ejpam-5923	138	41	)	)	PUNCT
ejpam-5923	138	42	esu	esu	NOUN
ejpam-5923	138	43	type	type	NOUN
ejpam-5923	138	44	-	-	PUNCT
ejpam-5923	138	45	i	i	PRON
ejpam-5923	138	46	distribution	distribution	NOUN
ejpam-5923	138	47	;	;	PUNCT
ejpam-5923	138	48	and	and	CCONJ
ejpam-5923	138	49	(	(	PUNCT
ejpam-5923	138	50	b	b	X
ejpam-5923	138	51	)	)	PUNCT
ejpam-5923	138	52	esu	esu	NOUN
ejpam-5923	138	53	type	type	NOUN
ejpam-5923	138	54	-	-	PUNCT
ejpam-5923	138	55	ii	ii	NOUN
ejpam-5923	138	56	distribution	distribution	NOUN
ejpam-5923	138	57	.	.	PUNCT
ejpam-5923	139	1	(	(	PUNCT
ejpam-5923	139	2	a	a	X
ejpam-5923	139	3	)	)	PUNCT
ejpam-5923	139	4	(	(	PUNCT
ejpam-5923	139	5	b	b	X
ejpam-5923	139	6	)	)	PUNCT
ejpam-5923	139	7	figure	figure	NOUN
ejpam-5923	139	8	3	3	NUM
ejpam-5923	139	9	:	:	PUNCT
ejpam-5923	139	10	pdf	pdf	NOUN
ejpam-5923	139	11	plots	plot	NOUN
ejpam-5923	139	12	of	of	ADP
ejpam-5923	139	13	the	the	DET
ejpam-5923	139	14	distributions	distribution	NOUN
ejpam-5923	139	15	for	for	ADP
ejpam-5923	139	16	varying	vary	VERB
ejpam-5923	139	17	values	value	NOUN
ejpam-5923	139	18	of	of	ADP
ejpam-5923	139	19	λ	λ	NOUN
ejpam-5923	139	20	:	:	PUNCT
ejpam-5923	139	21	(	(	PUNCT
ejpam-5923	139	22	a	a	X
ejpam-5923	139	23	)	)	PUNCT
ejpam-5923	139	24	esu	esu	NOUN
ejpam-5923	139	25	type	type	NOUN
ejpam-5923	139	26	-	-	PUNCT
ejpam-5923	139	27	iii	iii	NOUN
ejpam-5923	139	28	distribution	distribution	NOUN
ejpam-5923	139	29	;	;	PUNCT
ejpam-5923	139	30	and	and	CCONJ
ejpam-5923	139	31	(	(	PUNCT
ejpam-5923	139	32	b	b	X
ejpam-5923	139	33	)	)	PUNCT
ejpam-5923	139	34	esu	esu	NOUN
ejpam-5923	139	35	type	type	NOUN
ejpam-5923	139	36	-	-	PUNCT
ejpam-5923	139	37	iv	iv	NOUN
ejpam-5923	139	38	distribution	distribution	NOUN
ejpam-5923	139	39	.	.	PUNCT
ejpam-5923	140	1	figures	figure	NOUN
ejpam-5923	140	2	2a-3b	2a-3b	NUM
ejpam-5923	140	3	show	show	VERB
ejpam-5923	140	4	the	the	DET
ejpam-5923	140	5	behavior	behavior	NOUN
ejpam-5923	140	6	of	of	ADP
ejpam-5923	140	7	the	the	DET
ejpam-5923	140	8	pdf	pdf	NOUN
ejpam-5923	140	9	of	of	ADP
ejpam-5923	140	10	the	the	DET
ejpam-5923	140	11	esu	esu	NOUN
ejpam-5923	140	12	type	type	NOUN
ejpam-5923	140	13	-	-	PUNCT
ejpam-5923	140	14	i	i	PROPN
ejpam-5923	140	15	,	,	PUNCT
ejpam-5923	140	16	esu	esu	NOUN
ejpam-5923	140	17	type	type	PROPN
ejpam-5923	140	18	-	-	PUNCT
ejpam-5923	140	19	ii	ii	NOUN
ejpam-5923	140	20	,	,	PUNCT
ejpam-5923	140	21	esu	esu	NOUN
ejpam-5923	140	22	type	type	NOUN
ejpam-5923	140	23	-	-	PUNCT
ejpam-5923	140	24	iii	iii	NOUN
ejpam-5923	140	25	and	and	CCONJ
ejpam-5923	140	26	esu	esu	NOUN
ejpam-5923	140	27	type	type	NOUN
ejpam-5923	140	28	-	-	PUNCT
ejpam-5923	140	29	iv	iv	NUM
ejpam-5923	140	30	distributions	distribution	NOUN
ejpam-5923	140	31	,	,	PUNCT
ejpam-5923	140	32	respectively	respectively	ADV
ejpam-5923	140	33	.	.	PUNCT
ejpam-5923	141	1	it	it	PRON
ejpam-5923	141	2	can	can	AUX
ejpam-5923	141	3	be	be	AUX
ejpam-5923	141	4	seen	see	VERB
ejpam-5923	141	5	from	from	ADP
ejpam-5923	141	6	the	the	DET
ejpam-5923	141	7	said	say	VERB
ejpam-5923	141	8	figures	figure	NOUN
ejpam-5923	141	9	that	that	SCONJ
ejpam-5923	141	10	for	for	ADP
ejpam-5923	141	11	varying	vary	VERB
ejpam-5923	141	12	values	value	NOUN
ejpam-5923	141	13	of	of	ADP
ejpam-5923	141	14	λ	λ	PROPN
ejpam-5923	141	15	,	,	PUNCT
ejpam-5923	141	16	the	the	DET
ejpam-5923	141	17	behavior	behavior	NOUN
ejpam-5923	141	18	of	of	ADP
ejpam-5923	141	19	each	each	PRON
ejpam-5923	141	20	of	of	ADP
ejpam-5923	141	21	the	the	DET
ejpam-5923	141	22	said	say	VERB
ejpam-5923	141	23	distributions	distribution	NOUN
ejpam-5923	141	24	follows	follow	VERB
ejpam-5923	141	25	some	some	DET
ejpam-5923	141	26	decreasing	decrease	VERB
ejpam-5923	141	27	function	function	NOUN
ejpam-5923	141	28	for	for	ADP
ejpam-5923	141	29	λ	λ	PROPN
ejpam-5923	141	30	∈	∈	PROPN
ejpam-5923	141	31	(	(	PUNCT
ejpam-5923	141	32	−0.5	−0.5	PROPN
ejpam-5923	141	33	,	,	PUNCT
ejpam-5923	141	34	0	0	NUM
ejpam-5923	141	35	)	)	PUNCT
ejpam-5923	141	36	,	,	PUNCT
ejpam-5923	141	37	constant	constant	ADJ
ejpam-5923	141	38	for	for	ADP
ejpam-5923	141	39	λ	λ	PROPN
ejpam-5923	141	40	=	=	SYM
ejpam-5923	141	41	0	0	NUM
ejpam-5923	141	42	,	,	PUNCT
ejpam-5923	141	43	and	and	CCONJ
ejpam-5923	141	44	asymmetric	asymmetric	ADJ
ejpam-5923	141	45	to	to	ADP
ejpam-5923	141	46	the	the	DET
ejpam-5923	141	47	right	right	ADJ
ejpam-5923	141	48	bathtub	bathtub	NOUN
ejpam-5923	141	49	for	for	ADP
ejpam-5923	141	50	λ	λ	PROPN
ejpam-5923	141	51	∈	∈	PROPN
ejpam-5923	141	52	(	(	PUNCT
ejpam-5923	141	53	0	0	NUM
ejpam-5923	141	54	,	,	PUNCT
ejpam-5923	141	55	1	1	NUM
ejpam-5923	141	56	]	]	PUNCT
ejpam-5923	141	57	.	.	PUNCT
ejpam-5923	142	1	in	in	ADP
ejpam-5923	142	2	addition	addition	NOUN
ejpam-5923	142	3	,	,	PUNCT
ejpam-5923	142	4	it	it	PRON
ejpam-5923	142	5	is	be	AUX
ejpam-5923	142	6	also	also	ADV
ejpam-5923	142	7	observed	observe	VERB
ejpam-5923	142	8	that	that	SCONJ
ejpam-5923	142	9	the	the	DET
ejpam-5923	142	10	parameter	parameter	NOUN
ejpam-5923	142	11	a	a	PRON
ejpam-5923	142	12	is	be	AUX
ejpam-5923	142	13	the	the	DET
ejpam-5923	142	14	minimum	minimum	NOUN
ejpam-5923	142	15	of	of	ADP
ejpam-5923	142	16	the	the	DET
ejpam-5923	142	17	distribution	distribution	NOUN
ejpam-5923	142	18	for	for	ADP
ejpam-5923	142	19	bathtub	bathtub	ADJ
ejpam-5923	142	20	shapes	shape	NOUN
ejpam-5923	142	21	and	and	CCONJ
ejpam-5923	142	22	it	it	PRON
ejpam-5923	142	23	is	be	AUX
ejpam-5923	142	24	the	the	DET
ejpam-5923	142	25	maximum	maximum	NOUN
ejpam-5923	142	26	for	for	ADP
ejpam-5923	142	27	the	the	DET
ejpam-5923	142	28	inverted	inverted	ADJ
ejpam-5923	142	29	bathtub	bathtub	NOUN
ejpam-5923	142	30	shapes	shape	NOUN
ejpam-5923	142	31	.	.	PUNCT
ejpam-5923	143	1	i.	i.	PROPN
ejpam-5923	143	2	a.	a.	PROPN
ejpam-5923	143	3	lakibul	lakibul	PROPN
ejpam-5923	143	4	,	,	PUNCT
ejpam-5923	143	5	d.	d.	PROPN
ejpam-5923	143	6	l.	l.	PROPN
ejpam-5923	143	7	polestico	polestico	PROPN
ejpam-5923	143	8	,	,	PUNCT
ejpam-5923	143	9	a.	a.	PROPN
ejpam-5923	143	10	p.	p.	NOUN
ejpam-5923	143	11	supe	supe	PROPN
ejpam-5923	143	12	/	/	SYM
ejpam-5923	143	13	eur	eur	PROPN
ejpam-5923	143	14	.	.	PUNCT
ejpam-5923	144	1	j.	j.	PROPN
ejpam-5923	144	2	pure	pure	PROPN
ejpam-5923	144	3	appl	appl	PROPN
ejpam-5923	144	4	.	.	PROPN
ejpam-5923	144	5	math	math	PROPN
ejpam-5923	144	6	,	,	PUNCT
ejpam-5923	144	7	18	18	NUM
ejpam-5923	144	8	(	(	PUNCT
ejpam-5923	144	9	2	2	NUM
ejpam-5923	144	10	)	)	PUNCT
ejpam-5923	144	11	(	(	PUNCT
ejpam-5923	144	12	2025	2025	NUM
ejpam-5923	144	13	)	)	PUNCT
ejpam-5923	144	14	,	,	PUNCT
ejpam-5923	144	15	5923	5923	NUM
ejpam-5923	144	16	9	9	NUM
ejpam-5923	144	17	of	of	ADP
ejpam-5923	144	18	21	21	NUM
ejpam-5923	144	19	(	(	PUNCT
ejpam-5923	144	20	a	a	NOUN
ejpam-5923	144	21	)	)	PUNCT
ejpam-5923	144	22	(	(	PUNCT
ejpam-5923	144	23	b	b	X
ejpam-5923	144	24	)	)	PUNCT
ejpam-5923	144	25	figure	figure	NOUN
ejpam-5923	144	26	4	4	NUM
ejpam-5923	144	27	:	:	PUNCT
ejpam-5923	144	28	pdf	pdf	NOUN
ejpam-5923	144	29	plots	plot	NOUN
ejpam-5923	144	30	of	of	ADP
ejpam-5923	144	31	the	the	DET
ejpam-5923	144	32	distributions	distribution	NOUN
ejpam-5923	144	33	for	for	ADP
ejpam-5923	144	34	varying	vary	VERB
ejpam-5923	144	35	values	value	NOUN
ejpam-5923	144	36	of	of	ADP
ejpam-5923	144	37	λ	λ	NOUN
ejpam-5923	144	38	:	:	PUNCT
ejpam-5923	144	39	(	(	PUNCT
ejpam-5923	144	40	a	a	X
ejpam-5923	144	41	)	)	PUNCT
ejpam-5923	144	42	esu	esu	NOUN
ejpam-5923	144	43	type	type	NOUN
ejpam-5923	144	44	-	-	PUNCT
ejpam-5923	144	45	vi	vi	NOUN
ejpam-5923	144	46	distribution	distribution	NOUN
ejpam-5923	144	47	;	;	PUNCT
ejpam-5923	144	48	and	and	CCONJ
ejpam-5923	144	49	(	(	PUNCT
ejpam-5923	144	50	b	b	X
ejpam-5923	144	51	)	)	PUNCT
ejpam-5923	144	52	esu	esu	NOUN
ejpam-5923	144	53	type	type	NOUN
ejpam-5923	144	54	-	-	PUNCT
ejpam-5923	144	55	vii	vii	NOUN
ejpam-5923	144	56	distribution	distribution	NOUN
ejpam-5923	144	57	.	.	PUNCT
ejpam-5923	145	1	(	(	PUNCT
ejpam-5923	145	2	a	a	X
ejpam-5923	145	3	)	)	PUNCT
ejpam-5923	145	4	(	(	PUNCT
ejpam-5923	145	5	b	b	X
ejpam-5923	145	6	)	)	PUNCT
ejpam-5923	145	7	figure	figure	NOUN
ejpam-5923	145	8	5	5	NUM
ejpam-5923	145	9	:	:	PUNCT
ejpam-5923	145	10	pdf	pdf	NOUN
ejpam-5923	145	11	plots	plot	NOUN
ejpam-5923	145	12	of	of	ADP
ejpam-5923	145	13	the	the	DET
ejpam-5923	145	14	distributions	distribution	NOUN
ejpam-5923	145	15	for	for	ADP
ejpam-5923	145	16	varying	vary	VERB
ejpam-5923	145	17	values	value	NOUN
ejpam-5923	145	18	of	of	ADP
ejpam-5923	145	19	λ	λ	NOUN
ejpam-5923	145	20	:	:	PUNCT
ejpam-5923	145	21	(	(	PUNCT
ejpam-5923	145	22	a	a	X
ejpam-5923	145	23	)	)	PUNCT
ejpam-5923	145	24	esu	esu	NOUN
ejpam-5923	145	25	type	type	NOUN
ejpam-5923	145	26	viii	viii	ADJ
ejpam-5923	145	27	distribution	distribution	NOUN
ejpam-5923	145	28	;	;	PUNCT
ejpam-5923	145	29	and	and	CCONJ
ejpam-5923	145	30	(	(	PUNCT
ejpam-5923	145	31	b	b	X
ejpam-5923	145	32	)	)	PUNCT
ejpam-5923	145	33	esu	esu	NOUN
ejpam-5923	145	34	type	type	NOUN
ejpam-5923	145	35	-	-	PUNCT
ejpam-5923	145	36	ix	ix	ADP
ejpam-5923	145	37	distribution	distribution	NOUN
ejpam-5923	145	38	.	.	PUNCT
ejpam-5923	146	1	figures	figure	NOUN
ejpam-5923	146	2	4a-5b	4a-5b	NOUN
ejpam-5923	146	3	show	show	VERB
ejpam-5923	146	4	almost	almost	ADV
ejpam-5923	146	5	same	same	ADJ
ejpam-5923	146	6	observations	observation	NOUN
ejpam-5923	146	7	with	with	ADP
ejpam-5923	146	8	the	the	DET
ejpam-5923	146	9	previous	previous	ADJ
ejpam-5923	146	10	figures	figure	NOUN
ejpam-5923	146	11	.	.	PUNCT
ejpam-5923	147	1	the	the	DET
ejpam-5923	147	2	difference	difference	NOUN
ejpam-5923	147	3	is	be	AUX
ejpam-5923	147	4	asymmetric	asymmetric	ADJ
ejpam-5923	147	5	to	to	ADP
ejpam-5923	147	6	the	the	DET
ejpam-5923	147	7	left	left	ADJ
ejpam-5923	147	8	bathtub	bathtub	NOUN
ejpam-5923	147	9	shapes	shape	NOUN
ejpam-5923	147	10	are	be	AUX
ejpam-5923	147	11	produced	produce	VERB
ejpam-5923	147	12	in	in	ADP
ejpam-5923	147	13	this	this	DET
ejpam-5923	147	14	case	case	NOUN
ejpam-5923	147	15	.	.	PUNCT
ejpam-5923	148	1	figure	figure	VERB
ejpam-5923	148	2	6	6	NUM
ejpam-5923	148	3	:	:	PUNCT
ejpam-5923	148	4	pdf	pdf	NOUN
ejpam-5923	148	5	plots	plot	NOUN
ejpam-5923	148	6	of	of	ADP
ejpam-5923	148	7	the	the	DET
ejpam-5923	148	8	esu	esu	NOUN
ejpam-5923	148	9	type	type	NOUN
ejpam-5923	148	10	-	-	PUNCT
ejpam-5923	148	11	x	x	NOUN
ejpam-5923	148	12	distribution	distribution	NOUN
ejpam-5923	148	13	for	for	ADP
ejpam-5923	148	14	varying	vary	VERB
ejpam-5923	148	15	values	value	NOUN
ejpam-5923	148	16	of	of	ADP
ejpam-5923	148	17	λ	λ	PROPN
ejpam-5923	148	18	.	.	PUNCT
ejpam-5923	148	19	i.	i.	PROPN
ejpam-5923	148	20	a.	a.	PROPN
ejpam-5923	148	21	lakibul	lakibul	PROPN
ejpam-5923	148	22	,	,	PUNCT
ejpam-5923	148	23	d.	d.	PROPN
ejpam-5923	148	24	l.	l.	PROPN
ejpam-5923	148	25	polestico	polestico	PROPN
ejpam-5923	148	26	,	,	PUNCT
ejpam-5923	148	27	a.	a.	PROPN
ejpam-5923	148	28	p.	p.	NOUN
ejpam-5923	148	29	supe	supe	PROPN
ejpam-5923	148	30	/	/	SYM
ejpam-5923	148	31	eur	eur	PROPN
ejpam-5923	148	32	.	.	PUNCT
ejpam-5923	149	1	j.	j.	PROPN
ejpam-5923	149	2	pure	pure	PROPN
ejpam-5923	149	3	appl	appl	PROPN
ejpam-5923	149	4	.	.	PROPN
ejpam-5923	149	5	math	math	PROPN
ejpam-5923	149	6	,	,	PUNCT
ejpam-5923	149	7	18	18	NUM
ejpam-5923	149	8	(	(	PUNCT
ejpam-5923	149	9	2	2	NUM
ejpam-5923	149	10	)	)	PUNCT
ejpam-5923	149	11	(	(	PUNCT
ejpam-5923	149	12	2025	2025	NUM
ejpam-5923	149	13	)	)	PUNCT
ejpam-5923	149	14	,	,	PUNCT
ejpam-5923	149	15	5923	5923	NUM
ejpam-5923	149	16	10	10	NUM
ejpam-5923	149	17	of	of	ADP
ejpam-5923	149	18	21	21	NUM
ejpam-5923	149	19	figure	figure	NOUN
ejpam-5923	149	20	6	6	NUM
ejpam-5923	149	21	presents	present	NOUN
ejpam-5923	149	22	plots	plot	NOUN
ejpam-5923	149	23	of	of	ADP
ejpam-5923	149	24	the	the	DET
ejpam-5923	149	25	pdf	pdf	NOUN
ejpam-5923	149	26	of	of	ADP
ejpam-5923	149	27	the	the	DET
ejpam-5923	149	28	esu	esu	NOUN
ejpam-5923	149	29	type	type	NOUN
ejpam-5923	149	30	-	-	PUNCT
ejpam-5923	149	31	x	x	NOUN
ejpam-5923	149	32	distribution	distribution	NOUN
ejpam-5923	149	33	for	for	ADP
ejpam-5923	149	34	varying	vary	VERB
ejpam-5923	149	35	values	value	NOUN
ejpam-5923	149	36	of	of	ADP
ejpam-5923	149	37	λ	λ	PROPN
ejpam-5923	149	38	.	.	PUNCT
ejpam-5923	150	1	it	it	PRON
ejpam-5923	150	2	is	be	AUX
ejpam-5923	150	3	observed	observe	VERB
ejpam-5923	150	4	from	from	ADP
ejpam-5923	150	5	the	the	DET
ejpam-5923	150	6	said	say	VERB
ejpam-5923	150	7	figures	figure	NOUN
ejpam-5923	150	8	that	that	SCONJ
ejpam-5923	150	9	the	the	DET
ejpam-5923	150	10	behavior	behavior	NOUN
ejpam-5923	150	11	of	of	ADP
ejpam-5923	150	12	the	the	DET
ejpam-5923	150	13	distributions	distribution	NOUN
ejpam-5923	150	14	is	be	AUX
ejpam-5923	150	15	increasing	increase	VERB
ejpam-5923	150	16	for	for	ADP
ejpam-5923	150	17	λ	λ	PROPN
ejpam-5923	150	18	∈	∈	PROPN
ejpam-5923	151	1	[	[	X
ejpam-5923	151	2	−0.1	−0.1	PROPN
ejpam-5923	151	3	,	,	PUNCT
ejpam-5923	151	4	0	0	NUM
ejpam-5923	151	5	)	)	PUNCT
ejpam-5923	151	6	,	,	PUNCT
ejpam-5923	151	7	constant	constant	ADJ
ejpam-5923	151	8	for	for	ADP
ejpam-5923	151	9	λ	λ	PROPN
ejpam-5923	151	10	=	=	SYM
ejpam-5923	151	11	0	0	NUM
ejpam-5923	151	12	,	,	PUNCT
ejpam-5923	151	13	and	and	CCONJ
ejpam-5923	151	14	decreasing	decrease	VERB
ejpam-5923	151	15	for	for	ADP
ejpam-5923	151	16	λ	λ	PROPN
ejpam-5923	151	17	∈	∈	PROPN
ejpam-5923	151	18	(	(	PUNCT
ejpam-5923	151	19	0	0	NUM
ejpam-5923	151	20	,	,	PUNCT
ejpam-5923	151	21	1	1	NUM
ejpam-5923	151	22	]	]	PUNCT
ejpam-5923	151	23	.	.	PUNCT
ejpam-5923	152	1	3	3	X
ejpam-5923	152	2	.	.	X
ejpam-5923	153	1	some	some	DET
ejpam-5923	153	2	properties	property	NOUN
ejpam-5923	153	3	of	of	ADP
ejpam-5923	153	4	the	the	DET
ejpam-5923	153	5	generalized	generalize	VERB
ejpam-5923	153	6	extended	extend	VERB
ejpam-5923	153	7	standard	standard	ADJ
ejpam-5923	153	8	u	u	ADJ
ejpam-5923	153	9	-	-	ADJ
ejpam-5923	153	10	quadratic	quadratic	ADJ
ejpam-5923	153	11	distribution	distribution	NOUN
ejpam-5923	153	12	in	in	ADP
ejpam-5923	153	13	this	this	DET
ejpam-5923	153	14	section	section	NOUN
ejpam-5923	153	15	,	,	PUNCT
ejpam-5923	153	16	we	we	PRON
ejpam-5923	153	17	present	present	VERB
ejpam-5923	153	18	some	some	DET
ejpam-5923	153	19	properties	property	NOUN
ejpam-5923	153	20	of	of	ADP
ejpam-5923	153	21	the	the	DET
ejpam-5923	153	22	proposed	propose	VERB
ejpam-5923	153	23	generalized	generalized	ADJ
ejpam-5923	153	24	distribution	distribution	NOUN
ejpam-5923	153	25	such	such	ADJ
ejpam-5923	153	26	as	as	ADP
ejpam-5923	153	27	the	the	DET
ejpam-5923	153	28	limiting	limit	VERB
ejpam-5923	153	29	behavior	behavior	NOUN
ejpam-5923	153	30	of	of	ADP
ejpam-5923	153	31	the	the	DET
ejpam-5923	153	32	pdf	pdf	NOUN
ejpam-5923	153	33	,	,	PUNCT
ejpam-5923	153	34	mode	mode	NOUN
ejpam-5923	153	35	,	,	PUNCT
ejpam-5923	153	36	moments	moment	NOUN
ejpam-5923	153	37	,	,	PUNCT
ejpam-5923	153	38	mean	mean	VERB
ejpam-5923	153	39	,	,	PUNCT
ejpam-5923	153	40	variance	variance	NOUN
ejpam-5923	153	41	,	,	PUNCT
ejpam-5923	153	42	skewness	skewness	NOUN
ejpam-5923	153	43	,	,	PUNCT
ejpam-5923	153	44	kurtosis	kurtosis	NOUN
ejpam-5923	153	45	,	,	PUNCT
ejpam-5923	153	46	and	and	CCONJ
ejpam-5923	153	47	the	the	DET
ejpam-5923	153	48	moment	moment	NOUN
ejpam-5923	153	49	generating	generate	VERB
ejpam-5923	153	50	function	function	NOUN
ejpam-5923	153	51	.	.	PUNCT
ejpam-5923	154	1	lemma	lemma	PROPN
ejpam-5923	154	2	1	1	X
ejpam-5923	154	3	.	.	PUNCT
ejpam-5923	155	1	let	let	VERB
ejpam-5923	155	2	t	t	NOUN
ejpam-5923	155	3	be	be	AUX
ejpam-5923	155	4	a	a	DET
ejpam-5923	155	5	random	random	ADJ
ejpam-5923	155	6	variable	variable	NOUN
ejpam-5923	155	7	that	that	PRON
ejpam-5923	155	8	follows	follow	VERB
ejpam-5923	155	9	a	a	DET
ejpam-5923	155	10	gesu	gesu	NOUN
ejpam-5923	155	11	distribution	distribution	NOUN
ejpam-5923	155	12	,	,	PUNCT
ejpam-5923	155	13	then	then	ADV
ejpam-5923	155	14	lim	lim	PROPN
ejpam-5923	155	15	t→0	t→0	PUNCT
ejpam-5923	155	16	f(t	f(t	PROPN
ejpam-5923	155	17	)	)	PUNCT
ejpam-5923	155	18	=	=	SYM
ejpam-5923	155	19	1−	1−	NUM
ejpam-5923	155	20	λ+	λ+	PUNCT
ejpam-5923	155	21	3λa2	3λa2	NUM
ejpam-5923	155	22	(	(	PUNCT
ejpam-5923	155	23	1−	1−	NUM
ejpam-5923	155	24	a)3	a)3	ADJ
ejpam-5923	155	25	+	+	NUM
ejpam-5923	155	26	a3	a3	NOUN
ejpam-5923	155	27	,	,	PUNCT
ejpam-5923	155	28	and	and	CCONJ
ejpam-5923	155	29	lim	lim	PROPN
ejpam-5923	155	30	t→1	t→1	PROPN
ejpam-5923	155	31	f(t	f(t	PROPN
ejpam-5923	155	32	)	)	PUNCT
ejpam-5923	155	33	=	=	SYM
ejpam-5923	156	1	1−	1−	NUM
ejpam-5923	156	2	λ+	λ+	PUNCT
ejpam-5923	156	3	3λ(1−	3λ(1−	NUM
ejpam-5923	156	4	a)2	a)2	NOUN
ejpam-5923	156	5	(	(	PUNCT
ejpam-5923	156	6	1−	1−	NUM
ejpam-5923	156	7	a)3	a)3	ADJ
ejpam-5923	156	8	+	+	NUM
ejpam-5923	156	9	a3	a3	NOUN
ejpam-5923	156	10	,	,	PUNCT
ejpam-5923	156	11	where	where	SCONJ
ejpam-5923	156	12	t	t	PROPN
ejpam-5923	156	13	∈	∈	PROPN
ejpam-5923	157	1	[	[	X
ejpam-5923	157	2	0	0	NUM
ejpam-5923	157	3	,	,	PUNCT
ejpam-5923	157	4	1	1	NUM
ejpam-5923	157	5	]	]	PUNCT
ejpam-5923	157	6	,	,	PUNCT
ejpam-5923	157	7	a	a	DET
ejpam-5923	157	8	∈	∈	NOUN
ejpam-5923	158	1	[	[	X
ejpam-5923	158	2	0	0	NUM
ejpam-5923	158	3	,	,	PUNCT
ejpam-5923	158	4	1	1	NUM
ejpam-5923	158	5	]	]	PUNCT
ejpam-5923	158	6	and	and	CCONJ
ejpam-5923	158	7	λ	λ	PART
ejpam-5923	158	8	∈	∈	PROPN
ejpam-5923	158	9			X
ejpam-5923	158	10	[	[	PUNCT
ejpam-5923	158	11	−	−	X
ejpam-5923	158	12	(	(	PUNCT
ejpam-5923	158	13	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	158	14	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	158	15	,	,	PUNCT
ejpam-5923	158	16	1	1	NUM
ejpam-5923	158	17	]	]	PUNCT
ejpam-5923	158	18	,	,	PUNCT
ejpam-5923	158	19	if	if	SCONJ
ejpam-5923	158	20	a	a	DET
ejpam-5923	158	21	∈	∈	NOUN
ejpam-5923	159	1	[	[	X
ejpam-5923	159	2	0	0	NUM
ejpam-5923	159	3	,	,	PUNCT
ejpam-5923	159	4	0.5	0.5	NUM
ejpam-5923	159	5	]	]	PUNCT
ejpam-5923	159	6	[	[	PUNCT
ejpam-5923	159	7	−	−	X
ejpam-5923	159	8	(	(	PUNCT
ejpam-5923	159	9	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	159	10	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	159	11	,	,	PUNCT
ejpam-5923	159	12	1	1	NUM
ejpam-5923	159	13	]	]	PUNCT
ejpam-5923	159	14	,	,	PUNCT
ejpam-5923	159	15	if	if	SCONJ
ejpam-5923	159	16	a	a	DET
ejpam-5923	159	17	∈	∈	NOUN
ejpam-5923	159	18	[	[	X
ejpam-5923	159	19	0.5	0.5	NUM
ejpam-5923	159	20	,	,	PUNCT
ejpam-5923	159	21	1	1	NUM
ejpam-5923	159	22	]	]	PUNCT
ejpam-5923	159	23	.	.	PUNCT
ejpam-5923	160	1	proof	proof	NOUN
ejpam-5923	160	2	.	.	PUNCT
ejpam-5923	161	1	the	the	DET
ejpam-5923	161	2	limit	limit	NOUN
ejpam-5923	161	3	of	of	ADP
ejpam-5923	161	4	f(t	f(t	PROPN
ejpam-5923	161	5	)	)	PUNCT
ejpam-5923	161	6	as	as	ADP
ejpam-5923	161	7	t	t	PROPN
ejpam-5923	161	8	→	→	SYM
ejpam-5923	161	9	0	0	NUM
ejpam-5923	161	10	and	and	CCONJ
ejpam-5923	161	11	t	t	PROPN
ejpam-5923	161	12	→	→	SYM
ejpam-5923	161	13	1	1	NUM
ejpam-5923	161	14	are	be	AUX
ejpam-5923	161	15	,	,	PUNCT
ejpam-5923	161	16	respectively	respectively	ADV
ejpam-5923	161	17	,	,	PUNCT
ejpam-5923	161	18	computed	compute	VERB
ejpam-5923	161	19	as	as	ADP
ejpam-5923	161	20	lim	lim	PROPN
ejpam-5923	161	21	t→0	t→0	PUNCT
ejpam-5923	161	22	f(t	f(t	PROPN
ejpam-5923	161	23	)	)	PUNCT
ejpam-5923	161	24	=	=	SYM
ejpam-5923	161	25	lim	lim	PROPN
ejpam-5923	161	26	t→0	t→0	X
ejpam-5923	162	1	[	[	PUNCT
ejpam-5923	162	2	1−	1−	NUM
ejpam-5923	162	3	λ+	λ+	PUNCT
ejpam-5923	162	4	3λ	3λ	NUM
ejpam-5923	162	5	(	(	PUNCT
ejpam-5923	162	6	1−	1−	NUM
ejpam-5923	162	7	a)3	a)3	ADJ
ejpam-5923	162	8	+	+	NUM
ejpam-5923	162	9	a3	a3	NOUN
ejpam-5923	162	10	(	(	PUNCT
ejpam-5923	162	11	t−	t−	PROPN
ejpam-5923	162	12	a)2	a)2	NOUN
ejpam-5923	162	13	]	]	PUNCT
ejpam-5923	163	1	=	=	SYM
ejpam-5923	163	2	1−	1−	NUM
ejpam-5923	163	3	λ+	λ+	PUNCT
ejpam-5923	163	4	3λ	3λ	NUM
ejpam-5923	163	5	(	(	PUNCT
ejpam-5923	163	6	1−	1−	NUM
ejpam-5923	163	7	a)3	a)3	ADJ
ejpam-5923	163	8	+	+	NUM
ejpam-5923	163	9	a3	a3	NOUN
ejpam-5923	163	10	a2	a2	PROPN
ejpam-5923	163	11	,	,	PUNCT
ejpam-5923	163	12	and	and	CCONJ
ejpam-5923	163	13	lim	lim	PROPN
ejpam-5923	163	14	t→1	t→1	PROPN
ejpam-5923	163	15	f(t	f(t	PROPN
ejpam-5923	163	16	)	)	PUNCT
ejpam-5923	163	17	=	=	SYM
ejpam-5923	163	18	lim	lim	PROPN
ejpam-5923	163	19	t→1	t→1	PROPN
ejpam-5923	164	1	[	[	PUNCT
ejpam-5923	164	2	1−	1−	NUM
ejpam-5923	164	3	λ+	λ+	PUNCT
ejpam-5923	164	4	3λ	3λ	NUM
ejpam-5923	164	5	(	(	PUNCT
ejpam-5923	164	6	1−	1−	NUM
ejpam-5923	164	7	a)3	a)3	ADJ
ejpam-5923	164	8	+	+	NUM
ejpam-5923	164	9	a3	a3	NOUN
ejpam-5923	164	10	(	(	PUNCT
ejpam-5923	164	11	t−	t−	PROPN
ejpam-5923	164	12	a)2	a)2	NOUN
ejpam-5923	164	13	]	]	PUNCT
ejpam-5923	165	1	=	=	SYM
ejpam-5923	165	2	1−	1−	NUM
ejpam-5923	165	3	λ+	λ+	PUNCT
ejpam-5923	165	4	3λ	3λ	NUM
ejpam-5923	165	5	(	(	PUNCT
ejpam-5923	165	6	1−	1−	NUM
ejpam-5923	165	7	a)3	a)3	ADJ
ejpam-5923	165	8	+	+	NUM
ejpam-5923	165	9	a3	a3	NOUN
ejpam-5923	165	10	(	(	PUNCT
ejpam-5923	165	11	1−	1−	NUM
ejpam-5923	165	12	a)2	a)2	PROPN
ejpam-5923	165	13	,	,	PUNCT
ejpam-5923	165	14	where	where	SCONJ
ejpam-5923	165	15	t	t	PROPN
ejpam-5923	165	16	∈	∈	PROPN
ejpam-5923	166	1	[	[	X
ejpam-5923	166	2	0	0	NUM
ejpam-5923	166	3	,	,	PUNCT
ejpam-5923	166	4	1	1	NUM
ejpam-5923	166	5	]	]	PUNCT
ejpam-5923	166	6	,	,	PUNCT
ejpam-5923	166	7	a	a	DET
ejpam-5923	166	8	∈	∈	NOUN
ejpam-5923	167	1	[	[	X
ejpam-5923	167	2	0	0	NUM
ejpam-5923	167	3	,	,	PUNCT
ejpam-5923	167	4	1	1	NUM
ejpam-5923	167	5	]	]	PUNCT
ejpam-5923	167	6	and	and	CCONJ
ejpam-5923	167	7	λ	λ	PART
ejpam-5923	167	8	∈	∈	PROPN
ejpam-5923	167	9			X
ejpam-5923	167	10	[	[	PUNCT
ejpam-5923	167	11	−	−	X
ejpam-5923	167	12	(	(	PUNCT
ejpam-5923	167	13	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	167	14	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	167	15	,	,	PUNCT
ejpam-5923	167	16	1	1	NUM
ejpam-5923	167	17	]	]	PUNCT
ejpam-5923	167	18	,	,	PUNCT
ejpam-5923	167	19	if	if	SCONJ
ejpam-5923	167	20	a	a	DET
ejpam-5923	167	21	∈	∈	NOUN
ejpam-5923	168	1	[	[	X
ejpam-5923	168	2	0	0	NUM
ejpam-5923	168	3	,	,	PUNCT
ejpam-5923	168	4	0.5	0.5	NUM
ejpam-5923	168	5	]	]	PUNCT
ejpam-5923	168	6	[	[	PUNCT
ejpam-5923	168	7	−	−	X
ejpam-5923	168	8	(	(	PUNCT
ejpam-5923	168	9	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	168	10	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	168	11	,	,	PUNCT
ejpam-5923	168	12	1	1	NUM
ejpam-5923	168	13	]	]	PUNCT
ejpam-5923	168	14	,	,	PUNCT
ejpam-5923	168	15	if	if	SCONJ
ejpam-5923	168	16	a	a	DET
ejpam-5923	168	17	∈	∈	NOUN
ejpam-5923	168	18	[	[	X
ejpam-5923	168	19	0.5	0.5	NUM
ejpam-5923	168	20	,	,	PUNCT
ejpam-5923	168	21	1	1	NUM
ejpam-5923	168	22	]	]	PUNCT
ejpam-5923	168	23	.	.	PUNCT
ejpam-5923	168	24	i.	i.	PROPN
ejpam-5923	168	25	a.	a.	PROPN
ejpam-5923	168	26	lakibul	lakibul	PROPN
ejpam-5923	168	27	,	,	PUNCT
ejpam-5923	168	28	d.	d.	PROPN
ejpam-5923	168	29	l.	l.	PROPN
ejpam-5923	168	30	polestico	polestico	PROPN
ejpam-5923	168	31	,	,	PUNCT
ejpam-5923	168	32	a.	a.	PROPN
ejpam-5923	168	33	p.	p.	NOUN
ejpam-5923	168	34	supe	supe	PROPN
ejpam-5923	168	35	/	/	SYM
ejpam-5923	168	36	eur	eur	PROPN
ejpam-5923	168	37	.	.	PUNCT
ejpam-5923	169	1	j.	j.	PROPN
ejpam-5923	169	2	pure	pure	PROPN
ejpam-5923	169	3	appl	appl	PROPN
ejpam-5923	169	4	.	.	PROPN
ejpam-5923	169	5	math	math	PROPN
ejpam-5923	169	6	,	,	PUNCT
ejpam-5923	169	7	18	18	NUM
ejpam-5923	169	8	(	(	PUNCT
ejpam-5923	169	9	2	2	NUM
ejpam-5923	169	10	)	)	PUNCT
ejpam-5923	169	11	(	(	PUNCT
ejpam-5923	169	12	2025	2025	NUM
ejpam-5923	169	13	)	)	PUNCT
ejpam-5923	169	14	,	,	PUNCT
ejpam-5923	169	15	5923	5923	NUM
ejpam-5923	169	16	11	11	NUM
ejpam-5923	169	17	of	of	ADP
ejpam-5923	169	18	21	21	NUM
ejpam-5923	169	19	remark	remark	NOUN
ejpam-5923	169	20	1	1	NUM
ejpam-5923	169	21	.	.	PUNCT
ejpam-5923	170	1	if	if	SCONJ
ejpam-5923	170	2	a	a	DET
ejpam-5923	170	3	=	=	SYM
ejpam-5923	170	4	0.5	0.5	NUM
ejpam-5923	170	5	,	,	PUNCT
ejpam-5923	170	6	then	then	ADV
ejpam-5923	170	7	lim	lim	PROPN
ejpam-5923	170	8	t→0	t→0	PUNCT
ejpam-5923	170	9	f(t	f(t	PROPN
ejpam-5923	170	10	)	)	PUNCT
ejpam-5923	170	11	=	=	SYM
ejpam-5923	170	12	lim	lim	PROPN
ejpam-5923	170	13	t→1	t→1	PROPN
ejpam-5923	170	14	f(t	f(t	PROPN
ejpam-5923	170	15	)	)	PUNCT
ejpam-5923	170	16	=	=	SYM
ejpam-5923	170	17	1	1	NUM
ejpam-5923	170	18	+	+	NUM
ejpam-5923	170	19	2λ	2λ	NOUN
ejpam-5923	170	20	.	.	PUNCT
ejpam-5923	171	1	lemma	lemma	PROPN
ejpam-5923	171	2	2	2	X
ejpam-5923	171	3	.	.	PUNCT
ejpam-5923	172	1	let	let	VERB
ejpam-5923	172	2	t	t	PROPN
ejpam-5923	172	3	be	be	AUX
ejpam-5923	172	4	a	a	DET
ejpam-5923	172	5	random	random	ADJ
ejpam-5923	172	6	variable	variable	NOUN
ejpam-5923	172	7	that	that	PRON
ejpam-5923	172	8	follows	follow	VERB
ejpam-5923	172	9	a	a	DET
ejpam-5923	172	10	gesu	gesu	NOUN
ejpam-5923	172	11	distribution	distribution	NOUN
ejpam-5923	172	12	,	,	PUNCT
ejpam-5923	172	13	then	then	ADV
ejpam-5923	172	14	the	the	DET
ejpam-5923	172	15	mode	mode	NOUN
ejpam-5923	172	16	of	of	ADP
ejpam-5923	172	17	t	t	PROPN
ejpam-5923	172	18	is	be	AUX
ejpam-5923	172	19	a	a	DET
ejpam-5923	172	20	if	if	SCONJ
ejpam-5923	172	21	λ	λ	X
ejpam-5923	172	22	∈	∈	X
ejpam-5923	172	23			PUNCT
ejpam-5923	172	24	[	[	PUNCT
ejpam-5923	172	25	−	−	X
ejpam-5923	172	26	(	(	PUNCT
ejpam-5923	172	27	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	172	28	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	172	29	,	,	PUNCT
ejpam-5923	172	30	0	0	NUM
ejpam-5923	172	31	)	)	PUNCT
ejpam-5923	172	32	if	if	SCONJ
ejpam-5923	172	33	a	a	DET
ejpam-5923	172	34	∈	∈	NOUN
ejpam-5923	173	1	[	[	X
ejpam-5923	173	2	0	0	NUM
ejpam-5923	173	3	,	,	PUNCT
ejpam-5923	173	4	0.5	0.5	NUM
ejpam-5923	173	5	]	]	PUNCT
ejpam-5923	173	6	[	[	PUNCT
ejpam-5923	173	7	−	−	X
ejpam-5923	173	8	(	(	PUNCT
ejpam-5923	173	9	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	173	10	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	173	11	,	,	PUNCT
ejpam-5923	173	12	0	0	NUM
ejpam-5923	173	13	)	)	PUNCT
ejpam-5923	173	14	if	if	SCONJ
ejpam-5923	173	15	a	a	DET
ejpam-5923	173	16	∈	∈	NOUN
ejpam-5923	173	17	[	[	X
ejpam-5923	173	18	0.5	0.5	NUM
ejpam-5923	173	19	,	,	PUNCT
ejpam-5923	173	20	1	1	NUM
ejpam-5923	173	21	]	]	PUNCT
ejpam-5923	173	22	.	.	PUNCT
ejpam-5923	174	1	proof	proof	NOUN
ejpam-5923	174	2	.	.	PUNCT
ejpam-5923	175	1	let	let	VERB
ejpam-5923	175	2	t	t	NOUN
ejpam-5923	175	3	be	be	AUX
ejpam-5923	175	4	a	a	DET
ejpam-5923	175	5	random	random	ADJ
ejpam-5923	175	6	variable	variable	NOUN
ejpam-5923	175	7	that	that	PRON
ejpam-5923	175	8	follows	follow	VERB
ejpam-5923	175	9	a	a	DET
ejpam-5923	175	10	gesu	gesu	NOUN
ejpam-5923	175	11	distribution	distribution	NOUN
ejpam-5923	175	12	.	.	PUNCT
ejpam-5923	176	1	to	to	PART
ejpam-5923	176	2	compute	compute	VERB
ejpam-5923	176	3	for	for	ADP
ejpam-5923	176	4	the	the	DET
ejpam-5923	176	5	mode	mode	NOUN
ejpam-5923	176	6	of	of	ADP
ejpam-5923	176	7	a	a	DET
ejpam-5923	176	8	gesu	gesu	NOUN
ejpam-5923	176	9	distribution	distribution	NOUN
ejpam-5923	176	10	,	,	PUNCT
ejpam-5923	176	11	let	let	VERB
ejpam-5923	176	12	us	we	PRON
ejpam-5923	176	13	first	first	ADV
ejpam-5923	176	14	take	take	VERB
ejpam-5923	176	15	the	the	DET
ejpam-5923	176	16	first	first	ADJ
ejpam-5923	176	17	derivative	derivative	NOUN
ejpam-5923	176	18	of	of	ADP
ejpam-5923	176	19	f(t	f(t	NOUN
ejpam-5923	176	20	)	)	PUNCT
ejpam-5923	176	21	,	,	PUNCT
ejpam-5923	176	22	that	that	ADV
ejpam-5923	176	23	is	is	ADV
ejpam-5923	176	24	,	,	PUNCT
ejpam-5923	176	25	df(t	df(t	NOUN
ejpam-5923	176	26	)	)	PUNCT
ejpam-5923	176	27	dt	dt	NOUN
ejpam-5923	177	1	=	=	SYM
ejpam-5923	177	2	6λ	6λ	PROPN
ejpam-5923	177	3	(	(	PUNCT
ejpam-5923	177	4	1−	1−	NUM
ejpam-5923	177	5	a)3	a)3	ADJ
ejpam-5923	177	6	+	+	NUM
ejpam-5923	177	7	a3	a3	NOUN
ejpam-5923	177	8	(	(	PUNCT
ejpam-5923	177	9	t−	t−	PROPN
ejpam-5923	177	10	a	a	X
ejpam-5923	177	11	)	)	PUNCT
ejpam-5923	177	12	.	.	PUNCT
ejpam-5923	178	1	equating	equate	VERB
ejpam-5923	178	2	df(t	df(t	NOUN
ejpam-5923	178	3	)	)	PUNCT
ejpam-5923	178	4	dt	dt	NOUN
ejpam-5923	179	1	=	=	SYM
ejpam-5923	179	2	0	0	NUM
ejpam-5923	179	3	,	,	PUNCT
ejpam-5923	179	4	it	it	PRON
ejpam-5923	179	5	follows	follow	VERB
ejpam-5923	179	6	that	that	SCONJ
ejpam-5923	179	7	6λ(t−	6λ(t−	NUM
ejpam-5923	179	8	a	a	X
ejpam-5923	179	9	)	)	PUNCT
ejpam-5923	179	10	(	(	PUNCT
ejpam-5923	179	11	1−	1−	NUM
ejpam-5923	179	12	a)3	a)3	ADJ
ejpam-5923	179	13	+	+	NUM
ejpam-5923	179	14	a3	a3	NOUN
ejpam-5923	180	1	=	=	SYM
ejpam-5923	180	2	0	0	NUM
ejpam-5923	180	3	=	=	NOUN
ejpam-5923	180	4	⇒	⇒	NOUN
ejpam-5923	180	5	t	t	NOUN
ejpam-5923	180	6	=	=	NOUN
ejpam-5923	180	7	a	a	DET
ejpam-5923	180	8	the	the	DET
ejpam-5923	180	9	second	second	ADJ
ejpam-5923	180	10	derivative	derivative	NOUN
ejpam-5923	180	11	of	of	ADP
ejpam-5923	180	12	f(t	f(t	PROPN
ejpam-5923	180	13	)	)	PUNCT
ejpam-5923	180	14	is	be	AUX
ejpam-5923	180	15	given	give	VERB
ejpam-5923	180	16	by	by	ADP
ejpam-5923	180	17	f	f	PROPN
ejpam-5923	180	18	′′(t	′′(t	PROPN
ejpam-5923	180	19	)	)	PUNCT
ejpam-5923	180	20	=	=	PUNCT
ejpam-5923	181	1	[	[	PUNCT
ejpam-5923	181	2	6	6	NUM
ejpam-5923	181	3	(	(	PUNCT
ejpam-5923	181	4	1−	1−	NUM
ejpam-5923	181	5	a)3	a)3	ADJ
ejpam-5923	181	6	+	+	NUM
ejpam-5923	181	7	a3	a3	NOUN
ejpam-5923	181	8	]	]	PUNCT
ejpam-5923	181	9	λ	λ	AUX
ejpam-5923	181	10	.	.	PUNCT
ejpam-5923	181	11	note	note	VERB
ejpam-5923	181	12	that	that	SCONJ
ejpam-5923	181	13	,	,	PUNCT
ejpam-5923	181	14	for	for	ADP
ejpam-5923	181	15	a	a	DET
ejpam-5923	181	16	∈	∈	PROPN
ejpam-5923	181	17	[	[	X
ejpam-5923	181	18	0	0	NUM
ejpam-5923	181	19	,	,	PUNCT
ejpam-5923	181	20	1	1	NUM
ejpam-5923	181	21	]	]	PUNCT
ejpam-5923	181	22	and	and	CCONJ
ejpam-5923	181	23	t	t	PROPN
ejpam-5923	181	24	∈	∈	PROPN
ejpam-5923	182	1	[	[	X
ejpam-5923	182	2	0	0	NUM
ejpam-5923	182	3	,	,	PUNCT
ejpam-5923	182	4	1	1	NUM
ejpam-5923	182	5	]	]	PUNCT
ejpam-5923	182	6	,	,	PUNCT
ejpam-5923	182	7	we	we	PRON
ejpam-5923	182	8	have	have	VERB
ejpam-5923	182	9	6	6	NUM
ejpam-5923	182	10	(	(	PUNCT
ejpam-5923	182	11	1−	1−	NUM
ejpam-5923	182	12	a)3	a)3	ADJ
ejpam-5923	182	13	+	+	NUM
ejpam-5923	182	14	a3	a3	NOUN
ejpam-5923	182	15	>	>	X
ejpam-5923	182	16	0	0	X
ejpam-5923	182	17	.	.	PUNCT
ejpam-5923	183	1	so	so	ADV
ejpam-5923	183	2	,	,	PUNCT
ejpam-5923	183	3	f	f	PROPN
ejpam-5923	183	4	′′(t	′′(t	PROPN
ejpam-5923	183	5	)	)	PUNCT
ejpam-5923	184	1	<	<	X
ejpam-5923	184	2	0	0	PUNCT
ejpam-5923	185	1	if	if	SCONJ
ejpam-5923	185	2	λ	λ	PROPN
ejpam-5923	185	3	∈	∈	X
ejpam-5923	185	4			X
ejpam-5923	185	5	[	[	PUNCT
ejpam-5923	185	6	−	−	X
ejpam-5923	185	7	(	(	PUNCT
ejpam-5923	185	8	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	185	9	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	185	10	,	,	PUNCT
ejpam-5923	185	11	0	0	NUM
ejpam-5923	185	12	)	)	PUNCT
ejpam-5923	185	13	,	,	PUNCT
ejpam-5923	185	14	if	if	SCONJ
ejpam-5923	185	15	a	a	DET
ejpam-5923	185	16	∈	∈	NOUN
ejpam-5923	186	1	[	[	X
ejpam-5923	186	2	0	0	NUM
ejpam-5923	186	3	,	,	PUNCT
ejpam-5923	186	4	0.5	0.5	NUM
ejpam-5923	186	5	]	]	PUNCT
ejpam-5923	186	6	[	[	PUNCT
ejpam-5923	186	7	−	−	X
ejpam-5923	186	8	(	(	PUNCT
ejpam-5923	186	9	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	186	10	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	186	11	,	,	PUNCT
ejpam-5923	186	12	0	0	NUM
ejpam-5923	186	13	)	)	PUNCT
ejpam-5923	186	14	,	,	PUNCT
ejpam-5923	186	15	if	if	SCONJ
ejpam-5923	186	16	a	a	DET
ejpam-5923	186	17	∈	∈	NOUN
ejpam-5923	186	18	[	[	X
ejpam-5923	186	19	0.5	0.5	NUM
ejpam-5923	186	20	,	,	PUNCT
ejpam-5923	186	21	1	1	NUM
ejpam-5923	186	22	]	]	PUNCT
ejpam-5923	186	23	.	.	PUNCT
ejpam-5923	187	1	thus	thus	ADV
ejpam-5923	187	2	,	,	PUNCT
ejpam-5923	187	3	the	the	DET
ejpam-5923	187	4	mode	mode	NOUN
ejpam-5923	187	5	of	of	ADP
ejpam-5923	187	6	t	t	PROPN
ejpam-5923	187	7	is	be	AUX
ejpam-5923	187	8	a	a	DET
ejpam-5923	187	9	if	if	SCONJ
ejpam-5923	187	10	λ	λ	X
ejpam-5923	187	11	∈	∈	X
ejpam-5923	187	12			PUNCT
ejpam-5923	187	13	[	[	PUNCT
ejpam-5923	187	14	−	−	X
ejpam-5923	187	15	(	(	PUNCT
ejpam-5923	187	16	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	187	17	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	187	18	,	,	PUNCT
ejpam-5923	187	19	0	0	NUM
ejpam-5923	187	20	)	)	PUNCT
ejpam-5923	187	21	,	,	PUNCT
ejpam-5923	187	22	if	if	SCONJ
ejpam-5923	187	23	a	a	DET
ejpam-5923	187	24	∈	∈	NOUN
ejpam-5923	188	1	[	[	X
ejpam-5923	188	2	0	0	NUM
ejpam-5923	188	3	,	,	PUNCT
ejpam-5923	188	4	0.5	0.5	NUM
ejpam-5923	188	5	]	]	PUNCT
ejpam-5923	188	6	[	[	PUNCT
ejpam-5923	188	7	−	−	X
ejpam-5923	188	8	(	(	PUNCT
ejpam-5923	188	9	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	188	10	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	188	11	,	,	PUNCT
ejpam-5923	188	12	0	0	NUM
ejpam-5923	188	13	)	)	PUNCT
ejpam-5923	188	14	,	,	PUNCT
ejpam-5923	188	15	if	if	SCONJ
ejpam-5923	188	16	a	a	DET
ejpam-5923	188	17	∈	∈	NOUN
ejpam-5923	188	18	[	[	X
ejpam-5923	188	19	0.5	0.5	NUM
ejpam-5923	188	20	,	,	PUNCT
ejpam-5923	188	21	1	1	NUM
ejpam-5923	188	22	]	]	PUNCT
ejpam-5923	188	23	.	.	PUNCT
ejpam-5923	189	1	i.	i.	PROPN
ejpam-5923	189	2	a.	a.	PROPN
ejpam-5923	189	3	lakibul	lakibul	PROPN
ejpam-5923	189	4	,	,	PUNCT
ejpam-5923	189	5	d.	d.	PROPN
ejpam-5923	189	6	l.	l.	PROPN
ejpam-5923	189	7	polestico	polestico	PROPN
ejpam-5923	189	8	,	,	PUNCT
ejpam-5923	189	9	a.	a.	PROPN
ejpam-5923	189	10	p.	p.	NOUN
ejpam-5923	189	11	supe	supe	PROPN
ejpam-5923	189	12	/	/	SYM
ejpam-5923	189	13	eur	eur	PROPN
ejpam-5923	189	14	.	.	PUNCT
ejpam-5923	190	1	j.	j.	PROPN
ejpam-5923	190	2	pure	pure	PROPN
ejpam-5923	190	3	appl	appl	PROPN
ejpam-5923	190	4	.	.	PROPN
ejpam-5923	190	5	math	math	PROPN
ejpam-5923	190	6	,	,	PUNCT
ejpam-5923	190	7	18	18	NUM
ejpam-5923	190	8	(	(	PUNCT
ejpam-5923	190	9	2	2	NUM
ejpam-5923	190	10	)	)	PUNCT
ejpam-5923	190	11	(	(	PUNCT
ejpam-5923	190	12	2025	2025	NUM
ejpam-5923	190	13	)	)	PUNCT
ejpam-5923	190	14	,	,	PUNCT
ejpam-5923	190	15	5923	5923	NUM
ejpam-5923	190	16	12	12	NUM
ejpam-5923	190	17	of	of	ADP
ejpam-5923	190	18	21	21	NUM
ejpam-5923	190	19	theorem	theorem	NOUN
ejpam-5923	190	20	2	2	NUM
ejpam-5923	190	21	.	.	PUNCT
ejpam-5923	191	1	let	let	VERB
ejpam-5923	191	2	t	t	PROPN
ejpam-5923	191	3	be	be	AUX
ejpam-5923	191	4	a	a	DET
ejpam-5923	191	5	random	random	ADJ
ejpam-5923	191	6	variable	variable	NOUN
ejpam-5923	191	7	that	that	PRON
ejpam-5923	191	8	follows	follow	VERB
ejpam-5923	191	9	a	a	DET
ejpam-5923	191	10	gesu	gesu	NOUN
ejpam-5923	191	11	distribution	distribution	NOUN
ejpam-5923	191	12	,	,	PUNCT
ejpam-5923	191	13	then	then	ADV
ejpam-5923	191	14	the	the	DET
ejpam-5923	191	15	rth	rth	PROPN
ejpam-5923	191	16	moment	moment	NOUN
ejpam-5923	191	17	of	of	ADP
ejpam-5923	191	18	t	t	PROPN
ejpam-5923	191	19	is	be	AUX
ejpam-5923	191	20	given	give	VERB
ejpam-5923	191	21	by	by	ADP
ejpam-5923	191	22	e[t	e[t	PUNCT
ejpam-5923	191	23	r	r	X
ejpam-5923	191	24	]	]	X
ejpam-5923	191	25	=	=	SYM
ejpam-5923	191	26	1−	1−	NUM
ejpam-5923	191	27	λ	λ	NOUN
ejpam-5923	191	28	r	r	NOUN
ejpam-5923	191	29	+	+	NOUN
ejpam-5923	191	30	1	1	NUM
ejpam-5923	191	31	+	+	X
ejpam-5923	191	32	3λ	3λ	NUM
ejpam-5923	191	33	(	(	PUNCT
ejpam-5923	191	34	1−	1−	NUM
ejpam-5923	191	35	a)3	a)3	ADJ
ejpam-5923	191	36	+	+	NUM
ejpam-5923	191	37	a3	a3	NOUN
ejpam-5923	191	38	2∑	2∑	NUM
ejpam-5923	191	39	k=0	k=0	X
ejpam-5923	191	40	(	(	PUNCT
ejpam-5923	191	41	2	2	NUM
ejpam-5923	191	42	k	k	NOUN
ejpam-5923	191	43	)	)	PUNCT
ejpam-5923	191	44	(	(	PUNCT
ejpam-5923	191	45	−a)k	−a)k	NOUN
ejpam-5923	191	46	r	r	NOUN
ejpam-5923	191	47	−	−	PROPN
ejpam-5923	191	48	k	k	PROPN
ejpam-5923	192	1	+	+	CCONJ
ejpam-5923	192	2	3	3	NUM
ejpam-5923	192	3	,	,	PUNCT
ejpam-5923	192	4	(	(	PUNCT
ejpam-5923	192	5	8)	8)	NUM
ejpam-5923	192	6	where	where	SCONJ
ejpam-5923	192	7	a	a	DET
ejpam-5923	192	8	∈	∈	NOUN
ejpam-5923	192	9	[	[	X
ejpam-5923	192	10	0	0	NUM
ejpam-5923	192	11	,	,	PUNCT
ejpam-5923	192	12	1	1	NUM
ejpam-5923	192	13	]	]	PUNCT
ejpam-5923	192	14	,	,	PUNCT
ejpam-5923	192	15	λ	λ	PROPN
ejpam-5923	192	16	∈	∈	PROPN
ejpam-5923	192	17			X
ejpam-5923	192	18	[	[	PUNCT
ejpam-5923	192	19	−	−	X
ejpam-5923	192	20	(	(	PUNCT
ejpam-5923	192	21	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	192	22	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	192	23	,	,	PUNCT
ejpam-5923	192	24	0	0	NUM
ejpam-5923	192	25	)	)	PUNCT
ejpam-5923	192	26	,	,	PUNCT
ejpam-5923	192	27	if	if	SCONJ
ejpam-5923	192	28	a	a	DET
ejpam-5923	192	29	∈	∈	NOUN
ejpam-5923	193	1	[	[	X
ejpam-5923	193	2	0	0	NUM
ejpam-5923	193	3	,	,	PUNCT
ejpam-5923	193	4	0.5	0.5	NUM
ejpam-5923	193	5	]	]	PUNCT
ejpam-5923	193	6	[	[	PUNCT
ejpam-5923	193	7	−	−	X
ejpam-5923	193	8	(	(	PUNCT
ejpam-5923	193	9	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	193	10	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	193	11	,	,	PUNCT
ejpam-5923	193	12	0	0	NUM
ejpam-5923	193	13	)	)	PUNCT
ejpam-5923	193	14	,	,	PUNCT
ejpam-5923	193	15	if	if	SCONJ
ejpam-5923	193	16	a	a	DET
ejpam-5923	193	17	∈	∈	NOUN
ejpam-5923	193	18	[	[	X
ejpam-5923	193	19	0.5	0.5	NUM
ejpam-5923	193	20	,	,	PUNCT
ejpam-5923	193	21	1	1	NUM
ejpam-5923	193	22	]	]	PUNCT
ejpam-5923	193	23	,	,	PUNCT
ejpam-5923	193	24	and	and	CCONJ
ejpam-5923	193	25	r	r	NOUN
ejpam-5923	193	26	=	=	SYM
ejpam-5923	193	27	1	1	NUM
ejpam-5923	193	28	,	,	PUNCT
ejpam-5923	193	29	2	2	NUM
ejpam-5923	193	30	,	,	PUNCT
ejpam-5923	193	31	3	3	NUM
ejpam-5923	193	32	,	,	PUNCT
ejpam-5923	193	33	....	....	PUNCT
ejpam-5923	194	1	proof	proof	NOUN
ejpam-5923	194	2	.	.	PUNCT
ejpam-5923	195	1	let	let	VERB
ejpam-5923	195	2	t	t	NOUN
ejpam-5923	195	3	be	be	AUX
ejpam-5923	195	4	a	a	DET
ejpam-5923	195	5	random	random	ADJ
ejpam-5923	195	6	variable	variable	NOUN
ejpam-5923	195	7	that	that	PRON
ejpam-5923	195	8	follows	follow	VERB
ejpam-5923	195	9	a	a	DET
ejpam-5923	195	10	gesu	gesu	NOUN
ejpam-5923	195	11	distribution	distribution	NOUN
ejpam-5923	195	12	.	.	PUNCT
ejpam-5923	196	1	the	the	DET
ejpam-5923	196	2	rth	rth	PROPN
ejpam-5923	196	3	moment	moment	NOUN
ejpam-5923	196	4	of	of	ADP
ejpam-5923	196	5	t	t	PROPN
ejpam-5923	196	6	is	be	AUX
ejpam-5923	196	7	defined	define	VERB
ejpam-5923	196	8	as	as	ADP
ejpam-5923	196	9	e[t	e[t	PUNCT
ejpam-5923	196	10	r	r	NOUN
ejpam-5923	196	11	]	]	PUNCT
ejpam-5923	196	12	=	=	SYM
ejpam-5923	196	13	∫	∫	PROPN
ejpam-5923	196	14	1	1	NUM
ejpam-5923	196	15	0	0	NUM
ejpam-5923	196	16	tr	tr	PUNCT
ejpam-5923	196	17	[	[	PUNCT
ejpam-5923	196	18	1−	1−	NUM
ejpam-5923	196	19	λ+	λ+	PUNCT
ejpam-5923	196	20	3λ	3λ	NUM
ejpam-5923	196	21	(	(	PUNCT
ejpam-5923	196	22	1−	1−	NUM
ejpam-5923	196	23	a)3	a)3	ADJ
ejpam-5923	196	24	+	+	NUM
ejpam-5923	196	25	a3	a3	NOUN
ejpam-5923	196	26	(	(	PUNCT
ejpam-5923	196	27	t−	t−	PROPN
ejpam-5923	196	28	a)2	a)2	PROPN
ejpam-5923	196	29	]	]	PUNCT
ejpam-5923	196	30	dt	dt	X
ejpam-5923	196	31	=(	=(	PROPN
ejpam-5923	196	32	1−	1−	NUM
ejpam-5923	196	33	λ	λ	NOUN
ejpam-5923	196	34	)	)	PUNCT
ejpam-5923	196	35	∫	∫	PROPN
ejpam-5923	197	1	1	1	NUM
ejpam-5923	197	2	0	0	NUM
ejpam-5923	197	3	trdt+	trdt+	NOUN
ejpam-5923	197	4	3λ	3λ	NUM
ejpam-5923	197	5	(	(	PUNCT
ejpam-5923	197	6	1−	1−	NUM
ejpam-5923	197	7	a)3	a)3	ADJ
ejpam-5923	197	8	+	+	NUM
ejpam-5923	197	9	a3	a3	NOUN
ejpam-5923	197	10	∫	∫	PROPN
ejpam-5923	197	11	1	1	NUM
ejpam-5923	197	12	0	0	NUM
ejpam-5923	197	13	(	(	PUNCT
ejpam-5923	197	14	t−	t−	PROPN
ejpam-5923	197	15	a)2trdt	a)2trdt	PROPN
ejpam-5923	197	16	.	.	PUNCT
ejpam-5923	198	1	but	but	CCONJ
ejpam-5923	198	2	since	since	SCONJ
ejpam-5923	198	3	the	the	DET
ejpam-5923	198	4	binomial	binomial	ADJ
ejpam-5923	198	5	expansion	expansion	NOUN
ejpam-5923	198	6	of	of	ADP
ejpam-5923	198	7	(	(	PUNCT
ejpam-5923	198	8	t−	t−	PROPN
ejpam-5923	198	9	a)2	a)2	PROPN
ejpam-5923	198	10	is	be	AUX
ejpam-5923	198	11	given	give	VERB
ejpam-5923	198	12	by	by	ADP
ejpam-5923	198	13	(	(	PUNCT
ejpam-5923	198	14	t−	t−	PROPN
ejpam-5923	198	15	a)2	a)2	NOUN
ejpam-5923	198	16	=	=	SYM
ejpam-5923	198	17	2∑	2∑	X
ejpam-5923	198	18	k=0	k=0	X
ejpam-5923	198	19	(	(	PUNCT
ejpam-5923	198	20	2	2	NUM
ejpam-5923	198	21	k	k	NOUN
ejpam-5923	198	22	)	)	PUNCT
ejpam-5923	199	1	t2−k(−a)k	t2−k(−a)k	NOUN
ejpam-5923	199	2	,	,	PUNCT
ejpam-5923	199	3	we	we	PRON
ejpam-5923	199	4	have	have	VERB
ejpam-5923	199	5	e[t	e[t	PUNCT
ejpam-5923	199	6	r	r	NOUN
ejpam-5923	199	7	]	]	X
ejpam-5923	199	8	=	=	NOUN
ejpam-5923	199	9	(	(	PUNCT
ejpam-5923	199	10	1−	1−	NUM
ejpam-5923	199	11	λ	λ	NOUN
ejpam-5923	199	12	)	)	PUNCT
ejpam-5923	199	13	∫	∫	PROPN
ejpam-5923	200	1	1	1	NUM
ejpam-5923	200	2	0	0	NUM
ejpam-5923	200	3	trdt+	trdt+	NOUN
ejpam-5923	200	4	3λ	3λ	NUM
ejpam-5923	200	5	(	(	PUNCT
ejpam-5923	200	6	1−	1−	NUM
ejpam-5923	200	7	a)3	a)3	ADJ
ejpam-5923	200	8	+	+	NUM
ejpam-5923	200	9	a3	a3	NOUN
ejpam-5923	200	10	∫	∫	PROPN
ejpam-5923	200	11	1	1	NUM
ejpam-5923	200	12	0	0	NUM
ejpam-5923	200	13	2∑	2∑	NUM
ejpam-5923	200	14	k=0	k=0	X
ejpam-5923	200	15	(	(	PUNCT
ejpam-5923	200	16	2	2	NUM
ejpam-5923	200	17	k	k	NOUN
ejpam-5923	200	18	)	)	PUNCT
ejpam-5923	200	19	t2−k(−a)ktrdt	t2−k(−a)ktrdt	PROPN
ejpam-5923	200	20	=(	=(	NOUN
ejpam-5923	200	21	1−	1−	NUM
ejpam-5923	200	22	λ	λ	NOUN
ejpam-5923	200	23	)	)	PUNCT
ejpam-5923	200	24	1r+1	1r+1	PROPN
ejpam-5923	200	25	r	r	NOUN
ejpam-5923	200	26	+	+	CCONJ
ejpam-5923	200	27	1	1	NUM
ejpam-5923	200	28	+	+	X
ejpam-5923	200	29	3λ	3λ	NUM
ejpam-5923	200	30	(	(	PUNCT
ejpam-5923	200	31	1−	1−	NUM
ejpam-5923	200	32	a)3	a)3	ADJ
ejpam-5923	200	33	+	+	NUM
ejpam-5923	200	34	a3	a3	NOUN
ejpam-5923	200	35	2∑	2∑	NUM
ejpam-5923	200	36	k=0	k=0	X
ejpam-5923	200	37	(	(	PUNCT
ejpam-5923	200	38	2	2	NUM
ejpam-5923	200	39	k	k	NOUN
ejpam-5923	200	40	)	)	PUNCT
ejpam-5923	200	41	(	(	PUNCT
ejpam-5923	200	42	−a)k	−a)k	NOUN
ejpam-5923	200	43	1r−k+3	1r−k+3	NUM
ejpam-5923	200	44	r	r	NOUN
ejpam-5923	200	45	−	−	PROPN
ejpam-5923	200	46	k	k	NOUN
ejpam-5923	201	1	+	+	CCONJ
ejpam-5923	201	2	3	3	NUM
ejpam-5923	201	3	=	=	SYM
ejpam-5923	201	4	1−	1−	NUM
ejpam-5923	201	5	λ	λ	NOUN
ejpam-5923	201	6	r	r	NOUN
ejpam-5923	201	7	+	+	NOUN
ejpam-5923	201	8	1	1	NUM
ejpam-5923	201	9	+	+	X
ejpam-5923	201	10	3λ	3λ	NUM
ejpam-5923	201	11	(	(	PUNCT
ejpam-5923	201	12	1−	1−	NUM
ejpam-5923	201	13	a)3	a)3	ADJ
ejpam-5923	201	14	+	+	NUM
ejpam-5923	201	15	a3	a3	NOUN
ejpam-5923	201	16	2∑	2∑	NUM
ejpam-5923	201	17	k=0	k=0	X
ejpam-5923	201	18	(	(	PUNCT
ejpam-5923	201	19	2	2	NUM
ejpam-5923	201	20	k	k	NOUN
ejpam-5923	201	21	)	)	PUNCT
ejpam-5923	201	22	(	(	PUNCT
ejpam-5923	201	23	−a)k	−a)k	NOUN
ejpam-5923	201	24	r	r	NOUN
ejpam-5923	201	25	−	−	PROPN
ejpam-5923	201	26	k	k	NOUN
ejpam-5923	201	27	+	+	CCONJ
ejpam-5923	201	28	3	3	X
ejpam-5923	201	29	.	.	PUNCT
ejpam-5923	202	1	corollary	corollary	ADJ
ejpam-5923	202	2	1	1	NUM
ejpam-5923	202	3	.	.	PUNCT
ejpam-5923	203	1	let	let	VERB
ejpam-5923	203	2	t	t	NOUN
ejpam-5923	203	3	be	be	AUX
ejpam-5923	203	4	a	a	DET
ejpam-5923	203	5	random	random	ADJ
ejpam-5923	203	6	variable	variable	NOUN
ejpam-5923	203	7	that	that	PRON
ejpam-5923	203	8	follows	follow	VERB
ejpam-5923	203	9	a	a	DET
ejpam-5923	203	10	gesu	gesu	NOUN
ejpam-5923	203	11	distribution	distribution	NOUN
ejpam-5923	203	12	,	,	PUNCT
ejpam-5923	203	13	then	then	ADV
ejpam-5923	203	14	the	the	DET
ejpam-5923	203	15	first	first	ADJ
ejpam-5923	203	16	to	to	ADP
ejpam-5923	203	17	the	the	DET
ejpam-5923	203	18	fourth	fourth	ADJ
ejpam-5923	203	19	raw	raw	ADJ
ejpam-5923	203	20	moment	moment	NOUN
ejpam-5923	203	21	of	of	ADP
ejpam-5923	203	22	t	t	PROPN
ejpam-5923	203	23	are	be	AUX
ejpam-5923	203	24	given	give	VERB
ejpam-5923	203	25	by	by	ADP
ejpam-5923	203	26	:	:	PUNCT
ejpam-5923	203	27	(	(	PUNCT
ejpam-5923	203	28	i.	i.	NOUN
ejpam-5923	203	29	)	)	PUNCT
ejpam-5923	203	30	e[t	e[t	PUNCT
ejpam-5923	203	31	]	]	PUNCT
ejpam-5923	204	1	=	=	PUNCT
ejpam-5923	204	2	1−λ	1−λ	NUM
ejpam-5923	204	3	2	2	NUM
ejpam-5923	204	4	+	+	NUM
ejpam-5923	204	5	3λ	3λ	NUM
ejpam-5923	204	6	(	(	PUNCT
ejpam-5923	204	7	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	204	8	∑2	∑2	NOUN
ejpam-5923	204	9	k=0	k=0	PROPN
ejpam-5923	204	10	(	(	PUNCT
ejpam-5923	204	11	2	2	NUM
ejpam-5923	204	12	k	k	NOUN
ejpam-5923	204	13	)	)	PUNCT
ejpam-5923	204	14	(	(	PUNCT
ejpam-5923	204	15	−a)k	−a)k	NOUN
ejpam-5923	204	16	4−k	4−k	NUM
ejpam-5923	204	17	;	;	PUNCT
ejpam-5923	204	18	(	(	PUNCT
ejpam-5923	204	19	ii	ii	NOUN
ejpam-5923	204	20	.	.	PUNCT
ejpam-5923	204	21	)	)	PUNCT
ejpam-5923	205	1	e[t	e[t	PROPN
ejpam-5923	205	2	2	2	X
ejpam-5923	205	3	]	]	PUNCT
ejpam-5923	205	4	=	=	SYM
ejpam-5923	205	5	1−λ	1−λ	NUM
ejpam-5923	205	6	3	3	NUM
ejpam-5923	205	7	+	+	NUM
ejpam-5923	205	8	3λ	3λ	NUM
ejpam-5923	205	9	(	(	PUNCT
ejpam-5923	205	10	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	205	11	∑2	∑2	NOUN
ejpam-5923	205	12	k=0	k=0	PROPN
ejpam-5923	205	13	(	(	PUNCT
ejpam-5923	205	14	2	2	NUM
ejpam-5923	205	15	k	k	NOUN
ejpam-5923	205	16	)	)	PUNCT
ejpam-5923	205	17	(	(	PUNCT
ejpam-5923	205	18	−a)k	−a)k	NOUN
ejpam-5923	205	19	5−k	5−k	NUM
ejpam-5923	205	20	;	;	PUNCT
ejpam-5923	205	21	i.	i.	PROPN
ejpam-5923	205	22	a.	a.	PROPN
ejpam-5923	205	23	lakibul	lakibul	PROPN
ejpam-5923	205	24	,	,	PUNCT
ejpam-5923	205	25	d.	d.	PROPN
ejpam-5923	205	26	l.	l.	PROPN
ejpam-5923	205	27	polestico	polestico	PROPN
ejpam-5923	205	28	,	,	PUNCT
ejpam-5923	205	29	a.	a.	PROPN
ejpam-5923	205	30	p.	p.	NOUN
ejpam-5923	205	31	supe	supe	PROPN
ejpam-5923	205	32	/	/	SYM
ejpam-5923	205	33	eur	eur	PROPN
ejpam-5923	205	34	.	.	PUNCT
ejpam-5923	206	1	j.	j.	PROPN
ejpam-5923	206	2	pure	pure	PROPN
ejpam-5923	206	3	appl	appl	PROPN
ejpam-5923	206	4	.	.	PROPN
ejpam-5923	206	5	math	math	PROPN
ejpam-5923	206	6	,	,	PUNCT
ejpam-5923	206	7	18	18	NUM
ejpam-5923	206	8	(	(	PUNCT
ejpam-5923	206	9	2	2	NUM
ejpam-5923	206	10	)	)	PUNCT
ejpam-5923	206	11	(	(	PUNCT
ejpam-5923	206	12	2025	2025	NUM
ejpam-5923	206	13	)	)	PUNCT
ejpam-5923	206	14	,	,	PUNCT
ejpam-5923	206	15	5923	5923	NUM
ejpam-5923	206	16	13	13	NUM
ejpam-5923	206	17	of	of	ADP
ejpam-5923	206	18	21	21	NUM
ejpam-5923	206	19	(	(	PUNCT
ejpam-5923	206	20	iii	iii	NOUN
ejpam-5923	206	21	.	.	PUNCT
ejpam-5923	206	22	)	)	PUNCT
ejpam-5923	207	1	e[t	e[t	X
ejpam-5923	208	1	3	3	X
ejpam-5923	208	2	]	]	X
ejpam-5923	208	3	=	=	SYM
ejpam-5923	208	4	1−λ	1−λ	NUM
ejpam-5923	208	5	4	4	NUM
ejpam-5923	208	6	+	+	X
ejpam-5923	208	7	3λ	3λ	NUM
ejpam-5923	208	8	(	(	PUNCT
ejpam-5923	208	9	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	208	10	∑2	∑2	NOUN
ejpam-5923	208	11	k=0	k=0	PROPN
ejpam-5923	208	12	(	(	PUNCT
ejpam-5923	208	13	2	2	NUM
ejpam-5923	208	14	k	k	NOUN
ejpam-5923	208	15	)	)	PUNCT
ejpam-5923	208	16	(	(	PUNCT
ejpam-5923	208	17	−a)k	−a)k	NOUN
ejpam-5923	208	18	6−k	6−k	NUM
ejpam-5923	208	19	;	;	PUNCT
ejpam-5923	208	20	and	and	CCONJ
ejpam-5923	208	21	(	(	PUNCT
ejpam-5923	208	22	iv	iv	X
ejpam-5923	208	23	.	.	PUNCT
ejpam-5923	208	24	)	)	PUNCT
ejpam-5923	209	1	e[t	e[t	X
ejpam-5923	209	2	4	4	X
ejpam-5923	209	3	]	]	PUNCT
ejpam-5923	209	4	=	=	SYM
ejpam-5923	209	5	1−λ	1−λ	NUM
ejpam-5923	209	6	5	5	NUM
ejpam-5923	209	7	+	+	NUM
ejpam-5923	209	8	3λ	3λ	NUM
ejpam-5923	209	9	(	(	PUNCT
ejpam-5923	209	10	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	209	11	∑2	∑2	NOUN
ejpam-5923	209	12	k=0	k=0	PROPN
ejpam-5923	209	13	(	(	PUNCT
ejpam-5923	209	14	2	2	NUM
ejpam-5923	209	15	k	k	NOUN
ejpam-5923	209	16	)	)	PUNCT
ejpam-5923	209	17	(	(	PUNCT
ejpam-5923	209	18	−a)k	−a)k	NOUN
ejpam-5923	209	19	7−k	7−k	NUM
ejpam-5923	209	20	.	.	PUNCT
ejpam-5923	210	1	the	the	DET
ejpam-5923	210	2	proof	proof	NOUN
ejpam-5923	210	3	is	be	AUX
ejpam-5923	210	4	straight	straight	ADV
ejpam-5923	210	5	forward	forward	ADV
ejpam-5923	210	6	from	from	ADP
ejpam-5923	210	7	the	the	DET
ejpam-5923	210	8	rth	rth	PROPN
ejpam-5923	210	9	moments	moment	NOUN
ejpam-5923	210	10	of	of	ADP
ejpam-5923	210	11	a	a	DET
ejpam-5923	210	12	gesu	gesu	NOUN
ejpam-5923	210	13	distribution	distribution	NOUN
ejpam-5923	210	14	by	by	ADP
ejpam-5923	210	15	taking	take	VERB
ejpam-5923	210	16	r	r	NOUN
ejpam-5923	210	17	=	=	SYM
ejpam-5923	210	18	1	1	NUM
ejpam-5923	210	19	,	,	PUNCT
ejpam-5923	210	20	r	r	NOUN
ejpam-5923	210	21	=	=	SYM
ejpam-5923	210	22	2	2	NUM
ejpam-5923	210	23	,	,	PUNCT
ejpam-5923	210	24	r	r	NOUN
ejpam-5923	210	25	=	=	SYM
ejpam-5923	210	26	3	3	NUM
ejpam-5923	210	27	and	and	CCONJ
ejpam-5923	210	28	r	r	NOUN
ejpam-5923	210	29	=	=	SYM
ejpam-5923	210	30	4	4	NUM
ejpam-5923	210	31	,	,	PUNCT
ejpam-5923	210	32	respectively	respectively	ADV
ejpam-5923	210	33	.	.	PUNCT
ejpam-5923	211	1	these	these	DET
ejpam-5923	211	2	moments	moment	NOUN
ejpam-5923	211	3	are	be	AUX
ejpam-5923	211	4	needed	need	VERB
ejpam-5923	211	5	for	for	ADP
ejpam-5923	211	6	the	the	DET
ejpam-5923	211	7	mean	mean	ADJ
ejpam-5923	211	8	,	,	PUNCT
ejpam-5923	211	9	variance	variance	NOUN
ejpam-5923	211	10	,	,	PUNCT
ejpam-5923	211	11	skewness	skewness	NOUN
ejpam-5923	211	12	and	and	CCONJ
ejpam-5923	211	13	kurtosis	kurtosis	NOUN
ejpam-5923	211	14	of	of	ADP
ejpam-5923	211	15	t	t	PROPN
ejpam-5923	211	16	as	as	SCONJ
ejpam-5923	211	17	given	give	VERB
ejpam-5923	211	18	in	in	ADP
ejpam-5923	211	19	the	the	DET
ejpam-5923	211	20	following	follow	VERB
ejpam-5923	211	21	remark	remark	NOUN
ejpam-5923	211	22	.	.	PUNCT
ejpam-5923	212	1	remark	remark	PROPN
ejpam-5923	212	2	2	2	NUM
ejpam-5923	212	3	.	.	PUNCT
ejpam-5923	213	1	let	let	VERB
ejpam-5923	213	2	t	t	NOUN
ejpam-5923	213	3	be	be	AUX
ejpam-5923	213	4	a	a	DET
ejpam-5923	213	5	random	random	ADJ
ejpam-5923	213	6	variable	variable	NOUN
ejpam-5923	213	7	that	that	PRON
ejpam-5923	213	8	follows	follow	VERB
ejpam-5923	213	9	a	a	DET
ejpam-5923	213	10	gesu	gesu	NOUN
ejpam-5923	213	11	distribution	distribution	NOUN
ejpam-5923	213	12	,	,	PUNCT
ejpam-5923	213	13	then	then	ADV
ejpam-5923	213	14	(	(	PUNCT
ejpam-5923	213	15	i.	i.	PROPN
ejpam-5923	213	16	)	)	PUNCT
ejpam-5923	213	17	the	the	DET
ejpam-5923	213	18	mean	mean	NOUN
ejpam-5923	213	19	of	of	ADP
ejpam-5923	213	20	t	t	PROPN
ejpam-5923	213	21	is	be	AUX
ejpam-5923	213	22	given	give	VERB
ejpam-5923	213	23	by	by	ADP
ejpam-5923	213	24	e[t	e[t	NOUN
ejpam-5923	213	25	]	]	PUNCT
ejpam-5923	214	1	=	=	PUNCT
ejpam-5923	214	2	1−	1−	NUM
ejpam-5923	214	3	λ	λ	SYM
ejpam-5923	214	4	2	2	NUM
ejpam-5923	214	5	+	+	NUM
ejpam-5923	214	6	3λ	3λ	NUM
ejpam-5923	214	7	(	(	PUNCT
ejpam-5923	214	8	1−	1−	NUM
ejpam-5923	214	9	a)3	a)3	ADJ
ejpam-5923	214	10	+	+	NUM
ejpam-5923	214	11	a3	a3	NOUN
ejpam-5923	214	12	2∑	2∑	NUM
ejpam-5923	214	13	k=0	k=0	X
ejpam-5923	214	14	(	(	PUNCT
ejpam-5923	214	15	2	2	NUM
ejpam-5923	214	16	k	k	NOUN
ejpam-5923	214	17	)	)	PUNCT
ejpam-5923	214	18	(	(	PUNCT
ejpam-5923	214	19	−a)k	−a)k	NOUN
ejpam-5923	214	20	4−	4−	PROPN
ejpam-5923	215	1	k	k	NOUN
ejpam-5923	215	2	;	;	PUNCT
ejpam-5923	215	3	(	(	PUNCT
ejpam-5923	215	4	ii	ii	NOUN
ejpam-5923	215	5	.	.	PUNCT
ejpam-5923	215	6	)	)	PUNCT
ejpam-5923	216	1	the	the	DET
ejpam-5923	216	2	variance	variance	NOUN
ejpam-5923	216	3	of	of	ADP
ejpam-5923	216	4	t	t	PROPN
ejpam-5923	216	5	is	be	AUX
ejpam-5923	216	6	given	give	VERB
ejpam-5923	216	7	by	by	ADP
ejpam-5923	216	8	v	v	NUM
ejpam-5923	216	9	ar(t	ar(t	NOUN
ejpam-5923	216	10	)	)	PUNCT
ejpam-5923	217	1	=	=	PRON
ejpam-5923	217	2	e[t	e[t	ADJ
ejpam-5923	217	3	2]−	2]−	NUM
ejpam-5923	217	4	(	(	PUNCT
ejpam-5923	217	5	e[t	e[t	X
ejpam-5923	217	6	]	]	X
ejpam-5923	217	7	)	)	PUNCT
ejpam-5923	217	8	2	2	NUM
ejpam-5923	217	9	=	=	SYM
ejpam-5923	217	10	1−	1−	NUM
ejpam-5923	217	11	λ	λ	NOUN
ejpam-5923	217	12	3	3	NUM
ejpam-5923	217	13	+	+	NUM
ejpam-5923	217	14	3λ	3λ	NUM
ejpam-5923	217	15	(	(	PUNCT
ejpam-5923	217	16	1−	1−	NUM
ejpam-5923	217	17	a)3	a)3	ADJ
ejpam-5923	217	18	+	+	NUM
ejpam-5923	217	19	a3	a3	NOUN
ejpam-5923	217	20	2∑	2∑	NUM
ejpam-5923	217	21	k=0	k=0	X
ejpam-5923	217	22	(	(	PUNCT
ejpam-5923	217	23	2	2	NUM
ejpam-5923	217	24	k	k	NOUN
ejpam-5923	217	25	)	)	PUNCT
ejpam-5923	217	26	(	(	PUNCT
ejpam-5923	217	27	−a)k	−a)k	NOUN
ejpam-5923	217	28	5−	5−	NUM
ejpam-5923	217	29	k	k	NOUN
ejpam-5923	217	30	−	−	PROPN
ejpam-5923	217	31	[	[	PUNCT
ejpam-5923	217	32	1−	1−	NUM
ejpam-5923	217	33	λ	λ	SYM
ejpam-5923	217	34	2	2	NUM
ejpam-5923	218	1	+	+	NUM
ejpam-5923	218	2	3λ	3λ	NUM
ejpam-5923	218	3	(	(	PUNCT
ejpam-5923	218	4	1−	1−	NUM
ejpam-5923	218	5	a)3	a)3	ADJ
ejpam-5923	218	6	+	+	NUM
ejpam-5923	218	7	a3	a3	NOUN
ejpam-5923	218	8	2∑	2∑	NUM
ejpam-5923	218	9	k=0	k=0	X
ejpam-5923	218	10	(	(	PUNCT
ejpam-5923	218	11	2	2	NUM
ejpam-5923	218	12	k	k	NOUN
ejpam-5923	218	13	)	)	PUNCT
ejpam-5923	218	14	(	(	PUNCT
ejpam-5923	218	15	−a)k	−a)k	NOUN
ejpam-5923	218	16	4−	4−	PROPN
ejpam-5923	219	1	k	k	X
ejpam-5923	219	2	]	]	X
ejpam-5923	219	3	2	2	NUM
ejpam-5923	219	4	;	;	PUNCT
ejpam-5923	219	5	(	(	PUNCT
ejpam-5923	219	6	iii	iii	NOUN
ejpam-5923	219	7	.	.	PUNCT
ejpam-5923	219	8	)	)	PUNCT
ejpam-5923	220	1	the	the	DET
ejpam-5923	220	2	skewness	skewness	NOUN
ejpam-5923	220	3	of	of	ADP
ejpam-5923	220	4	t	t	PROPN
ejpam-5923	220	5	,	,	PUNCT
ejpam-5923	220	6	denoted	denote	VERB
ejpam-5923	220	7	by	by	ADP
ejpam-5923	220	8	β2	β2	PROPN
ejpam-5923	220	9	,	,	PUNCT
ejpam-5923	220	10	is	be	AUX
ejpam-5923	220	11	given	give	VERB
ejpam-5923	220	12	by	by	ADP
ejpam-5923	220	13	β2	β2	PROPN
ejpam-5923	220	14	=	=	SYM
ejpam-5923	220	15	e[t	e[t	PROPN
ejpam-5923	220	16	3]−	3]−	NUM
ejpam-5923	220	17	3e[t	3e[t	NUM
ejpam-5923	220	18	2]e[t	2]e[t	NUM
ejpam-5923	220	19	]	]	PUNCT
ejpam-5923	221	1	+	+	CCONJ
ejpam-5923	221	2	2	2	NUM
ejpam-5923	221	3	(	(	PUNCT
ejpam-5923	221	4	e[t	e[t	X
ejpam-5923	221	5	]	]	X
ejpam-5923	221	6	)	)	PUNCT
ejpam-5923	221	7	3	3	NUM
ejpam-5923	221	8	(	(	PUNCT
ejpam-5923	221	9	v	v	NOUN
ejpam-5923	221	10	ar(t	ar(t	NOUN
ejpam-5923	221	11	)	)	PUNCT
ejpam-5923	221	12	)	)	PUNCT
ejpam-5923	221	13	3	3	NUM
ejpam-5923	221	14	2	2	NUM
ejpam-5923	221	15	,	,	PUNCT
ejpam-5923	221	16	where	where	SCONJ
ejpam-5923	221	17	e[t	e[t	PROPN
ejpam-5923	221	18	3	3	X
ejpam-5923	221	19	]	]	X
ejpam-5923	221	20	=	=	SYM
ejpam-5923	221	21	1−λ	1−λ	NUM
ejpam-5923	221	22	4	4	NUM
ejpam-5923	221	23	+	+	X
ejpam-5923	221	24	3λ	3λ	NUM
ejpam-5923	221	25	(	(	PUNCT
ejpam-5923	221	26	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	221	27	∑2	∑2	NOUN
ejpam-5923	221	28	k=0	k=0	PROPN
ejpam-5923	221	29	(	(	PUNCT
ejpam-5923	221	30	2	2	NUM
ejpam-5923	221	31	k	k	NOUN
ejpam-5923	221	32	)	)	PUNCT
ejpam-5923	221	33	(	(	PUNCT
ejpam-5923	221	34	−a)k	−a)k	NOUN
ejpam-5923	221	35	6−k	6−k	NUM
ejpam-5923	221	36	;	;	PUNCT
ejpam-5923	221	37	and	and	CCONJ
ejpam-5923	221	38	(	(	PUNCT
ejpam-5923	221	39	iii	iii	NOUN
ejpam-5923	221	40	.	.	PUNCT
ejpam-5923	221	41	)	)	PUNCT
ejpam-5923	222	1	the	the	DET
ejpam-5923	222	2	kurtosis	kurtosis	NOUN
ejpam-5923	222	3	of	of	ADP
ejpam-5923	222	4	t	t	PROPN
ejpam-5923	222	5	,	,	PUNCT
ejpam-5923	222	6	denoted	denote	VERB
ejpam-5923	222	7	by	by	ADP
ejpam-5923	222	8	κ	κ	PROPN
ejpam-5923	222	9	,	,	PUNCT
ejpam-5923	222	10	is	be	AUX
ejpam-5923	222	11	given	give	VERB
ejpam-5923	222	12	by	by	ADP
ejpam-5923	222	13	κ	κ	X
ejpam-5923	222	14	=	=	SYM
ejpam-5923	222	15	e[t	e[t	PROPN
ejpam-5923	222	16	4]−	4]−	NUM
ejpam-5923	222	17	4e[t	4e[t	NUM
ejpam-5923	222	18	]	]	PUNCT
ejpam-5923	222	19	e[t	e[t	X
ejpam-5923	222	20	3	3	NUM
ejpam-5923	222	21	]	]	PUNCT
ejpam-5923	222	22	+	+	CCONJ
ejpam-5923	222	23	6(e[t	6(e[t	NUM
ejpam-5923	222	24	]	]	SYM
ejpam-5923	222	25	)	)	PUNCT
ejpam-5923	222	26	2e[t	2e[t	NUM
ejpam-5923	222	27	2]−	2]−	NUM
ejpam-5923	222	28	3(e[t	3(e[t	NUM
ejpam-5923	222	29	]	]	X
ejpam-5923	222	30	)	)	PUNCT
ejpam-5923	222	31	4	4	NUM
ejpam-5923	222	32	(	(	PUNCT
ejpam-5923	222	33	v	v	NOUN
ejpam-5923	222	34	ar(t	ar(t	NOUN
ejpam-5923	222	35	)	)	PUNCT
ejpam-5923	222	36	)	)	PUNCT
ejpam-5923	222	37	2	2	NUM
ejpam-5923	222	38	,	,	PUNCT
ejpam-5923	222	39	where	where	SCONJ
ejpam-5923	222	40	e[t	e[t	PROPN
ejpam-5923	222	41	4	4	X
ejpam-5923	222	42	]	]	X
ejpam-5923	222	43	=	=	SYM
ejpam-5923	222	44	1−λ	1−λ	NUM
ejpam-5923	222	45	5	5	NUM
ejpam-5923	222	46	+	+	NUM
ejpam-5923	222	47	3λ	3λ	NUM
ejpam-5923	222	48	(	(	PUNCT
ejpam-5923	222	49	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	222	50	∑2	∑2	NOUN
ejpam-5923	222	51	k=0	k=0	PROPN
ejpam-5923	222	52	(	(	PUNCT
ejpam-5923	222	53	2	2	NUM
ejpam-5923	222	54	k	k	NOUN
ejpam-5923	222	55	)	)	PUNCT
ejpam-5923	222	56	(	(	PUNCT
ejpam-5923	222	57	−a)k	−a)k	NOUN
ejpam-5923	222	58	7−k	7−k	NUM
ejpam-5923	222	59	.	.	PUNCT
ejpam-5923	223	1	theorem	theorem	NOUN
ejpam-5923	223	2	3	3	X
ejpam-5923	223	3	.	.	PUNCT
ejpam-5923	224	1	let	let	VERB
ejpam-5923	224	2	t	t	PROPN
ejpam-5923	224	3	be	be	AUX
ejpam-5923	224	4	a	a	DET
ejpam-5923	224	5	random	random	ADJ
ejpam-5923	224	6	variable	variable	NOUN
ejpam-5923	224	7	that	that	PRON
ejpam-5923	224	8	follows	follow	VERB
ejpam-5923	224	9	a	a	DET
ejpam-5923	224	10	gesu	gesu	NOUN
ejpam-5923	224	11	distribution	distribution	NOUN
ejpam-5923	224	12	,	,	PUNCT
ejpam-5923	224	13	then	then	ADV
ejpam-5923	224	14	the	the	DET
ejpam-5923	224	15	moment	moment	NOUN
ejpam-5923	224	16	-	-	PUNCT
ejpam-5923	224	17	generating	generate	VERB
ejpam-5923	224	18	function	function	NOUN
ejpam-5923	224	19	of	of	ADP
ejpam-5923	224	20	t	t	PROPN
ejpam-5923	224	21	is	be	AUX
ejpam-5923	224	22	given	give	VERB
ejpam-5923	224	23	by	by	ADP
ejpam-5923	224	24	e[est	e[	ADJ
ejpam-5923	224	25	]	]	PUNCT
ejpam-5923	225	1	=	=	PUNCT
ejpam-5923	225	2	∞∑	∞∑	NUM
ejpam-5923	225	3	r=0	r=0	PROPN
ejpam-5923	225	4	sr	sr	PROPN
ejpam-5923	225	5	r	r	NOUN
ejpam-5923	225	6	!	!	PUNCT
ejpam-5923	226	1	[	[	PUNCT
ejpam-5923	226	2	1−	1−	NUM
ejpam-5923	226	3	λ	λ	NOUN
ejpam-5923	226	4	r	r	NOUN
ejpam-5923	226	5	+	+	NOUN
ejpam-5923	226	6	1	1	NUM
ejpam-5923	226	7	+	+	X
ejpam-5923	226	8	3λ	3λ	NUM
ejpam-5923	226	9	(	(	PUNCT
ejpam-5923	226	10	1−	1−	NUM
ejpam-5923	226	11	a)3	a)3	ADJ
ejpam-5923	226	12	+	+	NUM
ejpam-5923	226	13	a3	a3	NOUN
ejpam-5923	226	14	2∑	2∑	NUM
ejpam-5923	226	15	k=0	k=0	X
ejpam-5923	226	16	(	(	PUNCT
ejpam-5923	226	17	2	2	NUM
ejpam-5923	226	18	k	k	NOUN
ejpam-5923	226	19	)	)	PUNCT
ejpam-5923	226	20	(	(	PUNCT
ejpam-5923	226	21	−a)k	−a)k	NOUN
ejpam-5923	226	22	r	r	NOUN
ejpam-5923	226	23	−	−	PROPN
ejpam-5923	226	24	k	k	NOUN
ejpam-5923	227	1	+	+	PROPN
ejpam-5923	227	2	3	3	NUM
ejpam-5923	227	3	]	]	PUNCT
ejpam-5923	227	4	.	.	PUNCT
ejpam-5923	228	1	i.	i.	PROPN
ejpam-5923	228	2	a.	a.	PROPN
ejpam-5923	228	3	lakibul	lakibul	PROPN
ejpam-5923	228	4	,	,	PUNCT
ejpam-5923	228	5	d.	d.	PROPN
ejpam-5923	228	6	l.	l.	PROPN
ejpam-5923	228	7	polestico	polestico	PROPN
ejpam-5923	228	8	,	,	PUNCT
ejpam-5923	228	9	a.	a.	PROPN
ejpam-5923	228	10	p.	p.	NOUN
ejpam-5923	228	11	supe	supe	PROPN
ejpam-5923	228	12	/	/	SYM
ejpam-5923	228	13	eur	eur	PROPN
ejpam-5923	228	14	.	.	PUNCT
ejpam-5923	229	1	j.	j.	PROPN
ejpam-5923	229	2	pure	pure	PROPN
ejpam-5923	229	3	appl	appl	PROPN
ejpam-5923	229	4	.	.	PROPN
ejpam-5923	229	5	math	math	PROPN
ejpam-5923	229	6	,	,	PUNCT
ejpam-5923	229	7	18	18	NUM
ejpam-5923	229	8	(	(	PUNCT
ejpam-5923	229	9	2	2	NUM
ejpam-5923	229	10	)	)	PUNCT
ejpam-5923	229	11	(	(	PUNCT
ejpam-5923	229	12	2025	2025	NUM
ejpam-5923	229	13	)	)	PUNCT
ejpam-5923	229	14	,	,	PUNCT
ejpam-5923	229	15	5923	5923	NUM
ejpam-5923	229	16	14	14	NUM
ejpam-5923	229	17	of	of	ADP
ejpam-5923	229	18	21	21	NUM
ejpam-5923	229	19	proof	proof	NOUN
ejpam-5923	229	20	.	.	PUNCT
ejpam-5923	230	1	by	by	ADP
ejpam-5923	230	2	definition	definition	NOUN
ejpam-5923	230	3	of	of	ADP
ejpam-5923	230	4	moment	moment	NOUN
ejpam-5923	230	5	generating	generate	VERB
ejpam-5923	230	6	function	function	NOUN
ejpam-5923	230	7	,	,	PUNCT
ejpam-5923	230	8	we	we	PRON
ejpam-5923	230	9	have	have	VERB
ejpam-5923	230	10	e[est	e[	ADJ
ejpam-5923	230	11	]	]	PUNCT
ejpam-5923	231	1	=	=	SYM
ejpam-5923	231	2	∫	∫	PROPN
ejpam-5923	231	3	1	1	NUM
ejpam-5923	231	4	0	0	NUM
ejpam-5923	231	5	estf(t)dt	estf(t)dt	NOUN
ejpam-5923	231	6	.	.	PUNCT
ejpam-5923	232	1	now	now	ADV
ejpam-5923	232	2	,	,	PUNCT
ejpam-5923	232	3	since	since	SCONJ
ejpam-5923	232	4	est	est	X
ejpam-5923	232	5	=	=	SYM
ejpam-5923	232	6	∞∑	∞∑	NUM
ejpam-5923	232	7	r=0	r=0	PROPN
ejpam-5923	232	8	sr	sr	PROPN
ejpam-5923	232	9	r	r	NOUN
ejpam-5923	232	10	!	!	PUNCT
ejpam-5923	232	11	tr	tr	VERB
ejpam-5923	232	12	,	,	PUNCT
ejpam-5923	232	13	it	it	PRON
ejpam-5923	232	14	follows	follow	VERB
ejpam-5923	232	15	that	that	PRON
ejpam-5923	232	16	e[est	e[	ADJ
ejpam-5923	232	17	]	]	PUNCT
ejpam-5923	232	18	=	=	PUNCT
ejpam-5923	233	1	∞∑	∞∑	NUM
ejpam-5923	233	2	r=0	r=0	PROPN
ejpam-5923	233	3	sr	sr	PROPN
ejpam-5923	233	4	r	r	NOUN
ejpam-5923	233	5	!	!	PUNCT
ejpam-5923	233	6	e[t	e[t	PUNCT
ejpam-5923	234	1	r	r	NOUN
ejpam-5923	234	2	]	]	PUNCT
ejpam-5923	234	3	.	.	PUNCT
ejpam-5923	235	1	using	use	VERB
ejpam-5923	235	2	the	the	DET
ejpam-5923	235	3	rth	rth	ADJ
ejpam-5923	235	4	moment	moment	NOUN
ejpam-5923	235	5	of	of	ADP
ejpam-5923	235	6	t	t	PROPN
ejpam-5923	235	7	,	,	PUNCT
ejpam-5923	235	8	we	we	PRON
ejpam-5923	235	9	get	get	VERB
ejpam-5923	235	10	e[est	e[	ADJ
ejpam-5923	235	11	]	]	PUNCT
ejpam-5923	236	1	=	=	PUNCT
ejpam-5923	236	2	∞∑	∞∑	NUM
ejpam-5923	236	3	r=0	r=0	PROPN
ejpam-5923	236	4	sr	sr	PROPN
ejpam-5923	236	5	r	r	NOUN
ejpam-5923	236	6	!	!	PUNCT
ejpam-5923	237	1	[	[	PUNCT
ejpam-5923	237	2	1−	1−	NUM
ejpam-5923	237	3	λ	λ	NOUN
ejpam-5923	237	4	r	r	NOUN
ejpam-5923	237	5	+	+	NOUN
ejpam-5923	237	6	1	1	NUM
ejpam-5923	237	7	+	+	X
ejpam-5923	237	8	3λ	3λ	NUM
ejpam-5923	237	9	(	(	PUNCT
ejpam-5923	237	10	1−	1−	NUM
ejpam-5923	237	11	a)3	a)3	ADJ
ejpam-5923	237	12	+	+	NUM
ejpam-5923	237	13	a3	a3	NOUN
ejpam-5923	237	14	2∑	2∑	NUM
ejpam-5923	237	15	k=0	k=0	X
ejpam-5923	237	16	(	(	PUNCT
ejpam-5923	237	17	2	2	NUM
ejpam-5923	237	18	k	k	NOUN
ejpam-5923	237	19	)	)	PUNCT
ejpam-5923	237	20	(	(	PUNCT
ejpam-5923	237	21	−a)k	−a)k	NOUN
ejpam-5923	237	22	r	r	NOUN
ejpam-5923	237	23	−	−	PROPN
ejpam-5923	237	24	k	k	NOUN
ejpam-5923	238	1	+	+	PROPN
ejpam-5923	238	2	3	3	NUM
ejpam-5923	238	3	]	]	PUNCT
ejpam-5923	238	4	.	.	PUNCT
ejpam-5923	239	1	4	4	X
ejpam-5923	239	2	.	.	X
ejpam-5923	239	3	maximum	maximum	ADJ
ejpam-5923	239	4	likelihood	likelihood	NOUN
ejpam-5923	239	5	estimation	estimation	NOUN
ejpam-5923	239	6	let	let	VERB
ejpam-5923	239	7	x1,x2,	x1,x2,	PROPN
ejpam-5923	239	8	...	...	PUNCT
ejpam-5923	239	9	,xn	,xn	PUNCT
ejpam-5923	239	10	be	be	AUX
ejpam-5923	239	11	a	a	DET
ejpam-5923	239	12	random	random	ADJ
ejpam-5923	239	13	sample	sample	NOUN
ejpam-5923	239	14	of	of	ADP
ejpam-5923	239	15	size	size	NOUN
ejpam-5923	239	16	n	n	CCONJ
ejpam-5923	239	17	from	from	ADP
ejpam-5923	239	18	a	a	DET
ejpam-5923	239	19	generalized	generalize	VERB
ejpam-5923	239	20	extended	extend	VERB
ejpam-5923	239	21	standard	standard	ADJ
ejpam-5923	239	22	u	u	NOUN
ejpam-5923	239	23	-	-	ADJ
ejpam-5923	239	24	quadratic	quadratic	ADJ
ejpam-5923	239	25	(	(	PUNCT
ejpam-5923	239	26	gesu	gesu	NOUN
ejpam-5923	239	27	)	)	PUNCT
ejpam-5923	239	28	distribution	distribution	NOUN
ejpam-5923	239	29	.	.	PUNCT
ejpam-5923	240	1	then	then	ADV
ejpam-5923	240	2	the	the	DET
ejpam-5923	240	3	likelihood	likelihood	NOUN
ejpam-5923	240	4	function	function	NOUN
ejpam-5923	240	5	is	be	AUX
ejpam-5923	240	6	defined	define	VERB
ejpam-5923	240	7	by	by	ADP
ejpam-5923	240	8	l	l	NOUN
ejpam-5923	240	9	=	=	PUNCT
ejpam-5923	240	10	n∏	n∏	PROPN
ejpam-5923	240	11	i=1	i=1	X
ejpam-5923	241	1	[	[	PUNCT
ejpam-5923	241	2	1−	1−	NUM
ejpam-5923	241	3	λ+	λ+	PUNCT
ejpam-5923	241	4	3λ	3λ	NUM
ejpam-5923	241	5	(	(	PUNCT
ejpam-5923	241	6	1−	1−	NUM
ejpam-5923	241	7	a)3	a)3	ADJ
ejpam-5923	241	8	+	+	NUM
ejpam-5923	241	9	a3	a3	NOUN
ejpam-5923	241	10	(	(	PUNCT
ejpam-5923	241	11	ti	ti	NOUN
ejpam-5923	241	12	−	−	PROPN
ejpam-5923	241	13	a)2	a)2	PROPN
ejpam-5923	241	14	]	]	PUNCT
ejpam-5923	241	15	,	,	PUNCT
ejpam-5923	241	16	with	with	ADP
ejpam-5923	241	17	its	its	PRON
ejpam-5923	241	18	log	log	NOUN
ejpam-5923	241	19	-	-	PUNCT
ejpam-5923	241	20	likelihood	likelihood	NOUN
ejpam-5923	241	21	function	function	NOUN
ejpam-5923	241	22	is	be	AUX
ejpam-5923	241	23	given	give	VERB
ejpam-5923	241	24	by	by	ADP
ejpam-5923	241	25	logl	logl	NOUN
ejpam-5923	241	26	=	=	SYM
ejpam-5923	241	27	n∑	n∑	PROPN
ejpam-5923	241	28	i=1	i=1	PROPN
ejpam-5923	241	29	log	log	PROPN
ejpam-5923	241	30	[	[	PUNCT
ejpam-5923	241	31	1−	1−	NUM
ejpam-5923	241	32	λ+	λ+	PUNCT
ejpam-5923	241	33	3λ	3λ	NUM
ejpam-5923	241	34	(	(	PUNCT
ejpam-5923	241	35	1−	1−	NUM
ejpam-5923	241	36	a)3	a)3	ADJ
ejpam-5923	241	37	+	+	NUM
ejpam-5923	241	38	a3	a3	NOUN
ejpam-5923	241	39	(	(	PUNCT
ejpam-5923	241	40	ti	ti	NOUN
ejpam-5923	241	41	−	−	PROPN
ejpam-5923	241	42	a)2	a)2	PROPN
ejpam-5923	241	43	]	]	PUNCT
ejpam-5923	241	44	.	.	PUNCT
ejpam-5923	242	1	the	the	DET
ejpam-5923	242	2	partial	partial	ADJ
ejpam-5923	242	3	derivative	derivative	NOUN
ejpam-5923	242	4	of	of	ADP
ejpam-5923	242	5	logl	logl	NOUN
ejpam-5923	242	6	with	with	ADP
ejpam-5923	242	7	respect	respect	NOUN
ejpam-5923	242	8	to	to	ADP
ejpam-5923	242	9	the	the	DET
ejpam-5923	242	10	parameters	parameter	NOUN
ejpam-5923	242	11	λ	λ	PROPN
ejpam-5923	242	12	and	and	CCONJ
ejpam-5923	242	13	a	a	PRON
ejpam-5923	242	14	are	be	AUX
ejpam-5923	242	15	given	give	VERB
ejpam-5923	242	16	by	by	ADP
ejpam-5923	242	17	∂	∂	NUM
ejpam-5923	242	18	logl	logl	NOUN
ejpam-5923	242	19	∂λ	∂λ	PROPN
ejpam-5923	242	20	=	=	SYM
ejpam-5923	242	21	n∑	n∑	PROPN
ejpam-5923	242	22	i=1	i=1	PROPN
ejpam-5923	242	23	3	3	NUM
ejpam-5923	242	24	(	(	PUNCT
ejpam-5923	242	25	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	242	26	(	(	PUNCT
ejpam-5923	242	27	ti	ti	NOUN
ejpam-5923	242	28	−	−	PROPN
ejpam-5923	242	29	a)2	a)2	NOUN
ejpam-5923	242	30	−	−	PROPN
ejpam-5923	242	31	1	1	NUM
ejpam-5923	242	32	1−	1−	NUM
ejpam-5923	242	33	λ+	λ+	PUNCT
ejpam-5923	242	34	3λ	3λ	NUM
ejpam-5923	242	35	(	(	PUNCT
ejpam-5923	242	36	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	242	37	(	(	PUNCT
ejpam-5923	242	38	ti	ti	NOUN
ejpam-5923	242	39	−	−	PROPN
ejpam-5923	242	40	a)2	a)2	PROPN
ejpam-5923	242	41	,	,	PUNCT
ejpam-5923	242	42	and	and	CCONJ
ejpam-5923	242	43	∂	∂	NUM
ejpam-5923	242	44	logl	logl	NOUN
ejpam-5923	242	45	∂a	∂a	NOUN
ejpam-5923	242	46	=	=	PUNCT
ejpam-5923	242	47	n∑	n∑	PROPN
ejpam-5923	242	48	i=1	i=1	PROPN
ejpam-5923	242	49	3λ(ti	3λ(ti	NUM
ejpam-5923	242	50	−	−	NOUN
ejpam-5923	242	51	a	a	NOUN
ejpam-5923	242	52	)	)	PUNCT
ejpam-5923	242	53	[	[	PUNCT
ejpam-5923	242	54	(	(	PUNCT
ejpam-5923	242	55	1−	1−	NUM
ejpam-5923	242	56	a)3	a)3	ADJ
ejpam-5923	242	57	+	+	NUM
ejpam-5923	242	58	a3	a3	NOUN
ejpam-5923	242	59	]	]	X
ejpam-5923	242	60	−2	−2	NOUN
ejpam-5923	242	61	{	{	PUNCT
ejpam-5923	242	62	3(ti	3(ti	NOUN
ejpam-5923	242	63	−	−	PROPN
ejpam-5923	242	64	a	a	NOUN
ejpam-5923	242	65	)	)	PUNCT
ejpam-5923	242	66	[	[	PUNCT
ejpam-5923	242	67	(	(	PUNCT
ejpam-5923	242	68	1−	1−	NUM
ejpam-5923	242	69	a)2	a)2	PROPN
ejpam-5923	242	70	−	−	PROPN
ejpam-5923	242	71	a2	a2	PROPN
ejpam-5923	242	72	]	]	PUNCT
ejpam-5923	242	73	−	−	PROPN
ejpam-5923	242	74	2	2	NUM
ejpam-5923	242	75	[	[	PUNCT
ejpam-5923	242	76	(	(	PUNCT
ejpam-5923	242	77	1−	1−	NUM
ejpam-5923	242	78	a)3	a)3	ADJ
ejpam-5923	242	79	+	+	NUM
ejpam-5923	242	80	a3	a3	NOUN
ejpam-5923	242	81	]	]	PUNCT
ejpam-5923	242	82	}	}	PUNCT
ejpam-5923	242	83	1−	1−	NUM
ejpam-5923	242	84	λ+	λ+	PUNCT
ejpam-5923	242	85	3λ	3λ	NUM
ejpam-5923	242	86	(	(	PUNCT
ejpam-5923	242	87	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	242	88	(	(	PUNCT
ejpam-5923	242	89	ti	ti	NOUN
ejpam-5923	242	90	−	−	PROPN
ejpam-5923	242	91	a)2	a)2	PROPN
ejpam-5923	242	92	.	.	PUNCT
ejpam-5923	243	1	i.	i.	PROPN
ejpam-5923	243	2	a.	a.	PROPN
ejpam-5923	243	3	lakibul	lakibul	PROPN
ejpam-5923	243	4	,	,	PUNCT
ejpam-5923	243	5	d.	d.	PROPN
ejpam-5923	243	6	l.	l.	PROPN
ejpam-5923	243	7	polestico	polestico	PROPN
ejpam-5923	243	8	,	,	PUNCT
ejpam-5923	243	9	a.	a.	PROPN
ejpam-5923	243	10	p.	p.	NOUN
ejpam-5923	243	11	supe	supe	PROPN
ejpam-5923	243	12	/	/	SYM
ejpam-5923	243	13	eur	eur	PROPN
ejpam-5923	243	14	.	.	PUNCT
ejpam-5923	244	1	j.	j.	PROPN
ejpam-5923	244	2	pure	pure	PROPN
ejpam-5923	244	3	appl	appl	PROPN
ejpam-5923	244	4	.	.	PROPN
ejpam-5923	244	5	math	math	PROPN
ejpam-5923	244	6	,	,	PUNCT
ejpam-5923	244	7	18	18	NUM
ejpam-5923	244	8	(	(	PUNCT
ejpam-5923	244	9	2	2	NUM
ejpam-5923	244	10	)	)	PUNCT
ejpam-5923	244	11	(	(	PUNCT
ejpam-5923	244	12	2025	2025	NUM
ejpam-5923	244	13	)	)	PUNCT
ejpam-5923	244	14	,	,	PUNCT
ejpam-5923	244	15	5923	5923	NUM
ejpam-5923	244	16	15	15	NUM
ejpam-5923	244	17	of	of	ADP
ejpam-5923	244	18	21	21	NUM
ejpam-5923	244	19	remark	remark	NOUN
ejpam-5923	244	20	3	3	NUM
ejpam-5923	244	21	.	.	PUNCT
ejpam-5923	245	1	the	the	DET
ejpam-5923	245	2	maximum	maximum	ADJ
ejpam-5923	245	3	likelihood	likelihood	NOUN
ejpam-5923	245	4	estimates	estimate	NOUN
ejpam-5923	245	5	of	of	ADP
ejpam-5923	245	6	λ	λ	PROPN
ejpam-5923	245	7	and	and	CCONJ
ejpam-5923	245	8	a	a	PRON
ejpam-5923	245	9	are	be	AUX
ejpam-5923	245	10	obtained	obtain	VERB
ejpam-5923	245	11	by	by	ADP
ejpam-5923	245	12	solving	solve	VERB
ejpam-5923	245	13	the	the	DET
ejpam-5923	245	14	system	system	NOUN
ejpam-5923	245	15	of	of	ADP
ejpam-5923	245	16	two	two	NUM
ejpam-5923	245	17	score	score	NOUN
ejpam-5923	245	18	equations	equation	NOUN
ejpam-5923	245	19	given	give	VERB
ejpam-5923	245	20	as	as	ADP
ejpam-5923	245	21	follows:	follows:	PROPN
ejpam-5923	245	22	n∑	n∑	NOUN
ejpam-5923	245	23	i=1	i=1	PROPN
ejpam-5923	245	24	3	3	NUM
ejpam-5923	245	25	(	(	PUNCT
ejpam-5923	245	26	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	245	27	(	(	PUNCT
ejpam-5923	245	28	ti	ti	NOUN
ejpam-5923	245	29	−	−	PROPN
ejpam-5923	245	30	a)2	a)2	NOUN
ejpam-5923	245	31	−	−	PROPN
ejpam-5923	245	32	1	1	NUM
ejpam-5923	245	33	1−	1−	NUM
ejpam-5923	245	34	λ+	λ+	PUNCT
ejpam-5923	245	35	3λ	3λ	NUM
ejpam-5923	245	36	(	(	PUNCT
ejpam-5923	245	37	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	245	38	(	(	PUNCT
ejpam-5923	245	39	ti	ti	NOUN
ejpam-5923	245	40	−	−	PROPN
ejpam-5923	245	41	a)2	a)2	NOUN
ejpam-5923	245	42	=	=	SYM
ejpam-5923	245	43	0	0	NUM
ejpam-5923	245	44	n∑	n∑	NOUN
ejpam-5923	245	45	i=1	i=1	PROPN
ejpam-5923	246	1	3λ(ti	3λ(ti	NUM
ejpam-5923	246	2	−	−	NOUN
ejpam-5923	246	3	a	a	NOUN
ejpam-5923	246	4	)	)	PUNCT
ejpam-5923	247	1	[	[	X
ejpam-5923	247	2	(	(	PUNCT
ejpam-5923	247	3	1−	1−	NUM
ejpam-5923	247	4	a)3	a)3	ADJ
ejpam-5923	247	5	+	+	NUM
ejpam-5923	247	6	a3	a3	NOUN
ejpam-5923	247	7	]	]	X
ejpam-5923	247	8	−2	−2	NOUN
ejpam-5923	247	9	{	{	PUNCT
ejpam-5923	247	10	3(ti	3(ti	NOUN
ejpam-5923	247	11	−	−	PROPN
ejpam-5923	247	12	a	a	NOUN
ejpam-5923	247	13	)	)	PUNCT
ejpam-5923	248	1	[	[	X
ejpam-5923	248	2	(	(	PUNCT
ejpam-5923	248	3	1−	1−	NUM
ejpam-5923	248	4	a)2	a)2	NOUN
ejpam-5923	248	5	−	−	NOUN
ejpam-5923	248	6	a2]−	a2]−	ADJ
ejpam-5923	248	7	2	2	NUM
ejpam-5923	248	8	[	[	X
ejpam-5923	248	9	(	(	PUNCT
ejpam-5923	248	10	1−	1−	NUM
ejpam-5923	248	11	a)3	a)3	ADJ
ejpam-5923	248	12	+	+	NUM
ejpam-5923	248	13	a3	a3	NOUN
ejpam-5923	248	14	]	]	PUNCT
ejpam-5923	248	15	}	}	PUNCT
ejpam-5923	248	16	1−	1−	NUM
ejpam-5923	248	17	λ+	λ+	PUNCT
ejpam-5923	248	18	3λ	3λ	NUM
ejpam-5923	248	19	(	(	PUNCT
ejpam-5923	248	20	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	248	21	(	(	PUNCT
ejpam-5923	248	22	ti	ti	NOUN
ejpam-5923	248	23	−	−	PROPN
ejpam-5923	248	24	a)2	a)2	NOUN
ejpam-5923	248	25	=	=	NOUN
ejpam-5923	248	26	0	0	NUM
ejpam-5923	248	27	.	.	NOUN
ejpam-5923	248	28	5	5	NUM
ejpam-5923	248	29	.	.	X
ejpam-5923	248	30	random	random	ADJ
ejpam-5923	248	31	number	number	NOUN
ejpam-5923	248	32	generation	generation	NOUN
ejpam-5923	248	33	and	and	CCONJ
ejpam-5923	248	34	median	median	NOUN
ejpam-5923	248	35	of	of	ADP
ejpam-5923	248	36	the	the	DET
ejpam-5923	248	37	distribution	distribution	NOUN
ejpam-5923	248	38	this	this	DET
ejpam-5923	248	39	section	section	NOUN
ejpam-5923	248	40	presents	present	VERB
ejpam-5923	248	41	the	the	DET
ejpam-5923	248	42	algorithm	algorithm	NOUN
ejpam-5923	248	43	for	for	ADP
ejpam-5923	248	44	the	the	DET
ejpam-5923	248	45	generation	generation	NOUN
ejpam-5923	248	46	of	of	ADP
ejpam-5923	248	47	random	random	ADJ
ejpam-5923	248	48	numbers	number	NOUN
ejpam-5923	248	49	from	from	ADP
ejpam-5923	248	50	the	the	DET
ejpam-5923	248	51	generalized	generalize	VERB
ejpam-5923	248	52	extended	extend	VERB
ejpam-5923	248	53	standard	standard	ADJ
ejpam-5923	248	54	u	u	NOUN
ejpam-5923	248	55	-	-	ADJ
ejpam-5923	248	56	quadratic	quadratic	ADJ
ejpam-5923	248	57	(	(	PUNCT
ejpam-5923	248	58	gesu	gesu	NOUN
ejpam-5923	248	59	)	)	PUNCT
ejpam-5923	248	60	distribution	distribution	NOUN
ejpam-5923	248	61	.	.	PUNCT
ejpam-5923	249	1	considering	consider	VERB
ejpam-5923	249	2	the	the	DET
ejpam-5923	249	3	inversion	inversion	NOUN
ejpam-5923	249	4	method	method	NOUN
ejpam-5923	249	5	,	,	PUNCT
ejpam-5923	249	6	let	let	VERB
ejpam-5923	249	7	q	q	PART
ejpam-5923	249	8	be	be	AUX
ejpam-5923	249	9	generated	generate	VERB
ejpam-5923	249	10	from	from	ADP
ejpam-5923	249	11	a	a	DET
ejpam-5923	249	12	uniform	uniform	ADJ
ejpam-5923	249	13	distribution	distribution	NOUN
ejpam-5923	249	14	on	on	ADP
ejpam-5923	249	15	(	(	PUNCT
ejpam-5923	249	16	0	0	NUM
ejpam-5923	249	17	,	,	PUNCT
ejpam-5923	249	18	1	1	NUM
ejpam-5923	249	19	)	)	PUNCT
ejpam-5923	249	20	.	.	PUNCT
ejpam-5923	250	1	then	then	ADV
ejpam-5923	250	2	,	,	PUNCT
ejpam-5923	250	3	f	f	PROPN
ejpam-5923	250	4	(	(	PUNCT
ejpam-5923	250	5	t	t	PROPN
ejpam-5923	250	6	)	)	PUNCT
ejpam-5923	250	7	=	=	PUNCT
ejpam-5923	250	8	q	q	PUNCT
ejpam-5923	251	1	=	=	NOUN
ejpam-5923	251	2	⇒	⇒	NOUN
ejpam-5923	251	3	t	t	NOUN
ejpam-5923	251	4	=	=	SYM
ejpam-5923	251	5	f−1(q	f−1(q	PROPN
ejpam-5923	251	6	)	)	PUNCT
ejpam-5923	251	7	,	,	PUNCT
ejpam-5923	251	8	where	where	SCONJ
ejpam-5923	251	9	f	f	PROPN
ejpam-5923	251	10	(	(	PUNCT
ejpam-5923	251	11	t	t	PROPN
ejpam-5923	251	12	)	)	PUNCT
ejpam-5923	251	13	is	be	AUX
ejpam-5923	251	14	the	the	DET
ejpam-5923	251	15	cdf	cdf	PROPN
ejpam-5923	251	16	of	of	ADP
ejpam-5923	251	17	the	the	DET
ejpam-5923	251	18	random	random	ADJ
ejpam-5923	251	19	variable	variable	NOUN
ejpam-5923	251	20	t	t	NOUN
ejpam-5923	251	21	.	.	PUNCT
ejpam-5923	252	1	for	for	ADP
ejpam-5923	252	2	the	the	DET
ejpam-5923	252	3	gesu	gesu	PROPN
ejpam-5923	252	4	distribution	distribution	NOUN
ejpam-5923	252	5	,	,	PUNCT
ejpam-5923	252	6	the	the	DET
ejpam-5923	252	7	cdf	cdf	PROPN
ejpam-5923	252	8	is	be	AUX
ejpam-5923	252	9	given	give	VERB
ejpam-5923	252	10	by	by	ADP
ejpam-5923	252	11	f	f	PROPN
ejpam-5923	252	12	(	(	PUNCT
ejpam-5923	252	13	t	t	PROPN
ejpam-5923	252	14	)	)	PUNCT
ejpam-5923	252	15	=	=	PUNCT
ejpam-5923	252	16	(	(	PUNCT
ejpam-5923	252	17	1−	1−	NUM
ejpam-5923	252	18	λ)t+	λ)t+	NUM
ejpam-5923	252	19	λ	λ	NOUN
ejpam-5923	252	20	[	[	PUNCT
ejpam-5923	252	21	(	(	PUNCT
ejpam-5923	252	22	t−	t−	ADP
ejpam-5923	252	23	a)3	a)3	ADJ
ejpam-5923	252	24	+	+	NUM
ejpam-5923	252	25	a3	a3	NOUN
ejpam-5923	252	26	]	]	PUNCT
ejpam-5923	252	27	(	(	PUNCT
ejpam-5923	252	28	1−	1−	NUM
ejpam-5923	252	29	a)3	a)3	ADJ
ejpam-5923	252	30	+	+	NUM
ejpam-5923	252	31	a3	a3	NOUN
ejpam-5923	252	32	,	,	PUNCT
ejpam-5923	252	33	where	where	SCONJ
ejpam-5923	252	34	t	t	PROPN
ejpam-5923	252	35	∈	∈	PROPN
ejpam-5923	253	1	[	[	X
ejpam-5923	253	2	0	0	NUM
ejpam-5923	253	3	,	,	PUNCT
ejpam-5923	253	4	1	1	NUM
ejpam-5923	253	5	]	]	PUNCT
ejpam-5923	253	6	,	,	PUNCT
ejpam-5923	253	7	a	a	DET
ejpam-5923	253	8	∈	∈	NOUN
ejpam-5923	254	1	[	[	X
ejpam-5923	254	2	0	0	NUM
ejpam-5923	254	3	,	,	PUNCT
ejpam-5923	254	4	1	1	NUM
ejpam-5923	254	5	]	]	PUNCT
ejpam-5923	254	6	and	and	CCONJ
ejpam-5923	254	7	λ	λ	PART
ejpam-5923	254	8	∈	∈	PROPN
ejpam-5923	254	9			X
ejpam-5923	254	10	[	[	PUNCT
ejpam-5923	254	11	−	−	X
ejpam-5923	254	12	(	(	PUNCT
ejpam-5923	254	13	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	254	14	3(1−a)2−(1−a)3−a3	3(1−a)2−(1−a)3−a3	NUM
ejpam-5923	254	15	,	,	PUNCT
ejpam-5923	254	16	1	1	NUM
ejpam-5923	254	17	]	]	PUNCT
ejpam-5923	254	18	,	,	PUNCT
ejpam-5923	254	19	if	if	SCONJ
ejpam-5923	254	20	a	a	DET
ejpam-5923	254	21	∈	∈	NOUN
ejpam-5923	255	1	[	[	X
ejpam-5923	255	2	0	0	NUM
ejpam-5923	255	3	,	,	PUNCT
ejpam-5923	255	4	0.5	0.5	NUM
ejpam-5923	255	5	]	]	PUNCT
ejpam-5923	255	6	[	[	PUNCT
ejpam-5923	255	7	−	−	X
ejpam-5923	255	8	(	(	PUNCT
ejpam-5923	255	9	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	255	10	3a2−(1−a)3−a3	3a2−(1−a)3−a3	NUM
ejpam-5923	255	11	,	,	PUNCT
ejpam-5923	255	12	1	1	NUM
ejpam-5923	255	13	]	]	PUNCT
ejpam-5923	255	14	,	,	PUNCT
ejpam-5923	255	15	if	if	SCONJ
ejpam-5923	255	16	a	a	DET
ejpam-5923	255	17	∈	∈	NOUN
ejpam-5923	255	18	[	[	X
ejpam-5923	255	19	0.5	0.5	NUM
ejpam-5923	255	20	,	,	PUNCT
ejpam-5923	255	21	1	1	NUM
ejpam-5923	255	22	]	]	PUNCT
ejpam-5923	255	23	.	.	PUNCT
ejpam-5923	256	1	thus	thus	ADV
ejpam-5923	256	2	,	,	PUNCT
ejpam-5923	256	3	we	we	PRON
ejpam-5923	256	4	have	have	VERB
ejpam-5923	256	5	(	(	PUNCT
ejpam-5923	256	6	1−	1−	NUM
ejpam-5923	256	7	λ)t+	λ)t+	NUM
ejpam-5923	256	8	λ	λ	NOUN
ejpam-5923	256	9	[	[	PUNCT
ejpam-5923	256	10	(	(	PUNCT
ejpam-5923	256	11	t−	t−	ADP
ejpam-5923	256	12	a)3	a)3	ADJ
ejpam-5923	256	13	+	+	NUM
ejpam-5923	256	14	a3	a3	NOUN
ejpam-5923	256	15	]	]	PUNCT
ejpam-5923	256	16	(	(	PUNCT
ejpam-5923	256	17	1−	1−	NUM
ejpam-5923	256	18	a)3	a)3	ADJ
ejpam-5923	256	19	+	+	NUM
ejpam-5923	256	20	a3	a3	NOUN
ejpam-5923	256	21	=	=	SYM
ejpam-5923	256	22	q	q	NOUN
ejpam-5923	257	1	=	=	ADJ
ejpam-5923	257	2	⇒	⇒	NOUN
ejpam-5923	257	3	(	(	PUNCT
ejpam-5923	257	4	1−	1−	NUM
ejpam-5923	257	5	λ)t+	λ)t+	NUM
ejpam-5923	257	6	λ	λ	NOUN
ejpam-5923	257	7	[	[	PUNCT
ejpam-5923	257	8	(	(	PUNCT
ejpam-5923	257	9	t−	t−	ADP
ejpam-5923	257	10	a)3	a)3	ADJ
ejpam-5923	257	11	+	+	NUM
ejpam-5923	257	12	a3	a3	NOUN
ejpam-5923	257	13	]	]	PUNCT
ejpam-5923	257	14	(	(	PUNCT
ejpam-5923	257	15	1−	1−	NUM
ejpam-5923	257	16	a)3	a)3	ADJ
ejpam-5923	257	17	+	+	NUM
ejpam-5923	257	18	a3	a3	NOUN
ejpam-5923	257	19	−	−	NOUN
ejpam-5923	257	20	q	q	NOUN
ejpam-5923	258	1	=	=	NOUN
ejpam-5923	258	2	0	0	NUM
ejpam-5923	258	3	.	.	PUNCT
ejpam-5923	259	1	(	(	PUNCT
ejpam-5923	259	2	9	9	X
ejpam-5923	259	3	)	)	PUNCT
ejpam-5923	259	4	observe	observe	VERB
ejpam-5923	259	5	that	that	SCONJ
ejpam-5923	259	6	equation	equation	NOUN
ejpam-5923	259	7	(	(	PUNCT
ejpam-5923	259	8	9	9	X
ejpam-5923	259	9	)	)	PUNCT
ejpam-5923	259	10	can	can	AUX
ejpam-5923	259	11	not	not	PART
ejpam-5923	259	12	be	be	AUX
ejpam-5923	259	13	solved	solve	VERB
ejpam-5923	259	14	analytically	analytically	ADV
ejpam-5923	259	15	.	.	PUNCT
ejpam-5923	260	1	so	so	ADV
ejpam-5923	260	2	,	,	PUNCT
ejpam-5923	260	3	we	we	PRON
ejpam-5923	260	4	use	use	VERB
ejpam-5923	260	5	numerical	numerical	ADJ
ejpam-5923	260	6	method	method	NOUN
ejpam-5923	260	7	to	to	PART
ejpam-5923	260	8	solve	solve	VERB
ejpam-5923	260	9	for	for	ADP
ejpam-5923	260	10	t.	t.	PROPN
ejpam-5923	260	11	here	here	ADV
ejpam-5923	260	12	,	,	PUNCT
ejpam-5923	260	13	we	we	PRON
ejpam-5923	260	14	consider	consider	VERB
ejpam-5923	260	15	the	the	DET
ejpam-5923	260	16	newton	newton	PROPN
ejpam-5923	260	17	-	-	PUNCT
ejpam-5923	260	18	raphson	raphson	NOUN
ejpam-5923	260	19	method	method	NOUN
ejpam-5923	260	20	.	.	PUNCT
ejpam-5923	261	1	a	a	DET
ejpam-5923	261	2	newton	newton	PROPN
ejpam-5923	261	3	raphson	raphson	NOUN
ejpam-5923	261	4	method	method	NOUN
ejpam-5923	261	5	is	be	AUX
ejpam-5923	261	6	an	an	DET
ejpam-5923	261	7	iterative	iterative	ADJ
ejpam-5923	261	8	numerical	numerical	ADJ
ejpam-5923	261	9	technique	technique	NOUN
ejpam-5923	261	10	that	that	PRON
ejpam-5923	261	11	is	be	AUX
ejpam-5923	261	12	used	use	VERB
ejpam-5923	261	13	to	to	PART
ejpam-5923	261	14	find	find	VERB
ejpam-5923	261	15	roots	root	NOUN
ejpam-5923	261	16	of	of	ADP
ejpam-5923	261	17	real	real	ADV
ejpam-5923	261	18	-	-	PUNCT
ejpam-5923	261	19	valued	value	VERB
ejpam-5923	261	20	functions	function	NOUN
ejpam-5923	261	21	.	.	PUNCT
ejpam-5923	262	1	the	the	DET
ejpam-5923	262	2	algorithm	algorithm	NOUN
ejpam-5923	262	3	for	for	ADP
ejpam-5923	262	4	the	the	DET
ejpam-5923	262	5	newton	newton	PROPN
ejpam-5923	262	6	raphson	raphson	PROPN
ejpam-5923	262	7	method	method	NOUN
ejpam-5923	262	8	is	be	AUX
ejpam-5923	262	9	given	give	VERB
ejpam-5923	262	10	as	as	SCONJ
ejpam-5923	262	11	follows	follow	VERB
ejpam-5923	262	12	:	:	PUNCT
ejpam-5923	262	13	let	let	VERB
ejpam-5923	262	14	f(t	f(t	NOUN
ejpam-5923	262	15	)	)	PUNCT
ejpam-5923	262	16	be	be	AUX
ejpam-5923	262	17	a	a	DET
ejpam-5923	262	18	real	real	ADV
ejpam-5923	262	19	-	-	PUNCT
ejpam-5923	262	20	valued	value	VERB
ejpam-5923	262	21	function	function	NOUN
ejpam-5923	262	22	with	with	ADP
ejpam-5923	262	23	first	first	ADJ
ejpam-5923	262	24	derivative	derivative	ADJ
ejpam-5923	262	25	f	f	PROPN
ejpam-5923	262	26	′(t	′(t	PROPN
ejpam-5923	262	27	)	)	PUNCT
ejpam-5923	262	28	.	.	PUNCT
ejpam-5923	263	1	then	then	ADV
ejpam-5923	263	2	i.	i.	PROPN
ejpam-5923	263	3	a.	a.	PROPN
ejpam-5923	263	4	lakibul	lakibul	PROPN
ejpam-5923	263	5	,	,	PUNCT
ejpam-5923	263	6	d.	d.	PROPN
ejpam-5923	263	7	l.	l.	PROPN
ejpam-5923	263	8	polestico	polestico	PROPN
ejpam-5923	263	9	,	,	PUNCT
ejpam-5923	263	10	a.	a.	PROPN
ejpam-5923	263	11	p.	p.	NOUN
ejpam-5923	263	12	supe	supe	PROPN
ejpam-5923	263	13	/	/	SYM
ejpam-5923	263	14	eur	eur	PROPN
ejpam-5923	263	15	.	.	PUNCT
ejpam-5923	264	1	j.	j.	PROPN
ejpam-5923	264	2	pure	pure	PROPN
ejpam-5923	264	3	appl	appl	PROPN
ejpam-5923	264	4	.	.	PROPN
ejpam-5923	264	5	math	math	PROPN
ejpam-5923	264	6	,	,	PUNCT
ejpam-5923	264	7	18	18	NUM
ejpam-5923	264	8	(	(	PUNCT
ejpam-5923	264	9	2	2	NUM
ejpam-5923	264	10	)	)	PUNCT
ejpam-5923	264	11	(	(	PUNCT
ejpam-5923	264	12	2025	2025	NUM
ejpam-5923	264	13	)	)	PUNCT
ejpam-5923	264	14	,	,	PUNCT
ejpam-5923	264	15	5923	5923	NUM
ejpam-5923	264	16	16	16	NUM
ejpam-5923	264	17	of	of	ADP
ejpam-5923	264	18	21	21	NUM
ejpam-5923	264	19	steps	step	NOUN
ejpam-5923	264	20	description	description	NOUN
ejpam-5923	264	21	1	1	NUM
ejpam-5923	264	22	choose	choose	VERB
ejpam-5923	264	23	an	an	DET
ejpam-5923	264	24	initial	initial	ADJ
ejpam-5923	264	25	guess	guess	NOUN
ejpam-5923	264	26	(	(	PUNCT
ejpam-5923	264	27	t0	t0	NOUN
ejpam-5923	264	28	)	)	PUNCT
ejpam-5923	264	29	,	,	PUNCT
ejpam-5923	264	30	a	a	DET
ejpam-5923	264	31	tolerance	tolerance	NOUN
ejpam-5923	264	32	level	level	NOUN
ejpam-5923	264	33	(	(	PUNCT
ejpam-5923	264	34	tol	tol	NOUN
ejpam-5923	264	35	)	)	PUNCT
ejpam-5923	264	36	,	,	PUNCT
ejpam-5923	264	37	and	and	CCONJ
ejpam-5923	264	38	a	a	DET
ejpam-5923	264	39	maximum	maximum	ADJ
ejpam-5923	264	40	number	number	NOUN
ejpam-5923	264	41	of	of	ADP
ejpam-5923	264	42	iteration	iteration	NOUN
ejpam-5923	264	43	(	(	PUNCT
ejpam-5923	264	44	maxiter	maxiter	NOUN
ejpam-5923	264	45	)	)	PUNCT
ejpam-5923	264	46	.	.	PUNCT
ejpam-5923	265	1	2	2	NUM
ejpam-5923	265	2	evaluate	evaluate	VERB
ejpam-5923	265	3	f(tn	f(tn	NOUN
ejpam-5923	265	4	)	)	PUNCT
ejpam-5923	265	5	and	and	CCONJ
ejpam-5923	265	6	(	(	PUNCT
ejpam-5923	265	7	f	f	PROPN
ejpam-5923	265	8	′(tn	′(tn	PROPN
ejpam-5923	265	9	)	)	PUNCT
ejpam-5923	265	10	)	)	PUNCT
ejpam-5923	265	11	.	.	PUNCT
ejpam-5923	266	1	3	3	NUM
ejpam-5923	266	2	check	check	NOUN
ejpam-5923	266	3	for	for	ADP
ejpam-5923	266	4	convergence	convergence	NOUN
ejpam-5923	266	5	:	:	PUNCT
ejpam-5923	266	6	if	if	SCONJ
ejpam-5923	266	7	(	(	PUNCT
ejpam-5923	266	8	|f(tn)|	|f(tn)|	NOUN
ejpam-5923	266	9	<	<	X
ejpam-5923	266	10	tol	tol	NOUN
ejpam-5923	266	11	)	)	PUNCT
ejpam-5923	266	12	,	,	PUNCT
ejpam-5923	266	13	stop	stop	VERB
ejpam-5923	266	14	and	and	CCONJ
ejpam-5923	266	15	return	return	VERB
ejpam-5923	266	16	(	(	PUNCT
ejpam-5923	266	17	tn	tn	NOUN
ejpam-5923	266	18	)	)	PUNCT
ejpam-5923	266	19	.	.	PUNCT
ejpam-5923	267	1	4	4	NUM
ejpam-5923	267	2	update	update	NOUN
ejpam-5923	267	3	the	the	DET
ejpam-5923	267	4	estimate	estimate	NOUN
ejpam-5923	267	5	using	use	VERB
ejpam-5923	267	6	the	the	DET
ejpam-5923	267	7	following	follow	VERB
ejpam-5923	267	8	formula	formula	NOUN
ejpam-5923	267	9	tn+1	tn+1	NOUN
ejpam-5923	267	10	=	=	SYM
ejpam-5923	267	11	tn	tn	PROPN
ejpam-5923	267	12	−	−	PROPN
ejpam-5923	267	13	f(tn	f(tn	PROPN
ejpam-5923	267	14	)	)	PUNCT
ejpam-5923	267	15	f	f	PROPN
ejpam-5923	267	16	′(tn	′(tn	PROPN
ejpam-5923	267	17	)	)	PUNCT
ejpam-5923	267	18	,	,	PUNCT
ejpam-5923	267	19	n	n	NOUN
ejpam-5923	267	20	=	=	SYM
ejpam-5923	267	21	0	0	NUM
ejpam-5923	267	22	,	,	PUNCT
ejpam-5923	267	23	1	1	NUM
ejpam-5923	267	24	,	,	PUNCT
ejpam-5923	267	25	2	2	NUM
ejpam-5923	267	26	,	,	PUNCT
ejpam-5923	267	27	3	3	NUM
ejpam-5923	267	28	,	,	PUNCT
ejpam-5923	267	29	...	...	PUNCT
ejpam-5923	267	30	5	5	NUM
ejpam-5923	267	31	repeat	repeat	NOUN
ejpam-5923	267	32	until	until	SCONJ
ejpam-5923	267	33	the	the	DET
ejpam-5923	267	34	function	function	NOUN
ejpam-5923	267	35	value	value	NOUN
ejpam-5923	267	36	is	be	AUX
ejpam-5923	267	37	within	within	ADP
ejpam-5923	267	38	the	the	DET
ejpam-5923	267	39	desired	desire	VERB
ejpam-5923	267	40	tolerance	tolerance	NOUN
ejpam-5923	267	41	or	or	CCONJ
ejpam-5923	267	42	the	the	DET
ejpam-5923	267	43	maximum	maximum	ADJ
ejpam-5923	267	44	number	number	NOUN
ejpam-5923	267	45	of	of	ADP
ejpam-5923	267	46	iterations	iteration	NOUN
ejpam-5923	267	47	is	be	AUX
ejpam-5923	267	48	reached	reach	VERB
ejpam-5923	267	49	.	.	PUNCT
ejpam-5923	268	1	now	now	ADV
ejpam-5923	268	2	,	,	PUNCT
ejpam-5923	268	3	note	note	VERB
ejpam-5923	268	4	that	that	SCONJ
ejpam-5923	268	5	if	if	SCONJ
ejpam-5923	268	6	λ	λ	PROPN
ejpam-5923	268	7	=	=	SYM
ejpam-5923	268	8	0	0	NUM
ejpam-5923	268	9	,	,	PUNCT
ejpam-5923	268	10	then	then	ADV
ejpam-5923	268	11	the	the	DET
ejpam-5923	268	12	gesu	gesu	PROPN
ejpam-5923	268	13	distribution	distribution	NOUN
ejpam-5923	268	14	simplifies	simplifie	NOUN
ejpam-5923	268	15	to	to	ADP
ejpam-5923	268	16	the	the	DET
ejpam-5923	268	17	uniform	uniform	ADJ
ejpam-5923	268	18	distribution	distribution	NOUN
ejpam-5923	268	19	defined	define	VERB
ejpam-5923	268	20	on	on	ADP
ejpam-5923	268	21	(	(	PUNCT
ejpam-5923	268	22	0	0	NUM
ejpam-5923	268	23	,	,	PUNCT
ejpam-5923	268	24	1	1	NUM
ejpam-5923	268	25	)	)	PUNCT
ejpam-5923	268	26	.	.	PUNCT
ejpam-5923	269	1	so	so	ADV
ejpam-5923	269	2	,	,	PUNCT
ejpam-5923	269	3	we	we	PRON
ejpam-5923	269	4	can	can	AUX
ejpam-5923	269	5	use	use	VERB
ejpam-5923	269	6	the	the	DET
ejpam-5923	269	7	uniform	uniform	ADJ
ejpam-5923	269	8	distribution	distribution	NOUN
ejpam-5923	269	9	as	as	ADP
ejpam-5923	269	10	initial	initial	ADJ
ejpam-5923	269	11	guess	guess	NOUN
ejpam-5923	269	12	(	(	PUNCT
ejpam-5923	269	13	t0	t0	NOUN
ejpam-5923	269	14	)	)	PUNCT
ejpam-5923	269	15	.	.	PUNCT
ejpam-5923	270	1	thus	thus	ADV
ejpam-5923	270	2	,	,	PUNCT
ejpam-5923	270	3	we	we	PRON
ejpam-5923	270	4	have	have	VERB
ejpam-5923	270	5	the	the	DET
ejpam-5923	270	6	following	follow	VERB
ejpam-5923	270	7	modified	modified	ADJ
ejpam-5923	270	8	algorithm	algorithm	NOUN
ejpam-5923	270	9	to	to	PART
ejpam-5923	270	10	generate	generate	VERB
ejpam-5923	270	11	random	random	ADJ
ejpam-5923	270	12	numbers	number	NOUN
ejpam-5923	270	13	from	from	ADP
ejpam-5923	270	14	the	the	DET
ejpam-5923	270	15	gesu	gesu	PROPN
ejpam-5923	270	16	distribution	distribution	NOUN
ejpam-5923	270	17	.	.	PUNCT
ejpam-5923	271	1	set	set	VERB
ejpam-5923	271	2	true	true	ADJ
ejpam-5923	271	3	values	value	NOUN
ejpam-5923	271	4	for	for	ADP
ejpam-5923	271	5	λ	λ	PROPN
ejpam-5923	271	6	and	and	CCONJ
ejpam-5923	271	7	a.	a.	NOUN
ejpam-5923	271	8	then	then	ADV
ejpam-5923	271	9	,	,	PUNCT
ejpam-5923	271	10	steps	step	VERB
ejpam-5923	271	11	description	description	NOUN
ejpam-5923	271	12	1	1	NUM
ejpam-5923	271	13	set	set	VERB
ejpam-5923	271	14	t0	t0	NOUN
ejpam-5923	271	15	=	=	SYM
ejpam-5923	271	16	q	q	X
ejpam-5923	271	17	,	,	PUNCT
ejpam-5923	271	18	tol	tol	NOUN
ejpam-5923	271	19	=	=	PUNCT
ejpam-5923	271	20	1×	1×	NUM
ejpam-5923	271	21	10−8	10−8	NUM
ejpam-5923	271	22	,	,	PUNCT
ejpam-5923	271	23	and	and	CCONJ
ejpam-5923	271	24	maxiter	maxit	ADJ
ejpam-5923	271	25	=	=	NOUN
ejpam-5923	271	26	100	100	NUM
ejpam-5923	271	27	.	.	X
ejpam-5923	271	28	2	2	NUM
ejpam-5923	271	29	evaluate	evaluate	VERB
ejpam-5923	271	30	f(tn	f(tn	NOUN
ejpam-5923	271	31	)	)	PUNCT
ejpam-5923	271	32	=	=	PUNCT
ejpam-5923	271	33	(	(	PUNCT
ejpam-5923	272	1	1−	1−	NUM
ejpam-5923	272	2	λ)tn	λ)tn	PROPN
ejpam-5923	272	3	+	+	CCONJ
ejpam-5923	272	4	λ[(tn−a)3+a3	λ[(tn−a)3+a3	PROPN
ejpam-5923	272	5	]	]	X
ejpam-5923	272	6	(	(	PUNCT
ejpam-5923	272	7	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	272	8	−	−	NOUN
ejpam-5923	272	9	q	q	NOUN
ejpam-5923	272	10	,	,	PUNCT
ejpam-5923	272	11	and	and	CCONJ
ejpam-5923	272	12	f	f	PROPN
ejpam-5923	272	13	′(tn	′(tn	PROPN
ejpam-5923	272	14	)	)	PUNCT
ejpam-5923	272	15	=	=	SYM
ejpam-5923	272	16	1−	1−	NUM
ejpam-5923	272	17	λ+	λ+	PUNCT
ejpam-5923	272	18	3λ	3λ	NUM
ejpam-5923	272	19	(	(	PUNCT
ejpam-5923	272	20	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	272	21	(	(	PUNCT
ejpam-5923	272	22	tn	tn	NOUN
ejpam-5923	272	23	−	−	PROPN
ejpam-5923	272	24	a)2	a)2	PROPN
ejpam-5923	272	25	.	.	PUNCT
ejpam-5923	272	26	3	3	NUM
ejpam-5923	272	27	check	check	NOUN
ejpam-5923	272	28	for	for	ADP
ejpam-5923	272	29	convergence	convergence	NOUN
ejpam-5923	272	30	:	:	PUNCT
ejpam-5923	272	31	if	if	SCONJ
ejpam-5923	272	32	(	(	PUNCT
ejpam-5923	272	33	|f(tn)|	|f(tn)|	NOUN
ejpam-5923	272	34	<	<	X
ejpam-5923	272	35	tol	tol	NOUN
ejpam-5923	272	36	)	)	PUNCT
ejpam-5923	272	37	,	,	PUNCT
ejpam-5923	272	38	stop	stop	VERB
ejpam-5923	272	39	and	and	CCONJ
ejpam-5923	272	40	return	return	VERB
ejpam-5923	272	41	(	(	PUNCT
ejpam-5923	272	42	tn	tn	NOUN
ejpam-5923	272	43	)	)	PUNCT
ejpam-5923	272	44	.	.	PUNCT
ejpam-5923	273	1	4	4	NUM
ejpam-5923	273	2	update	update	NOUN
ejpam-5923	273	3	the	the	DET
ejpam-5923	273	4	estimate	estimate	NOUN
ejpam-5923	273	5	using	use	VERB
ejpam-5923	273	6	the	the	DET
ejpam-5923	273	7	following	follow	VERB
ejpam-5923	273	8	formula	formula	NOUN
ejpam-5923	273	9	tn+1	tn+1	NOUN
ejpam-5923	273	10	=	=	SYM
ejpam-5923	273	11	tn	tn	PROPN
ejpam-5923	273	12	−	−	PROPN
ejpam-5923	273	13	(	(	PUNCT
ejpam-5923	273	14	1−λ)tn+	1−λ)tn+	NUM
ejpam-5923	273	15	λ[(tn−a)3+a3	λ[(tn−a)3+a3	X
ejpam-5923	273	16	]	]	X
ejpam-5923	273	17	(	(	PUNCT
ejpam-5923	273	18	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	273	19	−q	−q	VERB
ejpam-5923	273	20	1−λ+	1−λ+	NUM
ejpam-5923	273	21	3λ	3λ	NUM
ejpam-5923	273	22	(	(	PUNCT
ejpam-5923	273	23	1−a)3+a3	1−a)3+a3	NUM
ejpam-5923	273	24	(	(	PUNCT
ejpam-5923	273	25	tn−a)2	tn−a)2	NUM
ejpam-5923	273	26	,	,	PUNCT
ejpam-5923	273	27	n	n	PROPN
ejpam-5923	273	28	=	=	SYM
ejpam-5923	273	29	0	0	NUM
ejpam-5923	273	30	,	,	PUNCT
ejpam-5923	273	31	1	1	NUM
ejpam-5923	273	32	,	,	PUNCT
ejpam-5923	273	33	2	2	NUM
ejpam-5923	273	34	,	,	PUNCT
ejpam-5923	273	35	3	3	NUM
ejpam-5923	273	36	,	,	PUNCT
ejpam-5923	273	37	...	...	PUNCT
ejpam-5923	273	38	5	5	NUM
ejpam-5923	273	39	repeat	repeat	NOUN
ejpam-5923	273	40	until	until	SCONJ
ejpam-5923	273	41	the	the	DET
ejpam-5923	273	42	function	function	NOUN
ejpam-5923	273	43	value	value	NOUN
ejpam-5923	273	44	is	be	AUX
ejpam-5923	273	45	within	within	ADP
ejpam-5923	273	46	the	the	DET
ejpam-5923	273	47	desired	desire	VERB
ejpam-5923	273	48	tolerance	tolerance	NOUN
ejpam-5923	273	49	or	or	CCONJ
ejpam-5923	273	50	the	the	DET
ejpam-5923	273	51	maximum	maximum	ADJ
ejpam-5923	273	52	number	number	NOUN
ejpam-5923	273	53	of	of	ADP
ejpam-5923	273	54	iterations	iteration	NOUN
ejpam-5923	273	55	is	be	AUX
ejpam-5923	273	56	reached	reach	VERB
ejpam-5923	273	57	.	.	PUNCT
ejpam-5923	274	1	in	in	ADP
ejpam-5923	274	2	addition	addition	NOUN
ejpam-5923	274	3	,	,	PUNCT
ejpam-5923	274	4	the	the	DET
ejpam-5923	274	5	median	median	NOUN
ejpam-5923	274	6	(	(	PUNCT
ejpam-5923	274	7	tmed	tme	VERB
ejpam-5923	274	8	)	)	PUNCT
ejpam-5923	274	9	of	of	ADP
ejpam-5923	274	10	the	the	DET
ejpam-5923	274	11	gesu	gesu	PROPN
ejpam-5923	274	12	distribution	distribution	NOUN
ejpam-5923	274	13	can	can	AUX
ejpam-5923	274	14	be	be	AUX
ejpam-5923	274	15	computed	compute	VERB
ejpam-5923	274	16	numerically	numerically	ADV
ejpam-5923	274	17	using	use	VERB
ejpam-5923	274	18	the	the	DET
ejpam-5923	274	19	newton	newton	PROPN
ejpam-5923	274	20	raphson	raphson	NOUN
ejpam-5923	274	21	method	method	NOUN
ejpam-5923	274	22	by	by	ADP
ejpam-5923	274	23	solving	solve	VERB
ejpam-5923	274	24	f	f	PROPN
ejpam-5923	274	25	(	(	PUNCT
ejpam-5923	274	26	tmed	tme	VERB
ejpam-5923	274	27	)	)	PUNCT
ejpam-5923	274	28	=	=	PUNCT
ejpam-5923	275	1	(	(	PUNCT
ejpam-5923	275	2	1−	1−	NUM
ejpam-5923	275	3	λ)tmed	λ)tmed	NUM
ejpam-5923	276	1	+	+	NUM
ejpam-5923	276	2	λ	λ	X
ejpam-5923	276	3	[	[	PUNCT
ejpam-5923	276	4	(	(	PUNCT
ejpam-5923	276	5	tmed	tme	VERB
ejpam-5923	276	6	−	−	PROPN
ejpam-5923	276	7	a)3	a)3	ADJ
ejpam-5923	276	8	+	+	NUM
ejpam-5923	276	9	a3	a3	NOUN
ejpam-5923	276	10	]	]	PUNCT
ejpam-5923	276	11	(	(	PUNCT
ejpam-5923	276	12	1−	1−	NUM
ejpam-5923	276	13	a)3	a)3	ADJ
ejpam-5923	276	14	+	+	NUM
ejpam-5923	276	15	a3	a3	NOUN
ejpam-5923	276	16	=	=	NOUN
ejpam-5923	276	17	1	1	NUM
ejpam-5923	276	18	2	2	NUM
ejpam-5923	276	19	.	.	PUNCT
ejpam-5923	277	1	now	now	ADV
ejpam-5923	277	2	,	,	PUNCT
ejpam-5923	277	3	to	to	PART
ejpam-5923	277	4	assess	assess	VERB
ejpam-5923	277	5	the	the	DET
ejpam-5923	277	6	above	above	ADJ
ejpam-5923	277	7	algorithm	algorithm	NOUN
ejpam-5923	277	8	for	for	ADP
ejpam-5923	277	9	generating	generate	VERB
ejpam-5923	277	10	random	random	ADJ
ejpam-5923	277	11	numbers	number	NOUN
ejpam-5923	277	12	from	from	ADP
ejpam-5923	277	13	the	the	DET
ejpam-5923	277	14	gesu	gesu	PROPN
ejpam-5923	277	15	distribution	distribution	NOUN
ejpam-5923	277	16	,	,	PUNCT
ejpam-5923	277	17	let	let	VERB
ejpam-5923	277	18	us	we	PRON
ejpam-5923	277	19	consider	consider	VERB
ejpam-5923	277	20	the	the	DET
ejpam-5923	277	21	following	follow	VERB
ejpam-5923	277	22	examples	example	NOUN
ejpam-5923	277	23	.	.	PUNCT
ejpam-5923	278	1	example	example	NOUN
ejpam-5923	279	1	1	1	NUM
ejpam-5923	279	2	.	.	PUNCT
ejpam-5923	279	3	random	random	ADJ
ejpam-5923	279	4	numbers	number	NOUN
ejpam-5923	279	5	generated	generate	VERB
ejpam-5923	279	6	from	from	ADP
ejpam-5923	279	7	gesu	gesu	PROPN
ejpam-5923	279	8	distribution	distribution	NOUN
ejpam-5923	279	9	of	of	ADP
ejpam-5923	279	10	size	size	NOUN
ejpam-5923	279	11	n	n	PROPN
ejpam-5923	279	12	=	=	SYM
ejpam-5923	279	13	10000	10000	NUM
ejpam-5923	279	14	.	.	PUNCT
ejpam-5923	280	1	i.	i.	PROPN
ejpam-5923	280	2	a.	a.	PROPN
ejpam-5923	280	3	lakibul	lakibul	PROPN
ejpam-5923	280	4	,	,	PUNCT
ejpam-5923	280	5	d.	d.	PROPN
ejpam-5923	280	6	l.	l.	PROPN
ejpam-5923	280	7	polestico	polestico	PROPN
ejpam-5923	280	8	,	,	PUNCT
ejpam-5923	280	9	a.	a.	PROPN
ejpam-5923	280	10	p.	p.	NOUN
ejpam-5923	280	11	supe	supe	PROPN
ejpam-5923	280	12	/	/	SYM
ejpam-5923	280	13	eur	eur	PROPN
ejpam-5923	280	14	.	.	PUNCT
ejpam-5923	281	1	j.	j.	PROPN
ejpam-5923	281	2	pure	pure	PROPN
ejpam-5923	281	3	appl	appl	PROPN
ejpam-5923	281	4	.	.	PROPN
ejpam-5923	281	5	math	math	PROPN
ejpam-5923	281	6	,	,	PUNCT
ejpam-5923	281	7	18	18	NUM
ejpam-5923	281	8	(	(	PUNCT
ejpam-5923	281	9	2	2	NUM
ejpam-5923	281	10	)	)	PUNCT
ejpam-5923	281	11	(	(	PUNCT
ejpam-5923	281	12	2025	2025	NUM
ejpam-5923	281	13	)	)	PUNCT
ejpam-5923	281	14	,	,	PUNCT
ejpam-5923	281	15	5923	5923	NUM
ejpam-5923	281	16	17	17	NUM
ejpam-5923	281	17	of	of	ADP
ejpam-5923	281	18	21	21	NUM
ejpam-5923	281	19	(	(	PUNCT
ejpam-5923	281	20	a	a	NOUN
ejpam-5923	281	21	)	)	PUNCT
ejpam-5923	281	22	(	(	PUNCT
ejpam-5923	281	23	b	b	X
ejpam-5923	281	24	)	)	PUNCT
ejpam-5923	281	25	figure	figure	NOUN
ejpam-5923	281	26	7	7	NUM
ejpam-5923	281	27	:	:	PUNCT
ejpam-5923	281	28	histogram	histogram	NOUN
ejpam-5923	281	29	of	of	ADP
ejpam-5923	281	30	the	the	DET
ejpam-5923	281	31	simulated	simulate	VERB
ejpam-5923	281	32	data	datum	NOUN
ejpam-5923	281	33	set	set	VERB
ejpam-5923	281	34	and	and	CCONJ
ejpam-5923	281	35	fitted	fit	VERB
ejpam-5923	281	36	density	density	NOUN
ejpam-5923	281	37	of	of	ADP
ejpam-5923	281	38	the	the	DET
ejpam-5923	281	39	true	true	ADJ
ejpam-5923	281	40	values	value	NOUN
ejpam-5923	281	41	of	of	ADP
ejpam-5923	281	42	the	the	DET
ejpam-5923	281	43	parameters	parameter	NOUN
ejpam-5923	281	44	for	for	ADP
ejpam-5923	281	45	gesu	gesu	NOUN
ejpam-5923	281	46	distribution	distribution	NOUN
ejpam-5923	281	47	with	with	ADP
ejpam-5923	281	48	the	the	DET
ejpam-5923	281	49	following	follow	VERB
ejpam-5923	281	50	values	value	NOUN
ejpam-5923	281	51	:	:	PUNCT
ejpam-5923	281	52	(	(	PUNCT
ejpam-5923	281	53	a	a	X
ejpam-5923	281	54	)	)	PUNCT
ejpam-5923	281	55	λ	λ	NOUN
ejpam-5923	281	56	=	=	NOUN
ejpam-5923	281	57	0.8	0.8	NUM
ejpam-5923	281	58	and	and	CCONJ
ejpam-5923	281	59	a	a	DET
ejpam-5923	281	60	=	=	ADJ
ejpam-5923	281	61	0.6	0.6	NUM
ejpam-5923	281	62	;	;	PUNCT
ejpam-5923	281	63	and	and	CCONJ
ejpam-5923	281	64	(	(	PUNCT
ejpam-5923	281	65	b	b	X
ejpam-5923	281	66	)	)	PUNCT
ejpam-5923	281	67	λ	λ	NOUN
ejpam-5923	281	68	=	=	SYM
ejpam-5923	281	69	−0.3	−0.3	PROPN
ejpam-5923	281	70	and	and	CCONJ
ejpam-5923	281	71	a	a	PRON
ejpam-5923	281	72	=	=	SYM
ejpam-5923	281	73	0.4	0.4	NUM
ejpam-5923	281	74	.	.	PUNCT
ejpam-5923	282	1	figures	figure	NOUN
ejpam-5923	282	2	7a	7a	NUM
ejpam-5923	282	3	and	and	CCONJ
ejpam-5923	282	4	7b	7b	NOUN
ejpam-5923	282	5	show	show	VERB
ejpam-5923	282	6	that	that	SCONJ
ejpam-5923	282	7	the	the	DET
ejpam-5923	282	8	true	true	ADJ
ejpam-5923	282	9	plots	plot	NOUN
ejpam-5923	282	10	fitted	fit	VERB
ejpam-5923	282	11	the	the	DET
ejpam-5923	282	12	simulated	simulated	ADJ
ejpam-5923	282	13	histogram	histogram	NOUN
ejpam-5923	282	14	for	for	ADP
ejpam-5923	282	15	gesu	gesu	NOUN
ejpam-5923	282	16	distribution	distribution	NOUN
ejpam-5923	282	17	.	.	PUNCT
ejpam-5923	283	1	this	this	PRON
ejpam-5923	283	2	implies	imply	VERB
ejpam-5923	283	3	that	that	SCONJ
ejpam-5923	283	4	the	the	DET
ejpam-5923	283	5	above	above	ADJ
ejpam-5923	283	6	algorithm	algorithm	NOUN
ejpam-5923	283	7	works	work	VERB
ejpam-5923	283	8	well	well	ADV
ejpam-5923	283	9	for	for	ADP
ejpam-5923	283	10	generating	generate	VERB
ejpam-5923	283	11	random	random	ADJ
ejpam-5923	283	12	numbers	number	NOUN
ejpam-5923	283	13	from	from	ADP
ejpam-5923	283	14	the	the	DET
ejpam-5923	283	15	gesu	gesu	PROPN
ejpam-5923	283	16	distribution	distribution	NOUN
ejpam-5923	283	17	.	.	PUNCT
ejpam-5923	284	1	6	6	X
ejpam-5923	284	2	.	.	X
ejpam-5923	284	3	simulation	simulation	NOUN
ejpam-5923	284	4	study	study	VERB
ejpam-5923	284	5	this	this	DET
ejpam-5923	284	6	section	section	NOUN
ejpam-5923	284	7	presents	present	VERB
ejpam-5923	284	8	the	the	DET
ejpam-5923	284	9	simulation	simulation	NOUN
ejpam-5923	284	10	results	result	VERB
ejpam-5923	284	11	to	to	PART
ejpam-5923	284	12	assess	assess	VERB
ejpam-5923	284	13	the	the	DET
ejpam-5923	284	14	behavior	behavior	NOUN
ejpam-5923	284	15	of	of	ADP
ejpam-5923	284	16	the	the	DET
ejpam-5923	284	17	maximum	maximum	ADJ
ejpam-5923	284	18	likelihood	likelihood	NOUN
ejpam-5923	284	19	estimate	estimate	NOUN
ejpam-5923	284	20	of	of	ADP
ejpam-5923	284	21	the	the	DET
ejpam-5923	284	22	parameter	parameter	NOUN
ejpam-5923	284	23	of	of	ADP
ejpam-5923	284	24	the	the	DET
ejpam-5923	284	25	proposed	propose	VERB
ejpam-5923	284	26	generalized	generalized	ADJ
ejpam-5923	284	27	distribution	distribution	NOUN
ejpam-5923	284	28	.	.	PUNCT
ejpam-5923	285	1	the	the	DET
ejpam-5923	285	2	simulation	simulation	NOUN
ejpam-5923	285	3	algorithm	algorithm	NOUN
ejpam-5923	285	4	is	be	AUX
ejpam-5923	285	5	given	give	VERB
ejpam-5923	285	6	as	as	SCONJ
ejpam-5923	285	7	follows	follow	VERB
ejpam-5923	285	8	:	:	PUNCT
ejpam-5923	285	9	steps	step	NOUN
ejpam-5923	285	10	description	description	NOUN
ejpam-5923	285	11	1	1	NUM
ejpam-5923	285	12	draw	draw	VERB
ejpam-5923	285	13	sample	sample	NOUN
ejpam-5923	285	14	of	of	ADP
ejpam-5923	285	15	size	size	NOUN
ejpam-5923	285	16	n	n	CCONJ
ejpam-5923	285	17	,	,	PUNCT
ejpam-5923	285	18	n	n	NOUN
ejpam-5923	285	19	=	=	SYM
ejpam-5923	285	20	50	50	NUM
ejpam-5923	285	21	,	,	PUNCT
ejpam-5923	285	22	100	100	NUM
ejpam-5923	285	23	,	,	PUNCT
ejpam-5923	285	24	200	200	NUM
ejpam-5923	285	25	,	,	PUNCT
ejpam-5923	285	26	500	500	NUM
ejpam-5923	285	27	,	,	PUNCT
ejpam-5923	285	28	800	800	NUM
ejpam-5923	285	29	,	,	PUNCT
ejpam-5923	285	30	1000	1000	NUM
ejpam-5923	285	31	,	,	PUNCT
ejpam-5923	285	32	from	from	ADP
ejpam-5923	285	33	a	a	DET
ejpam-5923	285	34	generalized	generalize	VERB
ejpam-5923	285	35	extended	extend	VERB
ejpam-5923	285	36	standard	standard	ADJ
ejpam-5923	285	37	u	u	NOUN
ejpam-5923	285	38	-	-	ADJ
ejpam-5923	285	39	quadratic	quadratic	ADJ
ejpam-5923	285	40	(	(	PUNCT
ejpam-5923	285	41	gesu	gesu	NOUN
ejpam-5923	285	42	)	)	PUNCT
ejpam-5923	285	43	distribution	distribution	NOUN
ejpam-5923	285	44	with	with	ADP
ejpam-5923	285	45	parameter	parameter	PROPN
ejpam-5923	285	46	λ	λ	PROPN
ejpam-5923	285	47	,	,	PUNCT
ejpam-5923	285	48	a	a	DET
ejpam-5923	285	49	using	use	VERB
ejpam-5923	285	50	the	the	DET
ejpam-5923	285	51	algorithm	algorithm	NOUN
ejpam-5923	285	52	given	give	VERB
ejpam-5923	285	53	in	in	ADP
ejpam-5923	285	54	previous	previous	ADJ
ejpam-5923	285	55	subsection	subsection	NOUN
ejpam-5923	285	56	.	.	PUNCT
ejpam-5923	286	1	2	2	NUM
ejpam-5923	286	2	using	use	VERB
ejpam-5923	286	3	the	the	DET
ejpam-5923	286	4	sample	sample	NOUN
ejpam-5923	286	5	x	x	PUNCT
ejpam-5923	286	6	obtained	obtain	VERB
ejpam-5923	286	7	in	in	ADP
ejpam-5923	286	8	step	step	NOUN
ejpam-5923	286	9	1	1	NUM
ejpam-5923	286	10	above	above	ADV
ejpam-5923	286	11	,	,	PUNCT
ejpam-5923	286	12	compute	compute	VERB
ejpam-5923	286	13	the	the	DET
ejpam-5923	286	14	maximum	maximum	ADJ
ejpam-5923	286	15	likelihood	likelihood	NOUN
ejpam-5923	286	16	estimate	estimate	NOUN
ejpam-5923	286	17	of	of	ADP
ejpam-5923	286	18	λ	λ	PROPN
ejpam-5923	286	19	and	and	CCONJ
ejpam-5923	286	20	a.	a.	NOUN
ejpam-5923	286	21	3	3	NUM
ejpam-5923	286	22	repeat	repeat	VERB
ejpam-5923	286	23	the	the	DET
ejpam-5923	286	24	preceding	precede	VERB
ejpam-5923	286	25	steps	step	NOUN
ejpam-5923	286	26	1	1	NUM
ejpam-5923	286	27	-	-	SYM
ejpam-5923	286	28	2	2	NUM
ejpam-5923	286	29	n	n	NOUN
ejpam-5923	286	30	=	=	SYM
ejpam-5923	286	31	1000	1000	NUM
ejpam-5923	286	32	times	time	NOUN
ejpam-5923	286	33	to	to	PART
ejpam-5923	286	34	get	get	VERB
ejpam-5923	286	35	1000	1000	NUM
ejpam-5923	286	36	estimates	estimate	NOUN
ejpam-5923	286	37	of	of	ADP
ejpam-5923	286	38	λ	λ	PROPN
ejpam-5923	286	39	and	and	CCONJ
ejpam-5923	286	40	a	a	PRON
ejpam-5923	286	41	,	,	PUNCT
ejpam-5923	286	42	respectively	respectively	ADV
ejpam-5923	286	43	.	.	PUNCT
ejpam-5923	287	1	4	4	NUM
ejpam-5923	287	2	compute	compute	VERB
ejpam-5923	287	3	the	the	DET
ejpam-5923	287	4	mean	mean	ADJ
ejpam-5923	287	5	,	,	PUNCT
ejpam-5923	287	6	bias	bias	NOUN
ejpam-5923	287	7	,	,	PUNCT
ejpam-5923	287	8	and	and	CCONJ
ejpam-5923	287	9	mean	mean	VERB
ejpam-5923	287	10	squared	square	VERB
ejpam-5923	287	11	error	error	NOUN
ejpam-5923	287	12	(	(	PUNCT
ejpam-5923	287	13	mse	mse	NOUN
ejpam-5923	287	14	)	)	PUNCT
ejpam-5923	287	15	of	of	ADP
ejpam-5923	287	16	the	the	DET
ejpam-5923	287	17	1000	1000	NUM
ejpam-5923	287	18	estimates	estimate	NOUN
ejpam-5923	287	19	obtained	obtain	VERB
ejpam-5923	287	20	in	in	ADP
ejpam-5923	287	21	step	step	NOUN
ejpam-5923	287	22	3	3	NUM
ejpam-5923	287	23	to	to	PART
ejpam-5923	287	24	get	get	VERB
ejpam-5923	287	25	the	the	DET
ejpam-5923	287	26	desired	desire	VERB
ejpam-5923	287	27	results	result	NOUN
ejpam-5923	287	28	.	.	PUNCT
ejpam-5923	288	1	the	the	DET
ejpam-5923	288	2	mean	mean	ADJ
ejpam-5923	288	3	(	(	PUNCT
ejpam-5923	288	4	ae	ae	PROPN
ejpam-5923	288	5	)	)	PUNCT
ejpam-5923	288	6	,	,	PUNCT
ejpam-5923	288	7	bias	bias	NOUN
ejpam-5923	288	8	,	,	PUNCT
ejpam-5923	288	9	and	and	CCONJ
ejpam-5923	288	10	mse	mse	PROPN
ejpam-5923	288	11	are	be	AUX
ejpam-5923	288	12	,	,	PUNCT
ejpam-5923	288	13	respectively	respectively	ADV
ejpam-5923	288	14	,	,	PUNCT
ejpam-5923	288	15	defined	define	VERB
ejpam-5923	288	16	by	by	ADP
ejpam-5923	288	17	ae	ae	PROPN
ejpam-5923	289	1	=	=	PROPN
ejpam-5923	289	2	n∑	n∑	PROPN
ejpam-5923	289	3	i=1	i=1	PROPN
ejpam-5923	289	4	θi	θi	ADP
ejpam-5923	289	5	n	n	PROPN
ejpam-5923	289	6	,	,	PUNCT
ejpam-5923	289	7	bias	bias	NOUN
ejpam-5923	289	8	=	=	SYM
ejpam-5923	289	9	ae	ae	PROPN
ejpam-5923	289	10	−	−	PROPN
ejpam-5923	289	11	θ	θ	PROPN
ejpam-5923	289	12	and	and	CCONJ
ejpam-5923	289	13	mse	mse	PROPN
ejpam-5923	289	14	=	=	SYM
ejpam-5923	289	15	n∑	n∑	PROPN
ejpam-5923	290	1	i=1	i=1	PROPN
ejpam-5923	290	2	(	(	PUNCT
ejpam-5923	290	3	θi	θi	NUM
ejpam-5923	290	4	−	−	PROPN
ejpam-5923	290	5	θ)2	θ)2	PROPN
ejpam-5923	290	6	n	n	NOUN
ejpam-5923	290	7	,	,	PUNCT
ejpam-5923	290	8	where	where	SCONJ
ejpam-5923	290	9	θi	θi	X
ejpam-5923	290	10	=	=	SYM
ejpam-5923	290	11	λi	λi	PROPN
ejpam-5923	290	12	,	,	PUNCT
ejpam-5923	290	13	ai	ai	VERB
ejpam-5923	290	14	,	,	PUNCT
ejpam-5923	290	15	and	and	CCONJ
ejpam-5923	290	16	θ	θ	PROPN
ejpam-5923	290	17	=	=	SYM
ejpam-5923	290	18	λ	λ	PROPN
ejpam-5923	290	19	,	,	PUNCT
ejpam-5923	290	20	a	a	PRON
ejpam-5923	290	21	,	,	PUNCT
ejpam-5923	290	22	respectively	respectively	ADV
ejpam-5923	290	23	.	.	PUNCT
ejpam-5923	291	1	i.	i.	PROPN
ejpam-5923	291	2	a.	a.	PROPN
ejpam-5923	291	3	lakibul	lakibul	PROPN
ejpam-5923	291	4	,	,	PUNCT
ejpam-5923	291	5	d.	d.	PROPN
ejpam-5923	291	6	l.	l.	PROPN
ejpam-5923	291	7	polestico	polestico	PROPN
ejpam-5923	291	8	,	,	PUNCT
ejpam-5923	291	9	a.	a.	PROPN
ejpam-5923	291	10	p.	p.	NOUN
ejpam-5923	291	11	supe	supe	PROPN
ejpam-5923	291	12	/	/	SYM
ejpam-5923	291	13	eur	eur	PROPN
ejpam-5923	291	14	.	.	PUNCT
ejpam-5923	292	1	j.	j.	PROPN
ejpam-5923	292	2	pure	pure	PROPN
ejpam-5923	292	3	appl	appl	PROPN
ejpam-5923	292	4	.	.	PROPN
ejpam-5923	292	5	math	math	PROPN
ejpam-5923	292	6	,	,	PUNCT
ejpam-5923	292	7	18	18	NUM
ejpam-5923	292	8	(	(	PUNCT
ejpam-5923	292	9	2	2	NUM
ejpam-5923	292	10	)	)	PUNCT
ejpam-5923	292	11	(	(	PUNCT
ejpam-5923	292	12	2025	2025	NUM
ejpam-5923	292	13	)	)	PUNCT
ejpam-5923	292	14	,	,	PUNCT
ejpam-5923	292	15	5923	5923	NUM
ejpam-5923	292	16	18	18	NUM
ejpam-5923	292	17	of	of	ADP
ejpam-5923	292	18	21	21	NUM
ejpam-5923	292	19	here	here	ADV
ejpam-5923	292	20	,	,	PUNCT
ejpam-5923	292	21	we	we	PRON
ejpam-5923	292	22	consider	consider	VERB
ejpam-5923	292	23	the	the	DET
ejpam-5923	292	24	following	follow	VERB
ejpam-5923	292	25	set	set	NOUN
ejpam-5923	292	26	of	of	ADP
ejpam-5923	292	27	values	value	NOUN
ejpam-5923	292	28	of	of	ADP
ejpam-5923	292	29	the	the	DET
ejpam-5923	292	30	parameters	parameter	NOUN
ejpam-5923	292	31	for	for	ADP
ejpam-5923	292	32	the	the	DET
ejpam-5923	292	33	b	b	PROPN
ejpam-5923	292	34	-	-	PUNCT
ejpam-5923	292	35	gesu	gesu	NOUN
ejpam-5923	292	36	distribution	distribution	NOUN
ejpam-5923	292	37	,	,	PUNCT
ejpam-5923	292	38	λ	λ	X
ejpam-5923	292	39	=	=	NOUN
ejpam-5923	292	40	0.7	0.7	NUM
ejpam-5923	292	41	and	and	CCONJ
ejpam-5923	292	42	a	a	DET
ejpam-5923	292	43	=	=	NUM
ejpam-5923	292	44	0.4	0.4	NUM
ejpam-5923	292	45	,	,	PUNCT
ejpam-5923	292	46	and	and	CCONJ
ejpam-5923	292	47	λ	λ	X
ejpam-5923	292	48	=	=	SYM
ejpam-5923	292	49	−0.3	−0.3	PROPN
ejpam-5923	292	50	and	and	CCONJ
ejpam-5923	292	51	a	a	PRON
ejpam-5923	292	52	=	=	SYM
ejpam-5923	292	53	0.4	0.4	NUM
ejpam-5923	292	54	.	.	PUNCT
ejpam-5923	292	55	table	table	NOUN
ejpam-5923	292	56	2	2	NUM
ejpam-5923	292	57	:	:	PUNCT
ejpam-5923	292	58	the	the	DET
ejpam-5923	292	59	average	average	NOUN
ejpam-5923	292	60	of	of	ADP
ejpam-5923	292	61	estimates	estimate	NOUN
ejpam-5923	292	62	(	(	PUNCT
ejpam-5923	292	63	ae	ae	PROPN
ejpam-5923	292	64	)	)	PUNCT
ejpam-5923	292	65	,	,	PUNCT
ejpam-5923	292	66	bias	bias	NOUN
ejpam-5923	292	67	and	and	CCONJ
ejpam-5923	292	68	mse	mse	NOUN
ejpam-5923	292	69	based	base	VERB
ejpam-5923	292	70	on	on	ADP
ejpam-5923	292	71	1,000	1,000	NUM
ejpam-5923	292	72	simulations	simulation	NOUN
ejpam-5923	292	73	of	of	ADP
ejpam-5923	292	74	the	the	DET
ejpam-5923	292	75	gesu	gesu	PROPN
ejpam-5923	292	76	distribution	distribution	NOUN
ejpam-5923	292	77	for	for	ADP
ejpam-5923	292	78	λ	λ	NOUN
ejpam-5923	292	79	=	=	NOUN
ejpam-5923	292	80	0.7	0.7	NUM
ejpam-5923	292	81	and	and	CCONJ
ejpam-5923	292	82	a	a	DET
ejpam-5923	292	83	=	=	NOUN
ejpam-5923	292	84	0.4	0.4	NUM
ejpam-5923	292	85	.	.	PUNCT
ejpam-5923	293	1	λ	λ	NOUN
ejpam-5923	293	2	=	=	NOUN
ejpam-5923	293	3	0.7	0.7	NUM
ejpam-5923	293	4	and	and	CCONJ
ejpam-5923	293	5	a	a	DET
ejpam-5923	293	6	=	=	SYM
ejpam-5923	293	7	0.4	0.4	NUM
ejpam-5923	293	8	n	n	NUM
ejpam-5923	293	9	mle	mle	PROPN
ejpam-5923	293	10	ae	ae	PROPN
ejpam-5923	293	11	bias	bias	PROPN
ejpam-5923	293	12	mse	mse	PROPN
ejpam-5923	293	13	50	50	NUM
ejpam-5923	293	14	λ̂	λ̂	NUM
ejpam-5923	293	15	0.799	0.799	NUM
ejpam-5923	293	16	0.099	0.099	NUM
ejpam-5923	293	17	0.017	0.017	NUM
ejpam-5923	293	18	100	100	NUM
ejpam-5923	293	19	λ̂	λ̂	NUM
ejpam-5923	293	20	0.771	0.771	NUM
ejpam-5923	293	21	0.071	0.071	NUM
ejpam-5923	293	22	0.009	0.009	NUM
ejpam-5923	293	23	200	200	NUM
ejpam-5923	293	24	λ̂	λ̂	NUM
ejpam-5923	293	25	0.750	0.750	NUM
ejpam-5923	293	26	0.050	0.050	NUM
ejpam-5923	293	27	0.004	0.004	NUM
ejpam-5923	293	28	500	500	NUM
ejpam-5923	293	29	λ̂	λ̂	NUM
ejpam-5923	293	30	0.735	0.735	NUM
ejpam-5923	293	31	0.035	0.035	NUM
ejpam-5923	293	32	0.002	0.002	NUM
ejpam-5923	293	33	800	800	NUM
ejpam-5923	293	34	λ̂	λ̂	NUM
ejpam-5923	293	35	0.733	0.733	NUM
ejpam-5923	293	36	0.033	0.033	NUM
ejpam-5923	293	37	0.002	0.002	NUM
ejpam-5923	293	38	1000	1000	NUM
ejpam-5923	293	39	λ̂	λ̂	NUM
ejpam-5923	293	40	0.732	0.732	NUM
ejpam-5923	293	41	0.032	0.032	NUM
ejpam-5923	293	42	0.002	0.002	NUM
ejpam-5923	293	43	50	50	NUM
ejpam-5923	293	44	â	â	ADP
ejpam-5923	293	45	0.393	0.393	NUM
ejpam-5923	293	46	−0.007	−0.007	NOUN
ejpam-5923	293	47	0.001	0.001	NUM
ejpam-5923	293	48	100	100	NUM
ejpam-5923	293	49	â	â	ADP
ejpam-5923	293	50	0.395	0.395	NUM
ejpam-5923	293	51	−0.005	−0.005	PROPN
ejpam-5923	293	52	0.001	0.001	NUM
ejpam-5923	293	53	200	200	NUM
ejpam-5923	293	54	â	â	ADP
ejpam-5923	293	55	0.397	0.397	NUM
ejpam-5923	293	56	−0.003	−0.003	NOUN
ejpam-5923	293	57	0.000	0.000	NUM
ejpam-5923	293	58	500	500	NUM
ejpam-5923	293	59	â	â	ADP
ejpam-5923	293	60	0.398	0.398	NUM
ejpam-5923	293	61	−0.002	−0.002	NOUN
ejpam-5923	293	62	0.000	0.000	NUM
ejpam-5923	293	63	800	800	NUM
ejpam-5923	293	64	â	â	ADP
ejpam-5923	293	65	0.400	0.400	NUM
ejpam-5923	293	66	0.000	0.000	NUM
ejpam-5923	293	67	0.000	0.000	NUM
ejpam-5923	293	68	1000	1000	NUM
ejpam-5923	293	69	â	â	ADP
ejpam-5923	293	70	0.400	0.400	NUM
ejpam-5923	293	71	0.000	0.000	NUM
ejpam-5923	293	72	0.000	0.000	NUM
ejpam-5923	293	73	table	table	NOUN
ejpam-5923	293	74	3	3	NUM
ejpam-5923	293	75	:	:	PUNCT
ejpam-5923	293	76	the	the	DET
ejpam-5923	293	77	average	average	NOUN
ejpam-5923	293	78	of	of	ADP
ejpam-5923	293	79	estimates	estimate	NOUN
ejpam-5923	293	80	(	(	PUNCT
ejpam-5923	293	81	ae	ae	PROPN
ejpam-5923	293	82	)	)	PUNCT
ejpam-5923	293	83	,	,	PUNCT
ejpam-5923	293	84	bias	bias	NOUN
ejpam-5923	293	85	and	and	CCONJ
ejpam-5923	293	86	mse	mse	NOUN
ejpam-5923	293	87	based	base	VERB
ejpam-5923	293	88	on	on	ADP
ejpam-5923	293	89	1,000	1,000	NUM
ejpam-5923	293	90	simulations	simulation	NOUN
ejpam-5923	293	91	of	of	ADP
ejpam-5923	293	92	the	the	DET
ejpam-5923	293	93	gesu	gesu	PROPN
ejpam-5923	293	94	distribution	distribution	NOUN
ejpam-5923	293	95	for	for	ADP
ejpam-5923	293	96	λ	λ	NOUN
ejpam-5923	293	97	=	=	SYM
ejpam-5923	293	98	−0.3	−0.3	PROPN
ejpam-5923	293	99	and	and	CCONJ
ejpam-5923	293	100	a	a	DET
ejpam-5923	293	101	=	=	NOUN
ejpam-5923	293	102	0.4	0.4	NUM
ejpam-5923	293	103	.	.	PUNCT
ejpam-5923	294	1	λ	λ	NOUN
ejpam-5923	294	2	=	=	SYM
ejpam-5923	294	3	−0.3	−0.3	PROPN
ejpam-5923	294	4	and	and	CCONJ
ejpam-5923	294	5	a	a	DET
ejpam-5923	294	6	=	=	SYM
ejpam-5923	294	7	0.4	0.4	NUM
ejpam-5923	294	8	n	n	NUM
ejpam-5923	294	9	mle	mle	PROPN
ejpam-5923	294	10	ae	ae	PROPN
ejpam-5923	294	11	bias	bias	PROPN
ejpam-5923	294	12	mse	mse	PROPN
ejpam-5923	294	13	50	50	NUM
ejpam-5923	294	14	λ̂	λ̂	NUM
ejpam-5923	294	15	−0.255	−0.255	PROPN
ejpam-5923	294	16	0.045	0.045	NUM
ejpam-5923	294	17	0.011	0.011	NUM
ejpam-5923	294	18	100	100	NUM
ejpam-5923	294	19	λ̂	λ̂	NUM
ejpam-5923	294	20	−0.277	−0.277	NOUN
ejpam-5923	294	21	0.023	0.023	NUM
ejpam-5923	294	22	0.003	0.003	NUM
ejpam-5923	294	23	200	200	NUM
ejpam-5923	294	24	λ̂	λ̂	NUM
ejpam-5923	294	25	−0.289	−0.289	PROPN
ejpam-5923	294	26	0.011	0.011	NUM
ejpam-5923	294	27	0.002	0.002	NUM
ejpam-5923	294	28	500	500	NUM
ejpam-5923	294	29	λ̂	λ̂	NUM
ejpam-5923	294	30	−0.301	−0.301	PROPN
ejpam-5923	294	31	−0.001	−0.001	NOUN
ejpam-5923	294	32	0.001	0.001	NUM
ejpam-5923	294	33	800	800	NUM
ejpam-5923	294	34	λ̂	λ̂	NUM
ejpam-5923	294	35	−0.305	−0.305	PROPN
ejpam-5923	294	36	−0.005	−0.005	PROPN
ejpam-5923	294	37	0.000	0.000	NUM
ejpam-5923	294	38	1000	1000	NUM
ejpam-5923	294	39	λ̂	λ̂	AUX
ejpam-5923	294	40	−0.306	−0.306	VERB
ejpam-5923	294	41	−0.006	−0.006	NOUN
ejpam-5923	294	42	0.000	0.000	NUM
ejpam-5923	294	43	50	50	NUM
ejpam-5923	294	44	â	â	ADP
ejpam-5923	294	45	0.379	0.379	NUM
ejpam-5923	294	46	−0.021	−0.021	NOUN
ejpam-5923	294	47	0.034	0.034	NUM
ejpam-5923	294	48	100	100	NUM
ejpam-5923	294	49	â	â	ADP
ejpam-5923	294	50	0.394	0.394	NUM
ejpam-5923	294	51	−0.006	−0.006	NOUN
ejpam-5923	294	52	0.010	0.010	NUM
ejpam-5923	294	53	200	200	NUM
ejpam-5923	294	54	â	â	ADP
ejpam-5923	294	55	0.415	0.415	NUM
ejpam-5923	294	56	0.015	0.015	NUM
ejpam-5923	294	57	0.003	0.003	NUM
ejpam-5923	294	58	500	500	NUM
ejpam-5923	294	59	â	â	ADP
ejpam-5923	294	60	0.421	0.421	NUM
ejpam-5923	294	61	0.021	0.021	NUM
ejpam-5923	294	62	0.001	0.001	NUM
ejpam-5923	294	63	800	800	NUM
ejpam-5923	294	64	â	â	ADP
ejpam-5923	294	65	0.422	0.422	NUM
ejpam-5923	294	66	0.022	0.022	NUM
ejpam-5923	294	67	0.001	0.001	NUM
ejpam-5923	294	68	1000	1000	NUM
ejpam-5923	294	69	â	â	ADP
ejpam-5923	294	70	0.421	0.421	NUM
ejpam-5923	294	71	0.021	0.021	NUM
ejpam-5923	294	72	0.001	0.001	NUM
ejpam-5923	294	73	the	the	DET
ejpam-5923	294	74	above	above	ADJ
ejpam-5923	294	75	tables	table	NOUN
ejpam-5923	294	76	show	show	VERB
ejpam-5923	294	77	the	the	DET
ejpam-5923	294	78	behavior	behavior	NOUN
ejpam-5923	294	79	of	of	ADP
ejpam-5923	294	80	the	the	DET
ejpam-5923	294	81	ml	ml	NOUN
ejpam-5923	294	82	estimates	estimate	NOUN
ejpam-5923	294	83	of	of	ADP
ejpam-5923	294	84	the	the	DET
ejpam-5923	294	85	gesu	gesu	PROPN
ejpam-5923	294	86	distribution	distribution	NOUN
ejpam-5923	294	87	parameters	parameter	NOUN
ejpam-5923	294	88	as	as	ADP
ejpam-5923	294	89	the	the	DET
ejpam-5923	294	90	sample	sample	NOUN
ejpam-5923	294	91	size	size	NOUN
ejpam-5923	294	92	n	n	VERB
ejpam-5923	294	93	becomes	become	VERB
ejpam-5923	294	94	large	large	ADJ
ejpam-5923	294	95	.	.	PUNCT
ejpam-5923	295	1	it	it	PRON
ejpam-5923	295	2	reveals	reveal	VERB
ejpam-5923	295	3	that	that	SCONJ
ejpam-5923	295	4	the	the	DET
ejpam-5923	295	5	ml	ml	NOUN
ejpam-5923	295	6	estimates	estimate	NOUN
ejpam-5923	295	7	of	of	ADP
ejpam-5923	295	8	the	the	DET
ejpam-5923	295	9	said	say	VERB
ejpam-5923	295	10	distribution	distribution	NOUN
ejpam-5923	295	11	parameters	parameter	NOUN
ejpam-5923	295	12	is	be	AUX
ejpam-5923	295	13	consistent	consistent	ADJ
ejpam-5923	295	14	for	for	ADP
ejpam-5923	295	15	all	all	DET
ejpam-5923	295	16	parameters	parameter	NOUN
ejpam-5923	295	17	since	since	SCONJ
ejpam-5923	295	18	the	the	DET
ejpam-5923	295	19	mse	mse	NOUN
ejpam-5923	295	20	decays	decay	VERB
ejpam-5923	295	21	toward	toward	ADP
ejpam-5923	295	22	zero	zero	NUM
ejpam-5923	295	23	.	.	PUNCT
ejpam-5923	296	1	a	a	DET
ejpam-5923	296	2	faster	fast	ADJ
ejpam-5923	296	3	rate	rate	NOUN
ejpam-5923	296	4	of	of	ADP
ejpam-5923	296	5	convergence	convergence	NOUN
ejpam-5923	296	6	of	of	ADP
ejpam-5923	296	7	the	the	DET
ejpam-5923	296	8	parameter	parameter	NOUN
ejpam-5923	296	9	estimates	estimate	NOUN
ejpam-5923	296	10	of	of	ADP
ejpam-5923	296	11	a	a	PRON
ejpam-5923	296	12	is	be	AUX
ejpam-5923	296	13	observed	observe	VERB
ejpam-5923	296	14	.	.	PUNCT
ejpam-5923	297	1	i.	i.	PROPN
ejpam-5923	297	2	a.	a.	PROPN
ejpam-5923	297	3	lakibul	lakibul	PROPN
ejpam-5923	297	4	,	,	PUNCT
ejpam-5923	297	5	d.	d.	PROPN
ejpam-5923	297	6	l.	l.	PROPN
ejpam-5923	297	7	polestico	polestico	PROPN
ejpam-5923	297	8	,	,	PUNCT
ejpam-5923	297	9	a.	a.	PROPN
ejpam-5923	297	10	p.	p.	NOUN
ejpam-5923	297	11	supe	supe	PROPN
ejpam-5923	297	12	/	/	SYM
ejpam-5923	297	13	eur	eur	PROPN
ejpam-5923	297	14	.	.	PUNCT
ejpam-5923	298	1	j.	j.	PROPN
ejpam-5923	298	2	pure	pure	PROPN
ejpam-5923	298	3	appl	appl	PROPN
ejpam-5923	298	4	.	.	PROPN
ejpam-5923	298	5	math	math	PROPN
ejpam-5923	298	6	,	,	PUNCT
ejpam-5923	298	7	18	18	NUM
ejpam-5923	298	8	(	(	PUNCT
ejpam-5923	298	9	2	2	NUM
ejpam-5923	298	10	)	)	PUNCT
ejpam-5923	298	11	(	(	PUNCT
ejpam-5923	298	12	2025	2025	NUM
ejpam-5923	298	13	)	)	PUNCT
ejpam-5923	298	14	,	,	PUNCT
ejpam-5923	298	15	5923	5923	NUM
ejpam-5923	298	16	19	19	NUM
ejpam-5923	298	17	of	of	ADP
ejpam-5923	298	18	21	21	NUM
ejpam-5923	298	19	7	7	NUM
ejpam-5923	298	20	.	.	PUNCT
ejpam-5923	298	21	application	application	NOUN
ejpam-5923	298	22	in	in	ADP
ejpam-5923	298	23	this	this	DET
ejpam-5923	298	24	section	section	NOUN
ejpam-5923	298	25	,	,	PUNCT
ejpam-5923	298	26	we	we	PRON
ejpam-5923	298	27	apply	apply	VERB
ejpam-5923	298	28	the	the	DET
ejpam-5923	298	29	gesu	gesu	PROPN
ejpam-5923	298	30	distribution	distribution	NOUN
ejpam-5923	298	31	into	into	ADP
ejpam-5923	298	32	a	a	DET
ejpam-5923	298	33	real	real	ADJ
ejpam-5923	298	34	dataset	dataset	NOUN
ejpam-5923	298	35	and	and	CCONJ
ejpam-5923	298	36	compare	compare	VERB
ejpam-5923	298	37	with	with	ADP
ejpam-5923	298	38	the	the	DET
ejpam-5923	298	39	esu	esu	NOUN
ejpam-5923	298	40	distribution	distribution	NOUN
ejpam-5923	298	41	.	.	PUNCT
ejpam-5923	299	1	also	also	ADV
ejpam-5923	299	2	,	,	PUNCT
ejpam-5923	299	3	we	we	PRON
ejpam-5923	299	4	compare	compare	VERB
ejpam-5923	299	5	the	the	DET
ejpam-5923	299	6	gesu	gesu	NOUN
ejpam-5923	299	7	distribution	distribution	NOUN
ejpam-5923	299	8	with	with	ADP
ejpam-5923	299	9	the	the	DET
ejpam-5923	299	10	following	follow	VERB
ejpam-5923	299	11	distributions	distribution	NOUN
ejpam-5923	299	12	:	:	PUNCT
ejpam-5923	299	13	•	•	NUM
ejpam-5923	299	14	unitrayleigh	unitrayleigh	ADJ
ejpam-5923	299	15	(	(	PUNCT
ejpam-5923	299	16	ur	ur	NOUN
ejpam-5923	299	17	)	)	PUNCT
ejpam-5923	299	18	distribution	distribution	NOUN
ejpam-5923	299	19	[	[	X
ejpam-5923	299	20	3	3	X
ejpam-5923	299	21	]	]	PUNCT
ejpam-5923	299	22	f(x	f(x	PROPN
ejpam-5923	299	23	)	)	PUNCT
ejpam-5923	299	24	=	=	PUNCT
ejpam-5923	300	1	−2α	−2α	PROPN
ejpam-5923	300	2	x	x	PUNCT
ejpam-5923	300	3	log(x)e−α(log(x))2	log(x)e−α(log(x))2	NOUN
ejpam-5923	300	4	,	,	PUNCT
ejpam-5923	300	5	where	where	SCONJ
ejpam-5923	300	6	x	x	X
ejpam-5923	300	7	∈	∈	PROPN
ejpam-5923	300	8	(	(	PUNCT
ejpam-5923	300	9	0	0	NUM
ejpam-5923	300	10	,	,	PUNCT
ejpam-5923	300	11	1	1	NUM
ejpam-5923	300	12	)	)	PUNCT
ejpam-5923	300	13	and	and	CCONJ
ejpam-5923	300	14	α	α	X
ejpam-5923	300	15	>	>	X
ejpam-5923	300	16	0	0	NUM
ejpam-5923	300	17	.	.	NOUN
ejpam-5923	300	18	•	•	PROPN
ejpam-5923	300	19	unit	unit	NOUN
ejpam-5923	300	20	burr	burr	PROPN
ejpam-5923	300	21	xii	xii	PROPN
ejpam-5923	300	22	(	(	PUNCT
ejpam-5923	300	23	ubxii	ubxii	NOUN
ejpam-5923	300	24	)	)	PUNCT
ejpam-5923	300	25	distribution	distribution	NOUN
ejpam-5923	301	1	[	[	X
ejpam-5923	301	2	10	10	NUM
ejpam-5923	301	3	]	]	X
ejpam-5923	301	4	f(x	f(x	PROPN
ejpam-5923	301	5	)	)	PUNCT
ejpam-5923	302	1	=	=	SYM
ejpam-5923	302	2	αβx−1(−	αβx−1(−	PROPN
ejpam-5923	302	3	log(x))β−1(1	log(x))β−1(1	ADJ
ejpam-5923	302	4	+	+	ADJ
ejpam-5923	302	5	(	(	PUNCT
ejpam-5923	302	6	−	−	PROPN
ejpam-5923	302	7	log(x))β)−α−1	log(x))β)−α−1	PROPN
ejpam-5923	302	8	,	,	PUNCT
ejpam-5923	302	9	where	where	SCONJ
ejpam-5923	302	10	x	x	X
ejpam-5923	302	11	∈	∈	PROPN
ejpam-5923	302	12	(	(	PUNCT
ejpam-5923	302	13	0	0	NUM
ejpam-5923	302	14	,	,	PUNCT
ejpam-5923	302	15	1	1	NUM
ejpam-5923	302	16	)	)	PUNCT
ejpam-5923	302	17	,	,	PUNCT
ejpam-5923	302	18	α	α	PROPN
ejpam-5923	302	19	>	>	X
ejpam-5923	302	20	0	0	PUNCT
ejpam-5923	302	21	and	and	CCONJ
ejpam-5923	302	22	β	β	X
ejpam-5923	302	23	>	>	X
ejpam-5923	302	24	0	0	X
ejpam-5923	302	25	.	.	PUNCT
ejpam-5923	303	1	here	here	ADV
ejpam-5923	303	2	,	,	PUNCT
ejpam-5923	303	3	we	we	PRON
ejpam-5923	303	4	use	use	VERB
ejpam-5923	303	5	a	a	DET
ejpam-5923	303	6	dataset	dataset	NOUN
ejpam-5923	303	7	from	from	ADP
ejpam-5923	303	8	the	the	DET
ejpam-5923	303	9	study	study	NOUN
ejpam-5923	303	10	of	of	ADP
ejpam-5923	303	11	quesenberry	quesenberry	NOUN
ejpam-5923	303	12	and	and	CCONJ
ejpam-5923	303	13	hales	hale	NOUN
ejpam-5923	303	14	[	[	X
ejpam-5923	303	15	11	11	NUM
ejpam-5923	303	16	]	]	PUNCT
ejpam-5923	303	17	.	.	PUNCT
ejpam-5923	304	1	this	this	DET
ejpam-5923	304	2	dataset	dataset	NOUN
ejpam-5923	304	3	is	be	AUX
ejpam-5923	304	4	related	relate	VERB
ejpam-5923	304	5	to	to	ADP
ejpam-5923	304	6	30	30	NUM
ejpam-5923	304	7	measurements	measurement	NOUN
ejpam-5923	304	8	of	of	ADP
ejpam-5923	304	9	tensile	tensile	NOUN
ejpam-5923	304	10	strength	strength	NOUN
ejpam-5923	304	11	of	of	ADP
ejpam-5923	304	12	polyester	polyester	NOUN
ejpam-5923	304	13	fibers	fiber	NOUN
ejpam-5923	304	14	.	.	PUNCT
ejpam-5923	305	1	the	the	DET
ejpam-5923	305	2	observations	observation	NOUN
ejpam-5923	305	3	are	be	AUX
ejpam-5923	305	4	given	give	VERB
ejpam-5923	305	5	as	as	ADP
ejpam-5923	305	6	follow	follow	NOUN
ejpam-5923	305	7	:	:	PUNCT
ejpam-5923	305	8	0.023	0.023	NUM
ejpam-5923	305	9	,	,	PUNCT
ejpam-5923	305	10	0.032	0.032	NUM
ejpam-5923	305	11	,	,	PUNCT
ejpam-5923	305	12	0.054	0.054	NUM
ejpam-5923	305	13	,	,	PUNCT
ejpam-5923	305	14	0.069	0.069	NUM
ejpam-5923	305	15	,	,	PUNCT
ejpam-5923	305	16	0.081	0.081	NUM
ejpam-5923	305	17	,	,	PUNCT
ejpam-5923	305	18	0.094	0.094	NUM
ejpam-5923	305	19	,	,	PUNCT
ejpam-5923	305	20	0.105	0.105	NUM
ejpam-5923	305	21	,	,	PUNCT
ejpam-5923	305	22	0.127	0.127	NUM
ejpam-5923	305	23	,	,	PUNCT
ejpam-5923	305	24	0.148	0.148	NUM
ejpam-5923	305	25	,	,	PUNCT
ejpam-5923	305	26	0.169	0.169	NUM
ejpam-5923	305	27	,	,	PUNCT
ejpam-5923	305	28	0.188	0.188	NUM
ejpam-5923	305	29	,	,	PUNCT
ejpam-5923	305	30	0.216	0.216	NUM
ejpam-5923	305	31	,	,	PUNCT
ejpam-5923	305	32	0.255	0.255	NUM
ejpam-5923	305	33	,	,	PUNCT
ejpam-5923	305	34	0.277	0.277	NUM
ejpam-5923	305	35	,	,	PUNCT
ejpam-5923	305	36	0.311	0.311	NUM
ejpam-5923	305	37	,	,	PUNCT
ejpam-5923	305	38	0.361	0.361	NUM
ejpam-5923	305	39	,	,	PUNCT
ejpam-5923	305	40	0.376	0.376	NUM
ejpam-5923	305	41	,	,	PUNCT
ejpam-5923	305	42	0.395	0.395	NUM
ejpam-5923	305	43	,	,	PUNCT
ejpam-5923	305	44	0.432	0.432	NUM
ejpam-5923	305	45	,	,	PUNCT
ejpam-5923	305	46	0.463	0.463	NUM
ejpam-5923	305	47	,	,	PUNCT
ejpam-5923	305	48	0.481	0.481	NUM
ejpam-5923	305	49	,	,	PUNCT
ejpam-5923	305	50	0.519	0.519	NUM
ejpam-5923	305	51	,	,	PUNCT
ejpam-5923	305	52	0.529	0.529	NUM
ejpam-5923	305	53	,	,	PUNCT
ejpam-5923	305	54	0.567	0.567	NUM
ejpam-5923	305	55	,	,	PUNCT
ejpam-5923	305	56	0.642	0.642	NUM
ejpam-5923	305	57	,	,	PUNCT
ejpam-5923	305	58	0.674	0.674	NUM
ejpam-5923	305	59	,	,	PUNCT
ejpam-5923	305	60	0.752	0.752	NUM
ejpam-5923	305	61	,	,	PUNCT
ejpam-5923	305	62	0.823	0.823	NUM
ejpam-5923	305	63	,	,	PUNCT
ejpam-5923	305	64	0.887	0.887	NUM
ejpam-5923	305	65	,	,	PUNCT
ejpam-5923	305	66	0.926	0.926	NUM
ejpam-5923	305	67	.	.	PUNCT
ejpam-5923	306	1	in	in	ADP
ejpam-5923	306	2	this	this	DET
ejpam-5923	306	3	application	application	NOUN
ejpam-5923	306	4	,	,	PUNCT
ejpam-5923	306	5	we	we	PRON
ejpam-5923	306	6	use	use	VERB
ejpam-5923	306	7	the	the	DET
ejpam-5923	306	8	following	follow	VERB
ejpam-5923	306	9	diagnostic	diagnostic	ADJ
ejpam-5923	306	10	statistics	statistic	NOUN
ejpam-5923	306	11	,	,	PUNCT
ejpam-5923	306	12	namely	namely	ADV
ejpam-5923	306	13	,	,	PUNCT
ejpam-5923	306	14	the	the	DET
ejpam-5923	306	15	akaike	akaike	ADJ
ejpam-5923	306	16	information	information	NOUN
ejpam-5923	306	17	criterion	criterion	NOUN
ejpam-5923	306	18	(	(	PUNCT
ejpam-5923	306	19	aic	aic	PROPN
ejpam-5923	306	20	)	)	PUNCT
ejpam-5923	306	21	,	,	PUNCT
ejpam-5923	306	22	bayesian	bayesian	NOUN
ejpam-5923	306	23	information	information	NOUN
ejpam-5923	306	24	criterion	criterion	NOUN
ejpam-5923	306	25	(	(	PUNCT
ejpam-5923	306	26	bic	bic	NOUN
ejpam-5923	306	27	)	)	PUNCT
ejpam-5923	306	28	,	,	PUNCT
ejpam-5923	306	29	and	and	CCONJ
ejpam-5923	306	30	kolmogorov	kolmogorov	PROPN
ejpam-5923	306	31	smirnov	smirnov	PROPN
ejpam-5923	306	32	(	(	PUNCT
ejpam-5923	306	33	k	k	NOUN
ejpam-5923	306	34	-	-	PUNCT
ejpam-5923	306	35	s	s	NOUN
ejpam-5923	306	36	)	)	PUNCT
ejpam-5923	306	37	as	as	ADP
ejpam-5923	306	38	the	the	DET
ejpam-5923	306	39	basis	basis	NOUN
ejpam-5923	306	40	for	for	ADP
ejpam-5923	306	41	comparing	compare	VERB
ejpam-5923	306	42	the	the	DET
ejpam-5923	306	43	proposed	propose	VERB
ejpam-5923	306	44	distribution	distribution	NOUN
ejpam-5923	306	45	with	with	ADP
ejpam-5923	306	46	the	the	DET
ejpam-5923	306	47	said	say	VERB
ejpam-5923	306	48	competing	compete	VERB
ejpam-5923	306	49	distributions	distribution	NOUN
ejpam-5923	306	50	.	.	PUNCT
ejpam-5923	307	1	the	the	DET
ejpam-5923	307	2	model	model	NOUN
ejpam-5923	307	3	which	which	PRON
ejpam-5923	307	4	has	have	VERB
ejpam-5923	307	5	the	the	DET
ejpam-5923	307	6	smallest	small	ADJ
ejpam-5923	307	7	values	value	NOUN
ejpam-5923	307	8	of	of	ADP
ejpam-5923	307	9	the	the	DET
ejpam-5923	307	10	said	say	VERB
ejpam-5923	307	11	diagnostic	diagnostic	ADJ
ejpam-5923	307	12	statistics	statistic	NOUN
ejpam-5923	307	13	is	be	AUX
ejpam-5923	307	14	chosen	choose	VERB
ejpam-5923	307	15	to	to	PART
ejpam-5923	307	16	be	be	AUX
ejpam-5923	307	17	the	the	DET
ejpam-5923	307	18	best	good	ADJ
ejpam-5923	307	19	model	model	NOUN
ejpam-5923	307	20	for	for	ADP
ejpam-5923	307	21	the	the	DET
ejpam-5923	307	22	data	datum	NOUN
ejpam-5923	307	23	.	.	PUNCT
ejpam-5923	308	1	in	in	ADP
ejpam-5923	308	2	addition	addition	NOUN
ejpam-5923	308	3	,	,	PUNCT
ejpam-5923	308	4	we	we	PRON
ejpam-5923	308	5	use	use	VERB
ejpam-5923	308	6	a	a	DET
ejpam-5923	308	7	package	package	NOUN
ejpam-5923	308	8	”	"	PUNCT
ejpam-5923	308	9	fitdistrplus	fitdistrplus	NOUN
ejpam-5923	308	10	”	"	PUNCT
ejpam-5923	308	11	in	in	ADP
ejpam-5923	308	12	r	r	NOUN
ejpam-5923	308	13	software	software	NOUN
ejpam-5923	308	14	to	to	PART
ejpam-5923	308	15	perform	perform	VERB
ejpam-5923	308	16	the	the	DET
ejpam-5923	308	17	analysis	analysis	NOUN
ejpam-5923	308	18	of	of	ADP
ejpam-5923	308	19	the	the	DET
ejpam-5923	308	20	data	datum	NOUN
ejpam-5923	308	21	.	.	PUNCT
ejpam-5923	309	1	table	table	NOUN
ejpam-5923	309	2	4	4	NUM
ejpam-5923	309	3	:	:	PUNCT
ejpam-5923	309	4	estimates	estimate	NOUN
ejpam-5923	309	5	and	and	CCONJ
ejpam-5923	309	6	some	some	DET
ejpam-5923	309	7	diagnostic	diagnostic	ADJ
ejpam-5923	309	8	values	value	NOUN
ejpam-5923	309	9	of	of	ADP
ejpam-5923	309	10	the	the	DET
ejpam-5923	309	11	fitted	fit	VERB
ejpam-5923	309	12	models	model	NOUN
ejpam-5923	309	13	for	for	ADP
ejpam-5923	309	14	the	the	DET
ejpam-5923	309	15	given	give	VERB
ejpam-5923	309	16	dataset	dataset	NOUN
ejpam-5923	309	17	.	.	PUNCT
ejpam-5923	310	1	distribution	distribution	NOUN
ejpam-5923	310	2	estimate	estimate	NOUN
ejpam-5923	310	3	loglik	loglik	NOUN
ejpam-5923	310	4	aic	aic	PROPN
ejpam-5923	310	5	bic	bic	PROPN
ejpam-5923	311	1	k	k	PROPN
ejpam-5923	312	1	−	−	PROPN
ejpam-5923	312	2	s	s	PART
ejpam-5923	312	3	gesu	gesu	NOUN
ejpam-5923	312	4	λ̂	λ̂	X
ejpam-5923	313	1	=	=	SYM
ejpam-5923	313	2	0.5426148	0.5426148	NUM
ejpam-5923	313	3	3.250599	3.250599	NUM
ejpam-5923	313	4	-2.501198	-2.501198	NOUN
ejpam-5923	313	5	0.3011964	0.3011964	NUM
ejpam-5923	313	6	0.06615338	0.06615338	NUM
ejpam-5923	313	7	â	â	ADP
ejpam-5923	313	8	=	=	SYM
ejpam-5923	313	9	1.0000000	1.0000000	NUM
ejpam-5923	313	10	esu	esu	NOUN
ejpam-5923	313	11	λ̂	λ̂	X
ejpam-5923	313	12	=	=	PUNCT
ejpam-5923	313	13	0.06649717	0.06649717	NUM
ejpam-5923	313	14	0.05187171	0.05187171	NUM
ejpam-5923	313	15	1.896257	1.896257	NUM
ejpam-5923	313	16	3.297454	3.297454	NUM
ejpam-5923	313	17	0.23958860	0.23958860	NUM
ejpam-5923	313	18	ur	ur	INTJ
ejpam-5923	313	19	α̂	α̂	NUM
ejpam-5923	313	20	=	=	NOUN
ejpam-5923	313	21	0.3481808	0.3481808	NUM
ejpam-5923	313	22	−0.271881	−0.271881	SYM
ejpam-5923	313	23	2.543762	2.543762	NUM
ejpam-5923	313	24	3.944959	3.944959	NUM
ejpam-5923	313	25	0.19666520	0.19666520	NUM
ejpam-5923	313	26	ubxii	ubxii	NOUN
ejpam-5923	313	27	α̂	α̂	NUM
ejpam-5923	313	28	=	=	PUNCT
ejpam-5923	313	29	1.033106	1.033106	NUM
ejpam-5923	313	30	1.038986	1.038986	NUM
ejpam-5923	313	31	1.922029	1.922029	NUM
ejpam-5923	313	32	4.724423	4.724423	NUM
ejpam-5923	313	33	0.09925780	0.09925780	NUM
ejpam-5923	313	34	β̂	β̂	ADP
ejpam-5923	313	35	=	=	SYM
ejpam-5923	313	36	1.846484	1.846484	NUM
ejpam-5923	313	37	table	table	NOUN
ejpam-5923	313	38	4	4	NUM
ejpam-5923	313	39	lists	list	NOUN
ejpam-5923	313	40	the	the	DET
ejpam-5923	313	41	ml	ml	NOUN
ejpam-5923	313	42	estimates	estimate	NOUN
ejpam-5923	313	43	and	and	CCONJ
ejpam-5923	313	44	the	the	DET
ejpam-5923	313	45	result	result	NOUN
ejpam-5923	313	46	of	of	ADP
ejpam-5923	313	47	the	the	DET
ejpam-5923	313	48	said	say	VERB
ejpam-5923	313	49	diagnostics	diagnostic	NOUN
ejpam-5923	313	50	statistics	statistic	NOUN
ejpam-5923	313	51	of	of	ADP
ejpam-5923	313	52	the	the	DET
ejpam-5923	313	53	fitted	fit	VERB
ejpam-5923	313	54	models	model	NOUN
ejpam-5923	313	55	for	for	ADP
ejpam-5923	313	56	the	the	DET
ejpam-5923	313	57	said	say	VERB
ejpam-5923	313	58	dataset	dataset	NOUN
ejpam-5923	313	59	and	and	CCONJ
ejpam-5923	313	60	it	it	PRON
ejpam-5923	313	61	suggests	suggest	VERB
ejpam-5923	313	62	that	that	SCONJ
ejpam-5923	313	63	the	the	DET
ejpam-5923	313	64	proposed	propose	VERB
ejpam-5923	313	65	distribution	distribution	NOUN
ejpam-5923	313	66	is	be	AUX
ejpam-5923	313	67	selected	select	VERB
ejpam-5923	313	68	to	to	PART
ejpam-5923	313	69	be	be	AUX
ejpam-5923	313	70	a	a	DET
ejpam-5923	313	71	best	good	ADJ
ejpam-5923	313	72	model	model	NOUN
ejpam-5923	313	73	for	for	ADP
ejpam-5923	313	74	the	the	DET
ejpam-5923	313	75	said	say	VERB
ejpam-5923	313	76	dataset	dataset	NOUN
ejpam-5923	313	77	since	since	SCONJ
ejpam-5923	313	78	it	it	PRON
ejpam-5923	313	79	has	have	VERB
ejpam-5923	313	80	the	the	DET
ejpam-5923	313	81	smallest	small	ADJ
ejpam-5923	313	82	values	value	NOUN
ejpam-5923	313	83	of	of	ADP
ejpam-5923	313	84	aic	aic	PROPN
ejpam-5923	313	85	,	,	PUNCT
ejpam-5923	313	86	bic	bic	PROPN
ejpam-5923	313	87	,	,	PUNCT
ejpam-5923	313	88	and	and	CCONJ
ejpam-5923	313	89	i.	i.	PROPN
ejpam-5923	313	90	a.	a.	PROPN
ejpam-5923	313	91	lakibul	lakibul	PROPN
ejpam-5923	313	92	,	,	PUNCT
ejpam-5923	313	93	d.	d.	PROPN
ejpam-5923	313	94	l.	l.	PROPN
ejpam-5923	313	95	polestico	polestico	PROPN
ejpam-5923	313	96	,	,	PUNCT
ejpam-5923	313	97	a.	a.	PROPN
ejpam-5923	313	98	p.	p.	NOUN
ejpam-5923	313	99	supe	supe	PROPN
ejpam-5923	313	100	/	/	SYM
ejpam-5923	313	101	eur	eur	PROPN
ejpam-5923	313	102	.	.	PUNCT
ejpam-5923	314	1	j.	j.	PROPN
ejpam-5923	314	2	pure	pure	PROPN
ejpam-5923	314	3	appl	appl	PROPN
ejpam-5923	314	4	.	.	PROPN
ejpam-5923	314	5	math	math	PROPN
ejpam-5923	314	6	,	,	PUNCT
ejpam-5923	314	7	18	18	NUM
ejpam-5923	314	8	(	(	PUNCT
ejpam-5923	314	9	2	2	NUM
ejpam-5923	314	10	)	)	PUNCT
ejpam-5923	314	11	(	(	PUNCT
ejpam-5923	314	12	2025	2025	NUM
ejpam-5923	314	13	)	)	PUNCT
ejpam-5923	314	14	,	,	PUNCT
ejpam-5923	314	15	5923	5923	NUM
ejpam-5923	314	16	20	20	NUM
ejpam-5923	314	17	of	of	ADP
ejpam-5923	314	18	21	21	NUM
ejpam-5923	314	19	k	k	NOUN
ejpam-5923	314	20	-	-	PUNCT
ejpam-5923	314	21	s	s	PRON
ejpam-5923	314	22	as	as	SCONJ
ejpam-5923	314	23	compared	compare	VERB
ejpam-5923	314	24	with	with	ADP
ejpam-5923	314	25	the	the	DET
ejpam-5923	314	26	esu	esu	NOUN
ejpam-5923	314	27	,	,	PUNCT
ejpam-5923	314	28	ur	ur	INTJ
ejpam-5923	314	29	and	and	CCONJ
ejpam-5923	314	30	ubxii	ubxii	PROPN
ejpam-5923	314	31	distributions	distribution	NOUN
ejpam-5923	314	32	.	.	PUNCT
ejpam-5923	315	1	moreover	moreover	ADV
ejpam-5923	315	2	,	,	PUNCT
ejpam-5923	315	3	the	the	DET
ejpam-5923	315	4	results	result	NOUN
ejpam-5923	315	5	of	of	ADP
ejpam-5923	315	6	the	the	DET
ejpam-5923	315	7	k	k	PROPN
ejpam-5923	315	8	-	-	PUNCT
ejpam-5923	315	9	s	s	PART
ejpam-5923	315	10	statistic	statistic	NOUN
ejpam-5923	315	11	are	be	AUX
ejpam-5923	315	12	consistent	consistent	ADJ
ejpam-5923	315	13	with	with	ADP
ejpam-5923	315	14	values	value	NOUN
ejpam-5923	315	15	of	of	ADP
ejpam-5923	315	16	the	the	DET
ejpam-5923	315	17	aic	aic	PROPN
ejpam-5923	315	18	and	and	CCONJ
ejpam-5923	315	19	bic	bic	PROPN
ejpam-5923	315	20	.	.	PUNCT
ejpam-5923	316	1	in	in	ADP
ejpam-5923	316	2	addition	addition	NOUN
ejpam-5923	316	3	,	,	PUNCT
ejpam-5923	316	4	the	the	DET
ejpam-5923	316	5	plot	plot	NOUN
ejpam-5923	316	6	of	of	ADP
ejpam-5923	316	7	the	the	DET
ejpam-5923	316	8	fitted	fit	VERB
ejpam-5923	316	9	models	model	NOUN
ejpam-5923	316	10	for	for	ADP
ejpam-5923	316	11	the	the	DET
ejpam-5923	316	12	given	give	VERB
ejpam-5923	316	13	dataset	dataset	NOUN
ejpam-5923	316	14	is	be	AUX
ejpam-5923	316	15	given	give	VERB
ejpam-5923	316	16	in	in	ADP
ejpam-5923	316	17	the	the	DET
ejpam-5923	316	18	following	follow	VERB
ejpam-5923	316	19	figure	figure	NOUN
ejpam-5923	316	20	8	8	NUM
ejpam-5923	316	21	and	and	CCONJ
ejpam-5923	316	22	same	same	ADJ
ejpam-5923	316	23	result	result	NOUN
ejpam-5923	316	24	is	be	AUX
ejpam-5923	316	25	observed	observe	VERB
ejpam-5923	316	26	.	.	PUNCT
ejpam-5923	317	1	figure	figure	VERB
ejpam-5923	317	2	8	8	NUM
ejpam-5923	317	3	:	:	PUNCT
ejpam-5923	317	4	estimated	estimated	ADJ
ejpam-5923	317	5	pdf	pdf	NOUN
ejpam-5923	317	6	of	of	ADP
ejpam-5923	317	7	the	the	DET
ejpam-5923	317	8	fitted	fit	VERB
ejpam-5923	317	9	models	model	NOUN
ejpam-5923	317	10	for	for	ADP
ejpam-5923	317	11	the	the	DET
ejpam-5923	317	12	given	give	VERB
ejpam-5923	317	13	data	datum	NOUN
ejpam-5923	317	14	.	.	PUNCT
ejpam-5923	318	1	8	8	X
ejpam-5923	318	2	.	.	PUNCT
ejpam-5923	318	3	conclusions	conclusion	NOUN
ejpam-5923	318	4	and	and	CCONJ
ejpam-5923	318	5	recommendations	recommendation	NOUN
ejpam-5923	318	6	in	in	ADP
ejpam-5923	318	7	this	this	DET
ejpam-5923	318	8	paper	paper	NOUN
ejpam-5923	318	9	,	,	PUNCT
ejpam-5923	318	10	the	the	DET
ejpam-5923	318	11	generalized	generalized	ADJ
ejpam-5923	318	12	version	version	NOUN
ejpam-5923	318	13	of	of	ADP
ejpam-5923	318	14	the	the	DET
ejpam-5923	318	15	extended	extended	ADJ
ejpam-5923	318	16	standard	standard	ADJ
ejpam-5923	318	17	u	u	ADJ
ejpam-5923	318	18	-	-	ADJ
ejpam-5923	318	19	quadratic	quadratic	ADJ
ejpam-5923	318	20	distribution	distribution	NOUN
ejpam-5923	318	21	has	have	AUX
ejpam-5923	318	22	been	be	AUX
ejpam-5923	318	23	derived	derive	VERB
ejpam-5923	318	24	.	.	PUNCT
ejpam-5923	319	1	some	some	DET
ejpam-5923	319	2	special	special	ADJ
ejpam-5923	319	3	cases	case	NOUN
ejpam-5923	319	4	of	of	ADP
ejpam-5923	319	5	the	the	DET
ejpam-5923	319	6	generalized	generalized	ADJ
ejpam-5923	319	7	distribution	distribution	NOUN
ejpam-5923	319	8	such	such	ADJ
ejpam-5923	319	9	as	as	ADP
ejpam-5923	319	10	the	the	DET
ejpam-5923	319	11	special	special	ADJ
ejpam-5923	319	12	esu	esu	NOUN
ejpam-5923	319	13	,	,	PUNCT
ejpam-5923	319	14	esu	esu	NOUN
ejpam-5923	319	15	type	type	PROPN
ejpam-5923	319	16	-	-	PUNCT
ejpam-5923	319	17	i	i	PROPN
ejpam-5923	319	18	,	,	PUNCT
ejpam-5923	319	19	esu	esu	NOUN
ejpam-5923	319	20	type	type	PROPN
ejpam-5923	319	21	-	-	PUNCT
ejpam-5923	319	22	ii	ii	NOUN
ejpam-5923	319	23	,	,	PUNCT
ejpam-5923	319	24	esu	esu	NOUN
ejpam-5923	319	25	type	type	NOUN
ejpam-5923	319	26	-	-	PUNCT
ejpam-5923	319	27	iii	iii	NOUN
ejpam-5923	319	28	,	,	PUNCT
ejpam-5923	319	29	esu	esu	NOUN
ejpam-5923	319	30	type	type	NOUN
ejpam-5923	319	31	-	-	PUNCT
ejpam-5923	319	32	iv	iv	NOUN
ejpam-5923	319	33	,	,	PUNCT
ejpam-5923	319	34	esu	esu	NOUN
ejpam-5923	319	35	type	type	NOUN
ejpam-5923	319	36	-	-	PUNCT
ejpam-5923	319	37	v	v	NOUN
ejpam-5923	319	38	,	,	PUNCT
ejpam-5923	319	39	esu	esu	NOUN
ejpam-5923	319	40	type	type	NOUN
ejpam-5923	319	41	-	-	PUNCT
ejpam-5923	319	42	vi	vi	NOUN
ejpam-5923	319	43	,	,	PUNCT
ejpam-5923	319	44	esu	esu	NOUN
ejpam-5923	319	45	type	type	NOUN
ejpam-5923	319	46	-	-	PUNCT
ejpam-5923	319	47	vii	vii	PROPN
ejpam-5923	319	48	,	,	PUNCT
ejpam-5923	319	49	esu	esu	NOUN
ejpam-5923	319	50	type	type	NOUN
ejpam-5923	319	51	-	-	PUNCT
ejpam-5923	319	52	viii	viii	NOUN
ejpam-5923	319	53	,	,	PUNCT
ejpam-5923	319	54	esu	esu	NOUN
ejpam-5923	319	55	type	type	NOUN
ejpam-5923	319	56	-	-	PUNCT
ejpam-5923	319	57	ix	ix	PROPN
ejpam-5923	319	58	and	and	CCONJ
ejpam-5923	319	59	esu	esu	NOUN
ejpam-5923	319	60	type	type	NOUN
ejpam-5923	319	61	-	-	PUNCT
ejpam-5923	319	62	x	x	NOUN
ejpam-5923	319	63	distributions	distribution	NOUN
ejpam-5923	319	64	were	be	AUX
ejpam-5923	319	65	generated	generate	VERB
ejpam-5923	319	66	.	.	PUNCT
ejpam-5923	320	1	moreover	moreover	ADV
ejpam-5923	320	2	,	,	PUNCT
ejpam-5923	320	3	some	some	DET
ejpam-5923	320	4	properties	property	NOUN
ejpam-5923	320	5	of	of	ADP
ejpam-5923	320	6	the	the	DET
ejpam-5923	320	7	proposed	propose	VERB
ejpam-5923	320	8	distribution	distribution	NOUN
ejpam-5923	320	9	such	such	ADJ
ejpam-5923	320	10	as	as	ADP
ejpam-5923	320	11	the	the	DET
ejpam-5923	320	12	moments	moment	NOUN
ejpam-5923	320	13	,	,	PUNCT
ejpam-5923	320	14	mean	mean	VERB
ejpam-5923	320	15	,	,	PUNCT
ejpam-5923	320	16	variance	variance	NOUN
ejpam-5923	320	17	,	,	PUNCT
ejpam-5923	320	18	mode	mode	NOUN
ejpam-5923	320	19	,	,	PUNCT
ejpam-5923	320	20	median	median	NOUN
ejpam-5923	320	21	,	,	PUNCT
ejpam-5923	320	22	moment	moment	NOUN
ejpam-5923	320	23	generating	generating	NOUN
ejpam-5923	320	24	function	function	NOUN
ejpam-5923	320	25	were	be	AUX
ejpam-5923	320	26	computed	compute	VERB
ejpam-5923	320	27	.	.	PUNCT
ejpam-5923	321	1	further	far	ADV
ejpam-5923	321	2	,	,	PUNCT
ejpam-5923	321	3	a	a	DET
ejpam-5923	321	4	newton	newton	PROPN
ejpam-5923	321	5	-	-	PUNCT
ejpam-5923	321	6	raphson	raphson	NOUN
ejpam-5923	321	7	method	method	NOUN
ejpam-5923	321	8	was	be	AUX
ejpam-5923	321	9	used	use	VERB
ejpam-5923	321	10	to	to	PART
ejpam-5923	321	11	generate	generate	VERB
ejpam-5923	321	12	a	a	DET
ejpam-5923	321	13	random	random	ADJ
ejpam-5923	321	14	numbers	number	NOUN
ejpam-5923	321	15	from	from	ADP
ejpam-5923	321	16	the	the	DET
ejpam-5923	321	17	proposed	propose	VERB
ejpam-5923	321	18	distribution	distribution	NOUN
ejpam-5923	321	19	.	.	PUNCT
ejpam-5923	322	1	in	in	ADP
ejpam-5923	322	2	addition	addition	NOUN
ejpam-5923	322	3	,	,	PUNCT
ejpam-5923	322	4	maximum	maximum	ADJ
ejpam-5923	322	5	likelihood	likelihood	NOUN
ejpam-5923	322	6	method	method	NOUN
ejpam-5923	322	7	was	be	AUX
ejpam-5923	322	8	used	use	VERB
ejpam-5923	322	9	to	to	PART
ejpam-5923	322	10	estimate	estimate	VERB
ejpam-5923	322	11	the	the	DET
ejpam-5923	322	12	parameters	parameter	NOUN
ejpam-5923	322	13	of	of	ADP
ejpam-5923	322	14	the	the	DET
ejpam-5923	322	15	distribution	distribution	NOUN
ejpam-5923	322	16	,	,	PUNCT
ejpam-5923	322	17	and	and	CCONJ
ejpam-5923	322	18	simulation	simulation	NOUN
ejpam-5923	322	19	study	study	NOUN
ejpam-5923	322	20	was	be	AUX
ejpam-5923	322	21	carried	carry	VERB
ejpam-5923	322	22	out	out	ADP
ejpam-5923	322	23	to	to	PART
ejpam-5923	322	24	evaluate	evaluate	VERB
ejpam-5923	322	25	the	the	DET
ejpam-5923	322	26	performance	performance	NOUN
ejpam-5923	322	27	of	of	ADP
ejpam-5923	322	28	the	the	DET
ejpam-5923	322	29	maximum	maximum	ADJ
ejpam-5923	322	30	likelihood	likelihood	NOUN
ejpam-5923	322	31	estimates	estimate	NOUN
ejpam-5923	322	32	of	of	ADP
ejpam-5923	322	33	the	the	DET
ejpam-5923	322	34	distribution	distribution	NOUN
ejpam-5923	322	35	.	.	PUNCT
ejpam-5923	323	1	finally	finally	ADV
ejpam-5923	323	2	,	,	PUNCT
ejpam-5923	323	3	the	the	DET
ejpam-5923	323	4	applicability	applicability	NOUN
ejpam-5923	323	5	of	of	ADP
ejpam-5923	323	6	the	the	DET
ejpam-5923	323	7	proposed	propose	VERB
ejpam-5923	323	8	distribution	distribution	NOUN
ejpam-5923	323	9	was	be	AUX
ejpam-5923	323	10	tested	test	VERB
ejpam-5923	323	11	by	by	ADP
ejpam-5923	323	12	applying	apply	VERB
ejpam-5923	323	13	on	on	ADP
ejpam-5923	323	14	a	a	DET
ejpam-5923	323	15	real	real	ADJ
ejpam-5923	323	16	dataset	dataset	NOUN
ejpam-5923	323	17	and	and	CCONJ
ejpam-5923	323	18	it	it	PRON
ejpam-5923	323	19	was	be	AUX
ejpam-5923	323	20	revealed	reveal	VERB
ejpam-5923	323	21	that	that	SCONJ
ejpam-5923	323	22	the	the	DET
ejpam-5923	323	23	gesu	gesu	PROPN
ejpam-5923	323	24	distribution	distribution	NOUN
ejpam-5923	323	25	provides	provide	VERB
ejpam-5923	323	26	better	well	ADJ
ejpam-5923	323	27	estimate	estimate	NOUN
ejpam-5923	323	28	as	as	ADP
ejpam-5923	323	29	compared	compare	VERB
ejpam-5923	323	30	with	with	ADP
ejpam-5923	323	31	the	the	DET
ejpam-5923	323	32	esu	esu	NOUN
ejpam-5923	323	33	,	,	PUNCT
ejpam-5923	323	34	unit	unit	NOUN
ejpam-5923	323	35	-	-	PUNCT
ejpam-5923	323	36	rayleigh	rayleigh	PROPN
ejpam-5923	323	37	and	and	CCONJ
ejpam-5923	323	38	the	the	DET
ejpam-5923	323	39	unit	unit	NOUN
ejpam-5923	323	40	-	-	PUNCT
ejpam-5923	323	41	burr	burr	PROPN
ejpam-5923	323	42	xii	xii	NOUN
ejpam-5923	323	43	distributions	distribution	NOUN
ejpam-5923	323	44	.	.	PUNCT
ejpam-5923	324	1	for	for	ADP
ejpam-5923	324	2	future	future	ADJ
ejpam-5923	324	3	studies	study	NOUN
ejpam-5923	324	4	in	in	ADP
ejpam-5923	324	5	this	this	DET
ejpam-5923	324	6	field	field	NOUN
ejpam-5923	324	7	,	,	PUNCT
ejpam-5923	324	8	it	it	PRON
ejpam-5923	324	9	is	be	AUX
ejpam-5923	324	10	recommended	recommend	VERB
ejpam-5923	324	11	to	to	PART
ejpam-5923	324	12	incorporate	incorporate	VERB
ejpam-5923	324	13	additional	additional	ADJ
ejpam-5923	324	14	parameters	parameter	NOUN
ejpam-5923	324	15	to	to	ADP
ejpam-5923	324	16	this	this	DET
ejpam-5923	324	17	proposed	propose	VERB
ejpam-5923	324	18	distribution	distribution	NOUN
ejpam-5923	324	19	in	in	ADP
ejpam-5923	324	20	order	order	NOUN
ejpam-5923	324	21	to	to	PART
ejpam-5923	324	22	model	model	VERB
ejpam-5923	324	23	more	more	ADJ
ejpam-5923	324	24	complex	complex	ADJ
ejpam-5923	324	25	behavior	behavior	NOUN
ejpam-5923	324	26	of	of	ADP
ejpam-5923	324	27	the	the	DET
ejpam-5923	324	28	data	datum	NOUN
ejpam-5923	324	29	on	on	ADP
ejpam-5923	324	30	the	the	DET
ejpam-5923	324	31	interval	interval	NOUN
ejpam-5923	324	32	[	[	X
ejpam-5923	324	33	0	0	NUM
ejpam-5923	324	34	,	,	PUNCT
ejpam-5923	324	35	1	1	NUM
ejpam-5923	324	36	]	]	PUNCT
ejpam-5923	324	37	or	or	CCONJ
ejpam-5923	324	38	(	(	PUNCT
ejpam-5923	324	39	0	0	NUM
ejpam-5923	324	40	,	,	PUNCT
ejpam-5923	324	41	1	1	NUM
ejpam-5923	324	42	)	)	PUNCT
ejpam-5923	324	43	.	.	PUNCT
ejpam-5923	325	1	i.	i.	PROPN
ejpam-5923	325	2	a.	a.	PROPN
ejpam-5923	325	3	lakibul	lakibul	PROPN
ejpam-5923	325	4	,	,	PUNCT
ejpam-5923	325	5	d.	d.	PROPN
ejpam-5923	325	6	l.	l.	PROPN
ejpam-5923	325	7	polestico	polestico	PROPN
ejpam-5923	325	8	,	,	PUNCT
ejpam-5923	325	9	a.	a.	PROPN
ejpam-5923	325	10	p.	p.	NOUN
ejpam-5923	325	11	supe	supe	PROPN
ejpam-5923	325	12	/	/	SYM
ejpam-5923	325	13	eur	eur	PROPN
ejpam-5923	325	14	.	.	PUNCT
ejpam-5923	326	1	j.	j.	PROPN
ejpam-5923	326	2	pure	pure	PROPN
ejpam-5923	326	3	appl	appl	PROPN
ejpam-5923	326	4	.	.	PROPN
ejpam-5923	326	5	math	math	PROPN
ejpam-5923	326	6	,	,	PUNCT
ejpam-5923	326	7	18	18	NUM
ejpam-5923	326	8	(	(	PUNCT
ejpam-5923	326	9	2	2	NUM
ejpam-5923	326	10	)	)	PUNCT
ejpam-5923	326	11	(	(	PUNCT
ejpam-5923	326	12	2025	2025	NUM
ejpam-5923	326	13	)	)	PUNCT
ejpam-5923	326	14	,	,	PUNCT
ejpam-5923	326	15	5923	5923	NUM
ejpam-5923	326	16	21	21	NUM
ejpam-5923	326	17	of	of	ADP
ejpam-5923	326	18	21	21	NUM
ejpam-5923	326	19	acknowledgements	acknowledgement	NOUN
ejpam-5923	326	20	the	the	DET
ejpam-5923	326	21	authors	author	NOUN
ejpam-5923	326	22	are	be	AUX
ejpam-5923	326	23	grateful	grateful	ADJ
ejpam-5923	326	24	to	to	ADP
ejpam-5923	326	25	the	the	DET
ejpam-5923	326	26	anonymous	anonymous	ADJ
ejpam-5923	326	27	referees	referee	NOUN
ejpam-5923	326	28	for	for	ADP
ejpam-5923	326	29	their	their	PRON
ejpam-5923	326	30	valuable	valuable	ADJ
ejpam-5923	326	31	comments	comment	NOUN
ejpam-5923	326	32	and	and	CCONJ
ejpam-5923	326	33	suggestions	suggestion	NOUN
ejpam-5923	326	34	.	.	PUNCT
ejpam-5923	327	1	moreover	moreover	ADV
ejpam-5923	327	2	,	,	PUNCT
ejpam-5923	327	3	idzhar	idzhar	PROPN
ejpam-5923	327	4	a.	a.	NOUN
ejpam-5923	327	5	lakibul	lakibul	PROPN
ejpam-5923	327	6	is	be	AUX
ejpam-5923	327	7	also	also	ADV
ejpam-5923	327	8	grateful	grateful	ADJ
ejpam-5923	327	9	to	to	ADP
ejpam-5923	327	10	the	the	DET
ejpam-5923	327	11	department	department	NOUN
ejpam-5923	327	12	of	of	ADP
ejpam-5923	327	13	science	science	NOUN
ejpam-5923	327	14	and	and	CCONJ
ejpam-5923	327	15	technology	technology	NOUN
ejpam-5923	327	16	accelerated	accelerate	VERB
ejpam-5923	327	17	science	science	NOUN
ejpam-5923	327	18	and	and	CCONJ
ejpam-5923	327	19	technology	technology	NOUN
ejpam-5923	327	20	human	human	ADJ
ejpam-5923	327	21	resource	resource	NOUN
ejpam-5923	327	22	development	development	NOUN
ejpam-5923	327	23	program	program	NOUN
ejpam-5923	327	24	(	(	PUNCT
ejpam-5923	327	25	dost	dost	NOUN
ejpam-5923	327	26	-	-	PUNCT
ejpam-5923	327	27	asthrdp	asthrdp	NOUN
ejpam-5923	327	28	)	)	PUNCT
ejpam-5923	327	29	for	for	ADP
ejpam-5923	327	30	giving	give	VERB
ejpam-5923	327	31	him	he	PRON
ejpam-5923	327	32	financial	financial	ADJ
ejpam-5923	327	33	support	support	NOUN
ejpam-5923	327	34	to	to	PART
ejpam-5923	327	35	study	study	VERB
ejpam-5923	327	36	at	at	ADP
ejpam-5923	327	37	mindanao	mindanao	PROPN
ejpam-5923	327	38	state	state	PROPN
ejpam-5923	327	39	university	university	PROPN
ejpam-5923	327	40	iligan	iligan	PROPN
ejpam-5923	327	41	institute	institute	PROPN
ejpam-5923	327	42	of	of	ADP
ejpam-5923	327	43	technology	technology	PROPN
ejpam-5923	327	44	(	(	PUNCT
ejpam-5923	327	45	msu	msu	PROPN
ejpam-5923	327	46	-	-	PUNCT
ejpam-5923	327	47	iit	iit	NOUN
ejpam-5923	327	48	)	)	PUNCT
ejpam-5923	327	49	.	.	PUNCT
ejpam-5923	328	1	in	in	ADP
ejpam-5923	328	2	addition	addition	NOUN
ejpam-5923	328	3	,	,	PUNCT
ejpam-5923	328	4	this	this	DET
ejpam-5923	328	5	paper	paper	NOUN
ejpam-5923	328	6	is	be	AUX
ejpam-5923	328	7	also	also	ADV
ejpam-5923	328	8	supported	support	VERB
ejpam-5923	328	9	by	by	ADP
ejpam-5923	328	10	the	the	DET
ejpam-5923	328	11	dost	dost	NOUN
ejpam-5923	328	12	-	-	PUNCT
ejpam-5923	328	13	asthrdp	asthrdp	PROPN
ejpam-5923	328	14	,	,	PUNCT
ejpam-5923	328	15	the	the	DET
ejpam-5923	328	16	msu	msu	PROPN
ejpam-5923	328	17	-	-	PUNCT
ejpam-5923	328	18	iligan	iligan	PROPN
ejpam-5923	328	19	institute	institute	PROPN
ejpam-5923	328	20	of	of	ADP
ejpam-5923	328	21	technology	technology	PROPN
ejpam-5923	328	22	and	and	CCONJ
ejpam-5923	328	23	the	the	DET
ejpam-5923	328	24	mindanao	mindanao	PROPN
ejpam-5923	328	25	state	state	PROPN
ejpam-5923	328	26	university	university	PROPN
ejpam-5923	328	27	sulu	sulu	PROPN
ejpam-5923	328	28	..	..	PUNCT
ejpam-5923	328	29	references	reference	NOUN
ejpam-5923	328	30	[	[	X
ejpam-5923	328	31	1	1	NUM
ejpam-5923	328	32	]	]	PUNCT
ejpam-5923	328	33	p.	p.	NOUN
ejpam-5923	328	34	kumaraswamy	kumaraswamy	NOUN
ejpam-5923	328	35	.	.	PUNCT
ejpam-5923	329	1	a	a	DET
ejpam-5923	329	2	generalized	generalize	VERB
ejpam-5923	329	3	probability	probability	NOUN
ejpam-5923	329	4	density	density	NOUN
ejpam-5923	329	5	function	function	NOUN
ejpam-5923	329	6	for	for	ADP
ejpam-5923	329	7	double	double	ADJ
ejpam-5923	329	8	-	-	PUNCT
ejpam-5923	329	9	bounded	bound	VERB
ejpam-5923	329	10	random	random	ADJ
ejpam-5923	329	11	processes	process	NOUN
ejpam-5923	329	12	.	.	PUNCT
ejpam-5923	330	1	journal	journal	NOUN
ejpam-5923	330	2	of	of	ADP
ejpam-5923	330	3	hydrology	hydrology	NOUN
ejpam-5923	330	4	,	,	PUNCT
ejpam-5923	330	5	46:79–88	46:79–88	NUM
ejpam-5923	330	6	,	,	PUNCT
ejpam-5923	330	7	1980	1980	NUM
ejpam-5923	330	8	.	.	PUNCT
ejpam-5923	331	1	[	[	X
ejpam-5923	331	2	2	2	X
ejpam-5923	331	3	]	]	PUNCT
ejpam-5923	331	4	j.	j.	PROPN
ejpam-5923	331	5	mazucheli	mazucheli	PROPN
ejpam-5923	331	6	,	,	PUNCT
ejpam-5923	331	7	a.	a.	PROPN
ejpam-5923	331	8	f.	f.	PROPN
ejpam-5923	331	9	b.	b.	PROPN
ejpam-5923	331	10	menezes	menezes	PROPN
ejpam-5923	331	11	,	,	PUNCT
ejpam-5923	331	12	and	and	CCONJ
ejpam-5923	331	13	s.	s.	PROPN
ejpam-5923	331	14	chakraborty	chakraborty	PROPN
ejpam-5923	331	15	.	.	PUNCT
ejpam-5923	332	1	on	on	ADP
ejpam-5923	332	2	the	the	DET
ejpam-5923	332	3	one	one	NUM
ejpam-5923	332	4	parameter	parameter	NOUN
ejpam-5923	332	5	unit	unit	NOUN
ejpam-5923	332	6	lindley	lindley	NOUN
ejpam-5923	332	7	distribution	distribution	NOUN
ejpam-5923	332	8	and	and	CCONJ
ejpam-5923	332	9	its	its	PRON
ejpam-5923	332	10	associated	associated	ADJ
ejpam-5923	332	11	regression	regression	NOUN
ejpam-5923	332	12	model	model	NOUN
ejpam-5923	332	13	for	for	ADP
ejpam-5923	332	14	proportion	proportion	NOUN
ejpam-5923	332	15	data	datum	NOUN
ejpam-5923	332	16	.	.	PUNCT
ejpam-5923	333	1	journal	journal	PROPN
ejpam-5923	333	2	of	of	ADP
ejpam-5923	333	3	applied	applied	ADJ
ejpam-5923	333	4	statistics	statistic	NOUN
ejpam-5923	333	5	,	,	PUNCT
ejpam-5923	333	6	46:700–714	46:700–714	PROPN
ejpam-5923	333	7	,	,	PUNCT
ejpam-5923	333	8	2019	2019	NUM
ejpam-5923	333	9	.	.	PUNCT
ejpam-5923	334	1	[	[	X
ejpam-5923	334	2	3	3	X
ejpam-5923	334	3	]	]	X
ejpam-5923	334	4	r.	r.	PROPN
ejpam-5923	334	5	a.	a.	PROPN
ejpam-5923	334	6	bantan	bantan	PROPN
ejpam-5923	334	7	,	,	PUNCT
ejpam-5923	334	8	c.	c.	PROPN
ejpam-5923	334	9	chesneau	chesneau	PROPN
ejpam-5923	334	10	,	,	PUNCT
ejpam-5923	334	11	f.	f.	PROPN
ejpam-5923	334	12	jamal	jamal	PROPN
ejpam-5923	334	13	,	,	PUNCT
ejpam-5923	334	14	m.	m.	NOUN
ejpam-5923	334	15	elgarhy	elgarhy	PROPN
ejpam-5923	334	16	,	,	PUNCT
ejpam-5923	334	17	m.	m.	NOUN
ejpam-5923	334	18	h.	h.	PROPN
ejpam-5923	334	19	tahir	tahir	PROPN
ejpam-5923	334	20	,	,	PUNCT
ejpam-5923	334	21	a.	a.	PROPN
ejpam-5923	334	22	ali	ali	PROPN
ejpam-5923	334	23	,	,	PUNCT
ejpam-5923	334	24	m.	m.	PROPN
ejpam-5923	334	25	zubair	zubair	PROPN
ejpam-5923	334	26	,	,	PUNCT
ejpam-5923	334	27	and	and	CCONJ
ejpam-5923	334	28	s.	s.	PROPN
ejpam-5923	334	29	anam	anam	PROPN
ejpam-5923	334	30	.	.	PUNCT
ejpam-5923	335	1	some	some	DET
ejpam-5923	335	2	new	new	ADJ
ejpam-5923	335	3	facts	fact	NOUN
ejpam-5923	335	4	about	about	ADP
ejpam-5923	335	5	the	the	DET
ejpam-5923	335	6	unitrayleigh	unitrayleigh	ADJ
ejpam-5923	335	7	distribution	distribution	NOUN
ejpam-5923	335	8	with	with	ADP
ejpam-5923	335	9	applications	application	NOUN
ejpam-5923	335	10	.	.	PUNCT
ejpam-5923	336	1	mathematics	mathematic	NOUN
ejpam-5923	336	2	,	,	PUNCT
ejpam-5923	336	3	8:1954	8:1954	NUM
ejpam-5923	336	4	,	,	PUNCT
ejpam-5923	336	5	2020	2020	NUM
ejpam-5923	336	6	.	.	PUNCT
ejpam-5923	337	1	[	[	X
ejpam-5923	337	2	4	4	X
ejpam-5923	337	3	]	]	PUNCT
ejpam-5923	337	4	j.	j.	PROPN
ejpam-5923	337	5	mazucheli	mazucheli	PROPN
ejpam-5923	337	6	,	,	PUNCT
ejpam-5923	337	7	s.	s.	PROPN
ejpam-5923	337	8	r.	r.	PROPN
ejpam-5923	337	9	bapat	bapat	PROPN
ejpam-5923	337	10	,	,	PUNCT
ejpam-5923	337	11	and	and	CCONJ
ejpam-5923	337	12	a.	a.	PROPN
ejpam-5923	337	13	f.	f.	PROPN
ejpam-5923	337	14	b.	b.	PROPN
ejpam-5923	337	15	menezes	menezes	PROPN
ejpam-5923	337	16	.	.	PUNCT
ejpam-5923	338	1	a	a	DET
ejpam-5923	338	2	new	new	ADJ
ejpam-5923	338	3	one	one	NUM
ejpam-5923	338	4	-	-	PUNCT
ejpam-5923	338	5	parameter	parameter	NOUN
ejpam-5923	338	6	unit	unit	NOUN
ejpam-5923	338	7	lindley	lindley	NOUN
ejpam-5923	338	8	distribution	distribution	NOUN
ejpam-5923	338	9	.	.	PUNCT
ejpam-5923	339	1	chilean	chilean	ADJ
ejpam-5923	339	2	journal	journal	PROPN
ejpam-5923	339	3	of	of	ADP
ejpam-5923	339	4	statistics	statistic	NOUN
ejpam-5923	339	5	,	,	PUNCT
ejpam-5923	339	6	11	11	NUM
ejpam-5923	339	7	,	,	PUNCT
ejpam-5923	339	8	2020a	2020a	NUM
ejpam-5923	339	9	.	.	PUNCT
ejpam-5923	340	1	[	[	X
ejpam-5923	340	2	5	5	X
ejpam-5923	340	3	]	]	PUNCT
ejpam-5923	340	4	j.	j.	PROPN
ejpam-5923	340	5	mazucheli	mazucheli	PROPN
ejpam-5923	340	6	,	,	PUNCT
ejpam-5923	340	7	a.	a.	PROPN
ejpam-5923	340	8	menezes	menezes	PROPN
ejpam-5923	340	9	,	,	PUNCT
ejpam-5923	340	10	l.	l.	PROPN
ejpam-5923	340	11	fernandes	fernandes	PROPN
ejpam-5923	340	12	,	,	PUNCT
ejpam-5923	340	13	r.	r.	PROPN
ejpam-5923	340	14	de	de	PROPN
ejpam-5923	340	15	oliveira	oliveira	PROPN
ejpam-5923	340	16	,	,	PUNCT
ejpam-5923	340	17	and	and	CCONJ
ejpam-5923	340	18	m.	m.	NOUN
ejpam-5923	340	19	ghitany	ghitany	NOUN
ejpam-5923	340	20	.	.	PUNCT
ejpam-5923	341	1	the	the	DET
ejpam-5923	341	2	unit	unit	NOUN
ejpam-5923	341	3	weibull	weibull	NOUN
ejpam-5923	341	4	distribution	distribution	NOUN
ejpam-5923	341	5	as	as	ADP
ejpam-5923	341	6	an	an	DET
ejpam-5923	341	7	alternative	alternative	NOUN
ejpam-5923	341	8	to	to	ADP
ejpam-5923	341	9	the	the	DET
ejpam-5923	341	10	kumaraswamy	kumaraswamy	ADJ
ejpam-5923	341	11	distribution	distribution	NOUN
ejpam-5923	341	12	for	for	ADP
ejpam-5923	341	13	the	the	DET
ejpam-5923	341	14	modeling	modeling	NOUN
ejpam-5923	341	15	of	of	ADP
ejpam-5923	341	16	quantiles	quantile	NOUN
ejpam-5923	341	17	conditional	conditional	ADJ
ejpam-5923	341	18	on	on	ADP
ejpam-5923	341	19	covariates	covariate	NOUN
ejpam-5923	341	20	.	.	PUNCT
ejpam-5923	342	1	journal	journal	NOUN
ejpam-5923	342	2	of	of	ADP
ejpam-5923	342	3	applied	applied	ADJ
ejpam-5923	342	4	statistics	statistic	NOUN
ejpam-5923	342	5	,	,	PUNCT
ejpam-5923	342	6	47:954	47:954	NUM
ejpam-5923	342	7	–	–	PUNCT
ejpam-5923	342	8	974	974	NUM
ejpam-5923	342	9	,	,	PUNCT
ejpam-5923	342	10	2020b	2020b	NUM
ejpam-5923	342	11	.	.	PUNCT
ejpam-5923	343	1	[	[	X
ejpam-5923	343	2	6	6	NUM
ejpam-5923	343	3	]	]	PUNCT
ejpam-5923	343	4	m.	m.	NOUN
ejpam-5923	343	5	m.	m.	PROPN
ejpam-5923	343	6	rahman	rahman	PROPN
ejpam-5923	343	7	,	,	PUNCT
ejpam-5923	343	8	b.	b.	PROPN
ejpam-5923	343	9	al	al	PROPN
ejpam-5923	343	10	-	-	PUNCT
ejpam-5923	343	11	zahrani	zahrani	PROPN
ejpam-5923	343	12	,	,	PUNCT
ejpam-5923	343	13	s.	s.	PROPN
ejpam-5923	343	14	h.	h.	PROPN
ejpam-5923	343	15	shahbaz	shahbaz	PROPN
ejpam-5923	343	16	,	,	PUNCT
ejpam-5923	343	17	and	and	CCONJ
ejpam-5923	343	18	m.	m.	PROPN
ejpam-5923	343	19	q.	q.	PROPN
ejpam-5923	343	20	shahbaz	shahbaz	PROPN
ejpam-5923	343	21	.	.	PUNCT
ejpam-5923	343	22	cubic	cubic	ADJ
ejpam-5923	343	23	transmuted	transmute	VERB
ejpam-5923	343	24	uniform	uniform	ADJ
ejpam-5923	343	25	distribution	distribution	NOUN
ejpam-5923	343	26	:	:	PUNCT
ejpam-5923	343	27	an	an	DET
ejpam-5923	343	28	alternative	alternative	NOUN
ejpam-5923	343	29	to	to	ADP
ejpam-5923	343	30	beta	beta	ADJ
ejpam-5923	343	31	and	and	CCONJ
ejpam-5923	343	32	kumaraswamy	kumaraswamy	ADJ
ejpam-5923	343	33	distributions	distribution	NOUN
ejpam-5923	343	34	.	.	PUNCT
ejpam-5923	344	1	european	european	ADJ
ejpam-5923	344	2	journal	journal	PROPN
ejpam-5923	344	3	of	of	ADP
ejpam-5923	344	4	pure	pure	ADJ
ejpam-5923	344	5	and	and	CCONJ
ejpam-5923	344	6	applied	applied	ADJ
ejpam-5923	344	7	mathematics	mathematic	NOUN
ejpam-5923	344	8	,	,	PUNCT
ejpam-5923	344	9	12:1106–1121	12:1106–1121	NUM
ejpam-5923	344	10	,	,	PUNCT
ejpam-5923	344	11	2019	2019	NUM
ejpam-5923	344	12	.	.	PUNCT
ejpam-5923	345	1	[	[	X
ejpam-5923	345	2	7	7	X
ejpam-5923	345	3	]	]	X
ejpam-5923	345	4	i.	i.	PROPN
ejpam-5923	345	5	a.	a.	PROPN
ejpam-5923	345	6	lakibul	lakibul	PROPN
ejpam-5923	345	7	and	and	CCONJ
ejpam-5923	345	8	b.	b.	PROPN
ejpam-5923	345	9	f.	f.	PROPN
ejpam-5923	345	10	tubo	tubo	PROPN
ejpam-5923	345	11	.	.	PROPN
ejpam-5923	346	1	on	on	ADP
ejpam-5923	346	2	the	the	DET
ejpam-5923	346	3	tesu	tesu	PROPN
ejpam-5923	346	4	-	-	PUNCT
ejpam-5923	346	5	g	g	NOUN
ejpam-5923	346	6	family	family	NOUN
ejpam-5923	346	7	of	of	ADP
ejpam-5923	346	8	distributions	distribution	NOUN
ejpam-5923	346	9	applied	apply	VERB
ejpam-5923	346	10	to	to	ADP
ejpam-5923	346	11	life	life	NOUN
ejpam-5923	346	12	data	datum	NOUN
ejpam-5923	346	13	analysis	analysis	NOUN
ejpam-5923	346	14	.	.	PUNCT
ejpam-5923	347	1	reliability	reliability	NOUN
ejpam-5923	347	2	:	:	PUNCT
ejpam-5923	347	3	theory	theory	NOUN
ejpam-5923	347	4	and	and	CCONJ
ejpam-5923	347	5	applications	application	NOUN
ejpam-5923	347	6	,	,	PUNCT
ejpam-5923	347	7	18:24–38	18:24–38	NUM
ejpam-5923	347	8	,	,	PUNCT
ejpam-5923	347	9	2023	2023	NUM
ejpam-5923	347	10	.	.	PUNCT
ejpam-5923	348	1	[	[	X
ejpam-5923	348	2	8	8	NUM
ejpam-5923	348	3	]	]	X
ejpam-5923	348	4	i.	i.	PROPN
ejpam-5923	348	5	a.	a.	PROPN
ejpam-5923	348	6	lakibul	lakibul	PROPN
ejpam-5923	348	7	and	and	CCONJ
ejpam-5923	348	8	b.	b.	PROPN
ejpam-5923	348	9	f.	f.	PROPN
ejpam-5923	348	10	tubo	tubo	PROPN
ejpam-5923	348	11	.	.	PROPN
ejpam-5923	349	1	on	on	ADP
ejpam-5923	349	2	the	the	DET
ejpam-5923	349	3	four	four	NUM
ejpam-5923	349	4	-	-	PUNCT
ejpam-5923	349	5	parameter	parameter	NOUN
ejpam-5923	349	6	t	t	PROPN
ejpam-5923	349	7	-	-	PUNCT
ejpam-5923	349	8	extended	extend	VERB
ejpam-5923	349	9	standard	standard	ADJ
ejpam-5923	349	10	uquadratic	uquadratic	ADJ
ejpam-5923	349	11	exponentiated	exponentiate	VERB
ejpam-5923	349	12	weibull	weibull	NOUN
ejpam-5923	349	13	distribution	distribution	NOUN
ejpam-5923	349	14	.	.	PUNCT
ejpam-5923	350	1	the	the	DET
ejpam-5923	350	2	mindanawan	mindanawan	PROPN
ejpam-5923	350	3	journal	journal	PROPN
ejpam-5923	350	4	of	of	ADP
ejpam-5923	350	5	mathematics	mathematic	NOUN
ejpam-5923	350	6	,	,	PUNCT
ejpam-5923	350	7	5:17–33	5:17–33	NOUN
ejpam-5923	350	8	,	,	PUNCT
ejpam-5923	350	9	2023	2023	NUM
ejpam-5923	350	10	.	.	PUNCT
ejpam-5923	351	1	[	[	X
ejpam-5923	351	2	9	9	NUM
ejpam-5923	351	3	]	]	PUNCT
ejpam-5923	351	4	i.	i.	PROPN
ejpam-5923	351	5	a.	a.	PROPN
ejpam-5923	351	6	lakibul	lakibul	PROPN
ejpam-5923	351	7	,	,	PUNCT
ejpam-5923	351	8	d.	d.	PROPN
ejpam-5923	351	9	l.	l.	PROPN
ejpam-5923	351	10	polestico	polestico	PROPN
ejpam-5923	351	11	,	,	PUNCT
ejpam-5923	351	12	and	and	CCONJ
ejpam-5923	351	13	a.	a.	PROPN
ejpam-5923	351	14	p.	p.	PROPN
ejpam-5923	351	15	supe	supe	PROPN
ejpam-5923	351	16	.	.	PUNCT
ejpam-5923	352	1	on	on	ADP
ejpam-5923	352	2	the	the	DET
ejpam-5923	352	3	bivariate	bivariate	ADJ
ejpam-5923	352	4	extension	extension	NOUN
ejpam-5923	352	5	of	of	ADP
ejpam-5923	352	6	the	the	DET
ejpam-5923	352	7	extended	extended	ADJ
ejpam-5923	352	8	standard	standard	ADJ
ejpam-5923	352	9	u	u	ADJ
ejpam-5923	352	10	-	-	ADJ
ejpam-5923	352	11	quadratic	quadratic	ADJ
ejpam-5923	352	12	distribution	distribution	NOUN
ejpam-5923	352	13	.	.	PUNCT
ejpam-5923	353	1	european	european	ADJ
ejpam-5923	353	2	journal	journal	PROPN
ejpam-5923	353	3	of	of	ADP
ejpam-5923	353	4	pure	pure	ADJ
ejpam-5923	353	5	and	and	CCONJ
ejpam-5923	353	6	applied	applied	ADJ
ejpam-5923	353	7	mathematics	mathematic	NOUN
ejpam-5923	353	8	,	,	PUNCT
ejpam-5923	353	9	17:790–809	17:790–809	NUM
ejpam-5923	353	10	,	,	PUNCT
ejpam-5923	353	11	2024	2024	NUM
ejpam-5923	353	12	.	.	PUNCT
ejpam-5923	354	1	[	[	X
ejpam-5923	354	2	10	10	NUM
ejpam-5923	354	3	]	]	PUNCT
ejpam-5923	354	4	m.	m.	NOUN
ejpam-5923	354	5	c.	c.	PROPN
ejpam-5923	354	6	korkmaz	korkmaz	PROPN
ejpam-5923	354	7	and	and	CCONJ
ejpam-5923	354	8	c.	c.	PROPN
ejpam-5923	354	9	chesneau	chesneau	PROPN
ejpam-5923	354	10	.	.	PUNCT
ejpam-5923	355	1	on	on	ADP
ejpam-5923	355	2	the	the	DET
ejpam-5923	355	3	unit	unit	NOUN
ejpam-5923	355	4	burr	burr	PROPN
ejpam-5923	355	5	-	-	PUNCT
ejpam-5923	355	6	xii	xii	NOUN
ejpam-5923	355	7	distribution	distribution	NOUN
ejpam-5923	355	8	with	with	ADP
ejpam-5923	355	9	the	the	DET
ejpam-5923	355	10	quantile	quantile	ADJ
ejpam-5923	355	11	regression	regression	NOUN
ejpam-5923	355	12	modeling	modeling	NOUN
ejpam-5923	355	13	.	.	PUNCT
ejpam-5923	356	1	computational	computational	ADJ
ejpam-5923	356	2	and	and	CCONJ
ejpam-5923	356	3	applied	applied	ADJ
ejpam-5923	356	4	mathematics	mathematic	NOUN
ejpam-5923	356	5	,	,	PUNCT
ejpam-5923	356	6	pages	page	NOUN
ejpam-5923	356	7	https://doi.org/10.1007/s40314–021–01418–5	https://doi.org/10.1007/s40314–021–01418–5	PROPN
ejpam-5923	356	8	,	,	PUNCT
ejpam-5923	356	9	2021	2021	NUM
ejpam-5923	356	10	.	.	PUNCT
ejpam-5923	357	1	[	[	X
ejpam-5923	357	2	11	11	NUM
ejpam-5923	357	3	]	]	X
ejpam-5923	357	4	c.	c.	PROPN
ejpam-5923	357	5	quesenberry	quesenberry	PROPN
ejpam-5923	357	6	and	and	CCONJ
ejpam-5923	357	7	c.	c.	PROPN
ejpam-5923	357	8	hales	hales	PROPN
ejpam-5923	357	9	.	.	PUNCT
ejpam-5923	358	1	concentration	concentration	NOUN
ejpam-5923	358	2	bands	band	NOUN
ejpam-5923	358	3	for	for	ADP
ejpam-5923	358	4	uniformity	uniformity	NOUN
ejpam-5923	358	5	plots	plot	NOUN
ejpam-5923	358	6	.	.	PUNCT
ejpam-5923	359	1	journal	journal	NOUN
ejpam-5923	359	2	of	of	ADP
ejpam-5923	359	3	statistical	statistical	ADJ
ejpam-5923	359	4	computation	computation	NOUN
ejpam-5923	359	5	and	and	CCONJ
ejpam-5923	359	6	simulation	simulation	NOUN
ejpam-5923	359	7	,	,	PUNCT
ejpam-5923	359	8	11:41–53	11:41–53	NUM
ejpam-5923	359	9	,	,	PUNCT
ejpam-5923	359	10	1980	1980	NUM
ejpam-5923	359	11	.	.	PUNCT