id	sid	tid	token	lemma	pos
esrj-65577	1	1	time	time	NOUN
esrj-65577	1	2	series	series	NOUN
esrj-65577	1	3	models	model	NOUN
esrj-65577	1	4	are	be	AUX
esrj-65577	1	5	often	often	ADV
esrj-65577	1	6	used	use	VERB
esrj-65577	1	7	in	in	ADP
esrj-65577	1	8	hydrology	hydrology	NOUN
esrj-65577	1	9	and	and	CCONJ
esrj-65577	1	10	meteorology	meteorology	NOUN
esrj-65577	1	11	studies	study	NOUN
esrj-65577	1	12	to	to	AUX
esrj-65577	1	13	model	model	PROPN
esrj-65577	1	14	streamflows	streamflow	NOUN
esrj-65577	1	15	series	series	PROPN
esrj-65577	1	16	in	in	ADP
esrj-65577	1	17	order	order	NOUN
esrj-65577	1	18	to	to	PART
esrj-65577	1	19	make	make	VERB
esrj-65577	1	20	forecasting	forecasting	NOUN
esrj-65577	1	21	and	and	CCONJ
esrj-65577	1	22	generate	generate	VERB
esrj-65577	1	23	synthetic	synthetic	ADJ
esrj-65577	1	24	series	series	NOUN
esrj-65577	1	25	which	which	PRON
esrj-65577	1	26	are	be	AUX
esrj-65577	1	27	inputs	input	NOUN
esrj-65577	1	28	for	for	ADP
esrj-65577	1	29	the	the	DET
esrj-65577	1	30	analysis	analysis	NOUN
esrj-65577	1	31	of	of	ADP
esrj-65577	1	32	complex	complex	ADJ
esrj-65577	1	33	water	water	NOUN
esrj-65577	1	34	resources	resource	NOUN
esrj-65577	1	35	systems	system	NOUN
esrj-65577	1	36	.	.	PUNCT
esrj-65577	2	1	in	in	ADP
esrj-65577	2	2	this	this	DET
esrj-65577	2	3	paper	paper	NOUN
esrj-65577	2	4	we	we	PRON
esrj-65577	2	5	introduce	introduce	VERB
esrj-65577	2	6	a	a	DET
esrj-65577	2	7	new	new	ADJ
esrj-65577	2	8	modeling	modeling	NOUN
esrj-65577	2	9	approach	approach	NOUN
esrj-65577	2	10	for	for	ADP
esrj-65577	2	11	hydrologic	hydrologic	NOUN
esrj-65577	2	12	and	and	CCONJ
esrj-65577	2	13	meteorological	meteorological	ADJ
esrj-65577	2	14	time	time	NOUN
esrj-65577	2	15	series	series	PROPN
esrj-65577	2	16	assuming	assume	VERB
esrj-65577	2	17	a	a	DET
esrj-65577	2	18	continuous	continuous	ADJ
esrj-65577	2	19	distribution	distribution	NOUN
esrj-65577	2	20	for	for	ADP
esrj-65577	2	21	the	the	DET
esrj-65577	2	22	data	datum	NOUN
esrj-65577	2	23	,	,	PUNCT
esrj-65577	2	24	where	where	SCONJ
esrj-65577	2	25	both	both	CCONJ
esrj-65577	2	26	the	the	DET
esrj-65577	2	27	conditional	conditional	ADJ
esrj-65577	2	28	mean	mean	NOUN
esrj-65577	2	29	and	and	CCONJ
esrj-65577	2	30	conditional	conditional	ADJ
esrj-65577	2	31	variance	variance	NOUN
esrj-65577	2	32	parameters	parameter	NOUN
esrj-65577	2	33	are	be	AUX
esrj-65577	2	34	modeled	model	VERB
esrj-65577	2	35	.	.	PUNCT
esrj-65577	3	1	bayesian	bayesian	NOUN
esrj-65577	3	2	methods	method	NOUN
esrj-65577	3	3	using	use	VERB
esrj-65577	3	4	standard	standard	ADJ
esrj-65577	3	5	mcmc	mcmc	PROPN
esrj-65577	3	6	(	(	PUNCT
esrj-65577	3	7	markov	markov	PROPN
esrj-65577	3	8	chain	chain	NOUN
esrj-65577	3	9	monte	monte	PROPN
esrj-65577	3	10	carlo	carlo	PROPN
esrj-65577	3	11	methods	method	NOUN
esrj-65577	3	12	)	)	PUNCT
esrj-65577	3	13	are	be	AUX
esrj-65577	3	14	used	use	VERB
esrj-65577	3	15	to	to	PART
esrj-65577	3	16	simulate	simulate	VERB
esrj-65577	3	17	samples	sample	NOUN
esrj-65577	3	18	for	for	ADP
esrj-65577	3	19	the	the	DET
esrj-65577	3	20	joint	joint	ADJ
esrj-65577	3	21	posterior	posterior	ADJ
esrj-65577	3	22	distribution	distribution	NOUN
esrj-65577	3	23	of	of	ADP
esrj-65577	3	24	interest	interest	NOUN
esrj-65577	3	25	.	.	PUNCT
esrj-65577	4	1	two	two	NUM
esrj-65577	4	2	applications	application	NOUN
esrj-65577	4	3	to	to	ADP
esrj-65577	4	4	real	real	ADJ
esrj-65577	4	5	data	datum	NOUN
esrj-65577	4	6	sets	set	NOUN
esrj-65577	4	7	illustrate	illustrate	VERB
esrj-65577	4	8	the	the	DET
esrj-65577	4	9	proposed	propose	VERB
esrj-65577	4	10	methodology	methodology	NOUN
esrj-65577	4	11	,	,	PUNCT
esrj-65577	4	12	assuming	assume	VERB
esrj-65577	4	13	that	that	SCONJ
esrj-65577	4	14	the	the	DET
esrj-65577	4	15	observations	observation	NOUN
esrj-65577	4	16	come	come	VERB
esrj-65577	4	17	from	from	ADP
esrj-65577	4	18	a	a	DET
esrj-65577	4	19	normal	normal	ADJ
esrj-65577	4	20	,	,	PUNCT
esrj-65577	4	21	a	a	DET
esrj-65577	4	22	gamma	gamma	NOUN
esrj-65577	4	23	or	or	CCONJ
esrj-65577	4	24	a	a	DET
esrj-65577	4	25	beta	beta	ADJ
esrj-65577	4	26	distribution	distribution	NOUN
esrj-65577	4	27	.	.	PUNCT
esrj-65577	5	1	a	a	DET
esrj-65577	5	2	first	first	ADJ
esrj-65577	5	3	example	example	NOUN
esrj-65577	5	4	is	be	AUX
esrj-65577	5	5	given	give	VERB
esrj-65577	5	6	by	by	ADP
esrj-65577	5	7	a	a	DET
esrj-65577	5	8	time	time	NOUN
esrj-65577	5	9	series	series	NOUN
esrj-65577	5	10	of	of	ADP
esrj-65577	5	11	monthly	monthly	ADJ
esrj-65577	5	12	averages	average	NOUN
esrj-65577	5	13	of	of	ADP
esrj-65577	5	14	natural	natural	ADJ
esrj-65577	5	15	streamflows	streamflow	NOUN
esrj-65577	5	16	,	,	PUNCT
esrj-65577	5	17	measured	measure	VERB
esrj-65577	5	18	in	in	ADP
esrj-65577	5	19	the	the	DET
esrj-65577	5	20	year	year	NOUN
esrj-65577	5	21	period	period	NOUN
esrj-65577	5	22	ranging	range	VERB
esrj-65577	5	23	from	from	ADP
esrj-65577	5	24	1931	1931	NUM
esrj-65577	5	25	to	to	ADP
esrj-65577	5	26	2010	2010	NUM
esrj-65577	5	27	in	in	ADP
esrj-65577	5	28	furnas	furnas	PROPN
esrj-65577	5	29	hydroelectric	hydroelectric	PROPN
esrj-65577	5	30	dam	dam	PROPN
esrj-65577	5	31	,	,	PUNCT
esrj-65577	5	32	brazil	brazil	PROPN
esrj-65577	5	33	.	.	PUNCT
esrj-65577	6	1	a	a	DET
esrj-65577	6	2	second	second	ADJ
esrj-65577	6	3	example	example	NOUN
esrj-65577	6	4	is	be	AUX
esrj-65577	6	5	given	give	VERB
esrj-65577	6	6	with	with	ADP
esrj-65577	6	7	a	a	DET
esrj-65577	6	8	time	time	NOUN
esrj-65577	6	9	series	series	NOUN
esrj-65577	6	10	of	of	ADP
esrj-65577	6	11	313	313	NUM
esrj-65577	6	12	air	air	NOUN
esrj-65577	6	13	humidity	humidity	NOUN
esrj-65577	6	14	data	datum	NOUN
esrj-65577	6	15	measured	measure	VERB
esrj-65577	6	16	in	in	ADP
esrj-65577	6	17	a	a	DET
esrj-65577	6	18	weather	weather	NOUN
esrj-65577	6	19	station	station	NOUN
esrj-65577	6	20	of	of	ADP
esrj-65577	6	21	rio	rio	PROPN
esrj-65577	6	22	claro	claro	PROPN
esrj-65577	6	23	,	,	PUNCT
esrj-65577	6	24	a	a	DET
esrj-65577	6	25	brazilian	brazilian	ADJ
esrj-65577	6	26	city	city	NOUN
esrj-65577	6	27	located	locate	VERB
esrj-65577	6	28	in	in	ADP
esrj-65577	6	29	southeastern	southeastern	NOUN
esrj-65577	6	30	of	of	ADP
esrj-65577	6	31	brazil	brazil	PROPN
esrj-65577	6	32	.	.	PUNCT
esrj-65577	7	1	these	these	DET
esrj-65577	7	2	applications	application	NOUN
esrj-65577	7	3	motivate	motivate	VERB
esrj-65577	7	4	us	we	PRON
esrj-65577	7	5	to	to	PART
esrj-65577	7	6	introduce	introduce	VERB
esrj-65577	7	7	new	new	ADJ
esrj-65577	7	8	classes	class	NOUN
esrj-65577	7	9	of	of	ADP
esrj-65577	7	10	models	model	NOUN
esrj-65577	7	11	to	to	PART
esrj-65577	7	12	analyze	analyze	VERB
esrj-65577	7	13	hydrological	hydrological	ADJ
esrj-65577	7	14	and	and	CCONJ
esrj-65577	7	15	meteorological	meteorological	ADJ
esrj-65577	7	16	time	time	NOUN
esrj-65577	7	17	series	series	NOUN
esrj-65577	7	18	.	.	PUNCT
esrj-65577	8	1	abstract	abstract	ADJ
esrj-65577	8	2	keywords	keyword	NOUN
esrj-65577	8	3	:	:	PUNCT
esrj-65577	8	4	hydrology	hydrology	NOUN
esrj-65577	8	5	time	time	NOUN
esrj-65577	8	6	series	series	PROPN
esrj-65577	8	7	,	,	PUNCT
esrj-65577	8	8	meteorological	meteorological	ADJ
esrj-65577	8	9	time	time	NOUN
esrj-65577	8	10	series	series	NOUN
esrj-65577	8	11	,	,	PUNCT
esrj-65577	8	12	conditional	conditional	ADJ
esrj-65577	8	13	regression	regression	NOUN
esrj-65577	8	14	models	model	NOUN
esrj-65577	8	15	,	,	PUNCT
esrj-65577	8	16	bayesian	bayesian	NOUN
esrj-65577	8	17	analysis	analysis	NOUN
esrj-65577	8	18	,	,	PUNCT
esrj-65577	8	19	mcmc	mcmc	PROPN
esrj-65577	8	20	methods	method	NOUN
esrj-65577	8	21	.	.	PUNCT
esrj-65577	9	1	seasonal	seasonal	ADJ
esrj-65577	9	2	hydrological	hydrological	ADJ
esrj-65577	9	3	and	and	CCONJ
esrj-65577	9	4	meteorological	meteorological	ADJ
esrj-65577	9	5	time	time	NOUN
esrj-65577	9	6	series	series	PROPN
esrj-65577	9	7	issn	issn	PROPN
esrj-65577	9	8	1794	1794	NUM
esrj-65577	9	9	-	-	SYM
esrj-65577	9	10	6190	6190	NUM
esrj-65577	9	11	e	e	NOUN
esrj-65577	9	12	-	-	NOUN
esrj-65577	9	13	issn	issn	PROPN
esrj-65577	9	14	2339	2339	NUM
esrj-65577	9	15	-	-	SYM
esrj-65577	9	16	3459	3459	NUM
esrj-65577	9	17	http://dx.doi.org/10.15446/esrj.v22n2.65577	http://dx.doi.org/10.15446/esrj.v22n2.65577	PROPN
esrj-65577	9	18	edilberto	edilberto	VERB
esrj-65577	9	19	cepeda	cepeda	PROPN
esrj-65577	9	20	cuervo1	cuervo1	PROPN
esrj-65577	9	21	,	,	PUNCT
esrj-65577	9	22	jorge	jorge	PROPN
esrj-65577	9	23	alberto	alberto	PROPN
esrj-65577	9	24	achcar2	achcar2	PROPN
esrj-65577	9	25	,	,	PUNCT
esrj-65577	9	26	marinho	marinho	PROPN
esrj-65577	9	27	g.	g.	PROPN
esrj-65577	9	28	andrade3	andrade3	PROPN
esrj-65577	9	29	.	.	PUNCT
esrj-65577	10	1	1	1	X
esrj-65577	10	2	.	.	X
esrj-65577	10	3	statistics	statistics	PROPN
esrj-65577	10	4	department	department	PROPN
esrj-65577	10	5	science	science	PROPN
esrj-65577	10	6	faculty	faculty	PROPN
esrj-65577	10	7	universidad	universidad	PROPN
esrj-65577	10	8	nacional	nacional	PROPN
esrj-65577	10	9	de	de	X
esrj-65577	10	10	colombia	colombia	PROPN
esrj-65577	10	11	,	,	PUNCT
esrj-65577	10	12	bogotá	bogotá	NOUN
esrj-65577	10	13	,	,	PUNCT
esrj-65577	10	14	colombia	colombia	PROPN
esrj-65577	10	15	email	email	NOUN
esrj-65577	10	16	:	:	PUNCT
esrj-65577	10	17	ecepedac@unal.edu.co	ecepedac@unal.edu.co	NOUN
esrj-65577	10	18	2	2	NUM
esrj-65577	10	19	.	.	PUNCT
esrj-65577	10	20	social	social	ADJ
esrj-65577	10	21	medicine	medicine	PROPN
esrj-65577	10	22	department	department	NOUN
esrj-65577	10	23	fmrp	fmrp	NOUN
esrj-65577	10	24	,	,	PUNCT
esrj-65577	10	25	universidade	universidade	PROPN
esrj-65577	10	26	de	de	PROPN
esrj-65577	10	27	são	são	PROPN
esrj-65577	10	28	paulo	paulo	PROPN
esrj-65577	10	29	ribeirão	ribeirão	PROPN
esrj-65577	10	30	preto	preto	PROPN
esrj-65577	10	31	,	,	PUNCT
esrj-65577	10	32	s.p	s.p	PROPN
esrj-65577	10	33	.	.	PROPN
esrj-65577	10	34	,	,	PUNCT
esrj-65577	10	35	brazil	brazil	PROPN
esrj-65577	10	36	3	3	NUM
esrj-65577	10	37	.	.	PUNCT
esrj-65577	10	38	applied	apply	VERB
esrj-65577	10	39	mathematics	mathematic	NOUN
esrj-65577	10	40	and	and	CCONJ
esrj-65577	10	41	statistics	statistics	PROPN
esrj-65577	10	42	department	department	PROPN
esrj-65577	10	43	icmc	icmc	PROPN
esrj-65577	10	44	,	,	PUNCT
esrj-65577	10	45	universidade	universidade	PROPN
esrj-65577	10	46	de	de	PROPN
esrj-65577	10	47	são	são	PROPN
esrj-65577	10	48	paulo	paulo	PROPN
esrj-65577	10	49	sao	sao	PROPN
esrj-65577	10	50	carlos	carlos	PROPN
esrj-65577	10	51	,	,	PUNCT
esrj-65577	10	52	s.p	s.p	PROPN
esrj-65577	10	53	.	.	PROPN
esrj-65577	10	54	,	,	PUNCT
esrj-65577	10	55	brazil	brazil	PROPN
esrj-65577	10	56	earth	earth	PROPN
esrj-65577	10	57	sciences	sciences	PROPN
esrj-65577	10	58	research	research	PROPN
esrj-65577	10	59	journal	journal	PROPN
esrj-65577	10	60	earth	earth	PROPN
esrj-65577	10	61	sci	sci	PROPN
esrj-65577	10	62	.	.	PUNCT
esrj-65577	11	1	res	res	PROPN
esrj-65577	11	2	.	.	PUNCT
esrj-65577	12	1	j.	j.	PROPN
esrj-65577	12	2	vol	vol	PROPN
esrj-65577	12	3	.	.	PROPN
esrj-65577	13	1	22	22	NUM
esrj-65577	13	2	,	,	PUNCT
esrj-65577	13	3	no	no	INTJ
esrj-65577	13	4	.	.	NOUN
esrj-65577	13	5	2	2	NUM
esrj-65577	13	6	(	(	PUNCT
esrj-65577	13	7	june	june	PROPN
esrj-65577	13	8	,	,	PUNCT
esrj-65577	13	9	2018	2018	NUM
esrj-65577	13	10	):	):	PUNCT
esrj-65577	13	11	83	83	NUM
esrj-65577	13	12	-	-	SYM
esrj-65577	13	13	90	90	NUM
esrj-65577	13	14	los	los	PROPN
esrj-65577	13	15	modelos	modelos	PROPN
esrj-65577	13	16	de	de	PROPN
esrj-65577	13	17	series	series	PROPN
esrj-65577	13	18	de	de	PROPN
esrj-65577	13	19	tiempo	tiempo	PROPN
esrj-65577	13	20	se	se	X
esrj-65577	13	21	usan	usan	PROPN
esrj-65577	13	22	a	a	DET
esrj-65577	13	23	menudo	menudo	NOUN
esrj-65577	13	24	en	en	ADP
esrj-65577	13	25	estudios	estudio	NOUN
esrj-65577	13	26	de	de	AUX
esrj-65577	13	27	hidrología	hidrología	PROPN
esrj-65577	13	28	y	y	PROPN
esrj-65577	13	29	meteorología	meteorología	VERB
esrj-65577	13	30	para	para	PROPN
esrj-65577	13	31	modelar	modelar	PROPN
esrj-65577	13	32	series	series	PROPN
esrj-65577	14	1	de	de	PROPN
esrj-65577	14	2	flujos	flujo	VERB
esrj-65577	14	3	a	a	DET
esrj-65577	14	4	fin	fin	NOUN
esrj-65577	14	5	de	de	X
esrj-65577	14	6	hacer	hacer	PROPN
esrj-65577	14	7	pronósticos	pronósticos	PROPN
esrj-65577	14	8	y	y	PROPN
esrj-65577	14	9	generar	generar	PROPN
esrj-65577	14	10	series	series	NOUN
esrj-65577	14	11	sintéticas	sintéticas	PROPN
esrj-65577	14	12	que	que	PROPN
esrj-65577	14	13	son	son	PROPN
esrj-65577	14	14	insumos	insumos	PROPN
esrj-65577	14	15	para	para	PROPN
esrj-65577	14	16	el	el	PROPN
esrj-65577	14	17	análisis	análisis	PROPN
esrj-65577	14	18	de	de	PROPN
esrj-65577	14	19	sistemas	sistemas	PROPN
esrj-65577	14	20	complejos	complejos	PROPN
esrj-65577	14	21	de	de	PROPN
esrj-65577	14	22	recursos	recursos	X
esrj-65577	14	23	hídricos	hídricos	PROPN
esrj-65577	14	24	.	.	PUNCT
esrj-65577	15	1	en	en	ADP
esrj-65577	15	2	este	este	PROPN
esrj-65577	15	3	artículo	artículo	PROPN
esrj-65577	15	4	presentamos	presentamos	PROPN
esrj-65577	15	5	un	un	PROPN
esrj-65577	15	6	nuevo	nuevo	PROPN
esrj-65577	15	7	enfoque	enfoque	PROPN
esrj-65577	15	8	de	de	X
esrj-65577	15	9	modelado	modelado	X
esrj-65577	15	10	para	para	PROPN
esrj-65577	15	11	series	series	PROPN
esrj-65577	15	12	de	de	PROPN
esrj-65577	15	13	tiempo	tiempo	PROPN
esrj-65577	15	14	hidrológicas	hidrológica	NOUN
esrj-65577	15	15	y	y	PROPN
esrj-65577	15	16	meteorológicas	meteorológicas	PROPN
esrj-65577	15	17	asumiendo	asumiendo	PROPN
esrj-65577	15	18	una	una	PROPN
esrj-65577	15	19	distribución	distribución	PROPN
esrj-65577	15	20	continua	continua	PROPN
esrj-65577	15	21	para	para	PROPN
esrj-65577	15	22	los	los	PROPN
esrj-65577	15	23	datos	datos	X
esrj-65577	15	24	,	,	PUNCT
esrj-65577	15	25	donde	donde	PROPN
esrj-65577	15	26	se	se	PROPN
esrj-65577	15	27	modelan	modelan	PROPN
esrj-65577	15	28	los	los	PROPN
esrj-65577	15	29	parámetros	parámetros	PROPN
esrj-65577	15	30	tanto	tanto	PROPN
esrj-65577	15	31	de	de	X
esrj-65577	15	32	la	la	X
esrj-65577	15	33	media	media	PROPN
esrj-65577	15	34	condicional	condicional	PROPN
esrj-65577	15	35	como	como	PROPN
esrj-65577	15	36	de	de	X
esrj-65577	15	37	la	la	PROPN
esrj-65577	15	38	varianza	varianza	PROPN
esrj-65577	15	39	condicional	condicional	PROPN
esrj-65577	15	40	.	.	PUNCT
esrj-65577	16	1	métodos	métodos	PROPN
esrj-65577	16	2	bayesianos	bayesianos	PROPN
esrj-65577	16	3	estándares	estándare	NOUN
esrj-65577	16	4	que	que	PROPN
esrj-65577	16	5	usan	usan	PROPN
esrj-65577	16	6	mcmc	mcmc	PROPN
esrj-65577	16	7	(	(	PUNCT
esrj-65577	16	8	markov	markov	PROPN
esrj-65577	16	9	chain	chain	NOUN
esrj-65577	16	10	monte	monte	PROPN
esrj-65577	16	11	carlo	carlo	PROPN
esrj-65577	16	12	)	)	PUNCT
esrj-65577	16	13	son	son	NOUN
esrj-65577	16	14	usados	usados	PROPN
esrj-65577	16	15	para	para	PROPN
esrj-65577	16	16	simular	simular	ADV
esrj-65577	16	17	muestras	muestras	X
esrj-65577	16	18	de	de	PROPN
esrj-65577	16	19	la	la	PROPN
esrj-65577	16	20	distribución	distribución	PROPN
esrj-65577	16	21	a	a	DET
esrj-65577	16	22	posteriori	posteriori	NOUN
esrj-65577	16	23	conjunta	conjunta	PROPN
esrj-65577	16	24	de	de	X
esrj-65577	16	25	interés	interés	PROPN
esrj-65577	16	26	.	.	PUNCT
esrj-65577	17	1	dos	dos	PROPN
esrj-65577	17	2	aplicaciones	aplicaciones	PROPN
esrj-65577	17	3	a	a	DET
esrj-65577	17	4	conjuntos	conjuntos	PROPN
esrj-65577	17	5	de	de	PROPN
esrj-65577	17	6	datos	datos	X
esrj-65577	17	7	reales	real	NOUN
esrj-65577	17	8	ilustran	ilustran	VERB
esrj-65577	17	9	la	la	PRON
esrj-65577	17	10	metodología	metodología	PROPN
esrj-65577	17	11	propuesta	propuesta	PROPN
esrj-65577	17	12	,	,	PUNCT
esrj-65577	17	13	asumiendo	asumiendo	PROPN
esrj-65577	17	14	que	que	PROPN
esrj-65577	17	15	las	las	PROPN
esrj-65577	17	16	observaciones	observaciones	PROPN
esrj-65577	17	17	provienen	provienen	PROPN
esrj-65577	17	18	de	de	PROPN
esrj-65577	17	19	una	una	PROPN
esrj-65577	17	20	distribución	distribución	PROPN
esrj-65577	17	21	normal	normal	ADJ
esrj-65577	17	22	,	,	PUNCT
esrj-65577	17	23	gamma	gamma	NOUN
esrj-65577	17	24	o	o	PROPN
esrj-65577	17	25	beta	beta	PROPN
esrj-65577	17	26	.	.	PUNCT
esrj-65577	18	1	un	un	PROPN
esrj-65577	18	2	primer	primer	PROPN
esrj-65577	18	3	ejemplo	ejemplo	PROPN
esrj-65577	18	4	está	está	PROPN
esrj-65577	18	5	dado	dado	PROPN
esrj-65577	18	6	por	por	PROPN
esrj-65577	18	7	una	una	PROPN
esrj-65577	18	8	serie	serie	X
esrj-65577	18	9	temporal	temporal	ADJ
esrj-65577	18	10	de	de	X
esrj-65577	18	11	promedios	promedio	NOUN
esrj-65577	18	12	mensuales	mensuale	NOUN
esrj-65577	18	13	de	de	X
esrj-65577	18	14	los	los	PROPN
esrj-65577	18	15	caudales	caudales	PROPN
esrj-65577	18	16	naturales	naturale	NOUN
esrj-65577	18	17	,	,	PUNCT
esrj-65577	18	18	medidos	medido	NOUN
esrj-65577	18	19	en	en	ADP
esrj-65577	18	20	el	el	PROPN
esrj-65577	18	21	período	período	PROPN
esrj-65577	18	22	anual	anual	PROPN
esrj-65577	18	23	que	que	PROPN
esrj-65577	18	24	va	va	PROPN
esrj-65577	18	25	de	de	PROPN
esrj-65577	18	26	1931	1931	NUM
esrj-65577	18	27	a	a	DET
esrj-65577	18	28	2010	2010	NUM
esrj-65577	18	29	en	en	X
esrj-65577	18	30	la	la	PROPN
esrj-65577	18	31	presa	presa	PROPN
esrj-65577	18	32	hidroeléctrica	hidroeléctrica	PROPN
esrj-65577	18	33	de	de	PROPN
esrj-65577	18	34	furnas	furnas	PROPN
esrj-65577	18	35	,	,	PUNCT
esrj-65577	18	36	brasil	brasil	PROPN
esrj-65577	18	37	.	.	PUNCT
esrj-65577	19	1	un	un	PROPN
esrj-65577	19	2	segundo	segundo	PROPN
esrj-65577	19	3	ejemplo	ejemplo	PROPN
esrj-65577	19	4	considera	considera	PROPN
esrj-65577	19	5	una	una	PROPN
esrj-65577	19	6	serie	serie	PROPN
esrj-65577	19	7	temporal	temporal	PROPN
esrj-65577	19	8	de	de	X
esrj-65577	19	9	313	313	NUM
esrj-65577	19	10	datos	dato	NOUN
esrj-65577	19	11	de	de	PROPN
esrj-65577	19	12	humedad	humedad	X
esrj-65577	19	13	del	del	PROPN
esrj-65577	19	14	aire	aire	PROPN
esrj-65577	19	15	medidos	medido	NOUN
esrj-65577	19	16	en	en	ADP
esrj-65577	19	17	una	una	PROPN
esrj-65577	19	18	estación	estación	PROPN
esrj-65577	19	19	meteorológica	meteorológica	PROPN
esrj-65577	19	20	de	de	PROPN
esrj-65577	19	21	río	río	PROPN
esrj-65577	19	22	claro	claro	PROPN
esrj-65577	19	23	,	,	PUNCT
esrj-65577	19	24	una	una	PROPN
esrj-65577	19	25	ciudad	ciudad	PROPN
esrj-65577	19	26	brasileña	brasileña	PROPN
esrj-65577	19	27	ubicada	ubicada	PROPN
esrj-65577	19	28	en	en	PROPN
esrj-65577	19	29	el	el	PROPN
esrj-65577	19	30	sureste	sureste	PROPN
esrj-65577	19	31	de	de	PROPN
esrj-65577	19	32	brasil	brasil	PROPN
esrj-65577	19	33	.	.	PUNCT
esrj-65577	20	1	estas	estas	PROPN
esrj-65577	20	2	aplicaciones	aplicaciones	PROPN
esrj-65577	20	3	nos	nos	PROPN
esrj-65577	20	4	motivan	motivan	PROPN
esrj-65577	20	5	a	a	DET
esrj-65577	20	6	introducir	introducir	PROPN
esrj-65577	20	7	nuevas	nuevas	PROPN
esrj-65577	20	8	clases	clases	PROPN
esrj-65577	20	9	de	de	PROPN
esrj-65577	20	10	modelos	modelos	PROPN
esrj-65577	20	11	para	para	PROPN
esrj-65577	20	12	analizar	analizar	PROPN
esrj-65577	20	13	series	series	PROPN
esrj-65577	20	14	de	de	PROPN
esrj-65577	20	15	tiempo	tiempo	PROPN
esrj-65577	20	16	hidrológicas	hidrológica	NOUN
esrj-65577	20	17	y	y	PROPN
esrj-65577	20	18	meteorológicas	meteorológicas	PROPN
esrj-65577	20	19	.	.	PUNCT
esrj-65577	21	1	resumen	resuman	NOUN
esrj-65577	21	2	palabras	palabras	PROPN
esrj-65577	21	3	clave	clave	PROPN
esrj-65577	21	4	:	:	PUNCT
esrj-65577	21	5	:	:	PUNCT
esrj-65577	21	6	series	series	PROPN
esrj-65577	21	7	de	de	PROPN
esrj-65577	21	8	tiempo	tiempo	PROPN
esrj-65577	21	9	hidrológicas	hidrológicas	NOUN
esrj-65577	21	10	;	;	PUNCT
esrj-65577	21	11	series	series	PROPN
esrj-65577	21	12	de	de	PROPN
esrj-65577	21	13	tiempo	tiempo	PROPN
esrj-65577	21	14	meteorológicas	meteorológicas	PROPN
esrj-65577	21	15	;	;	PUNCT
esrj-65577	21	16	modelos	modelos	PROPN
esrj-65577	21	17	de	de	PROPN
esrj-65577	21	18	regresión	regresión	PROPN
esrj-65577	21	19	condicional	condicional	PROPN
esrj-65577	21	20	;	;	PUNCT
esrj-65577	21	21	análisis	análisis	NOUN
esrj-65577	21	22	bayesiano	bayesiano	ADV
esrj-65577	21	23	;	;	PUNCT
esrj-65577	21	24	métodos	métodos	PROPN
esrj-65577	21	25	mcmc	mcmc	PROPN
esrj-65577	21	26	.	.	PUNCT
esrj-65577	22	1	record	record	NOUN
esrj-65577	22	2	manuscript	manuscript	NOUN
esrj-65577	22	3	received	receive	VERB
esrj-65577	22	4	:	:	PUNCT
esrj-65577	22	5	09/06/2017	09/06/2017	NUM
esrj-65577	22	6	accepted	accept	VERB
esrj-65577	22	7	for	for	ADP
esrj-65577	22	8	publication	publication	NOUN
esrj-65577	22	9	:	:	PUNCT
esrj-65577	22	10	27/04/2018	27/04/2018	NUM
esrj-65577	22	11	how	how	SCONJ
esrj-65577	22	12	to	to	PART
esrj-65577	22	13	cite	cite	VERB
esrj-65577	22	14	item	item	PROPN
esrj-65577	22	15	cepeda	cepeda	PROPN
esrj-65577	22	16	-	-	PUNCT
esrj-65577	22	17	cuervo	cuervo	PROPN
esrj-65577	22	18	,	,	PUNCT
esrj-65577	22	19	e.	e.	PROPN
esrj-65577	22	20	,	,	PUNCT
esrj-65577	22	21	achcar	achcar	NOUN
esrj-65577	22	22	,	,	PUNCT
esrj-65577	22	23	j.	j.	PROPN
esrj-65577	22	24	a.	a.	PROPN
esrj-65577	22	25	,	,	PUNCT
esrj-65577	22	26	&	&	CCONJ
esrj-65577	22	27	andrade	andrade	PROPN
esrj-65577	22	28	,	,	PUNCT
esrj-65577	22	29	m.	m.	NOUN
esrj-65577	22	30	g.	g.	PROPN
esrj-65577	22	31	(	(	PUNCT
esrj-65577	22	32	2018	2018	NUM
esrj-65577	22	33	)	)	PUNCT
esrj-65577	22	34	.	.	PUNCT
esrj-65577	23	1	seasonal	seasonal	ADJ
esrj-65577	23	2	hydrological	hydrological	ADJ
esrj-65577	23	3	and	and	CCONJ
esrj-65577	23	4	meteorological	meteorological	ADJ
esrj-65577	23	5	time	time	NOUN
esrj-65577	23	6	series	series	PROPN
esrj-65577	23	7	.	.	PUNCT
esrj-65577	24	1	earth	earth	PROPN
esrj-65577	24	2	sciences	sciences	PROPN
esrj-65577	24	3	research	research	PROPN
esrj-65577	24	4	journal	journal	PROPN
esrj-65577	24	5	,	,	PUNCT
esrj-65577	24	6	22(2	22(2	NUM
esrj-65577	24	7	)	)	PUNCT
esrj-65577	24	8	,	,	PUNCT
esrj-65577	24	9	83	83	NUM
esrj-65577	24	10	-	-	SYM
esrj-65577	24	11	90	90	NUM
esrj-65577	24	12	.	.	PUNCT
esrj-65577	25	1	doi	doi	NOUN
esrj-65577	25	2	:	:	PUNCT
esrj-65577	25	3	http://dx.doi.org/10.15446/esrj.v22n2.65577	http://dx.doi.org/10.15446/esrj.v22n2.65577	PROPN
esrj-65577	25	4	series	series	NOUN
esrj-65577	25	5	de	de	X
esrj-65577	25	6	tiempo	tiempo	PROPN
esrj-65577	25	7	hidrológicas	hidrológica	NOUN
esrj-65577	25	8	y	y	PROPN
esrj-65577	25	9	meteorológicas	meteorológicas	PROPN
esrj-65577	25	10	estacionales	estacionale	NOUN
esrj-65577	26	1	h	h	NOUN
esrj-65577	26	2	y	y	PROPN
esrj-65577	27	1	d	d	NOUN
esrj-65577	27	2	r	r	NOUN
esrj-65577	27	3	o	o	X
esrj-65577	27	4	m	m	VERB
esrj-65577	27	5	et	et	NOUN
esrj-65577	27	6	eo	eo	NOUN
esrj-65577	27	7	r	r	NOUN
esrj-65577	27	8	o	o	NOUN
esrj-65577	28	1	lo	lo	NOUN
esrj-65577	28	2	g	g	PROPN
esrj-65577	28	3	y	y	PROPN
esrj-65577	28	4	84	84	NUM
esrj-65577	28	5	edilberto	edilberto	VERB
esrj-65577	28	6	cepeda	cepeda	PROPN
esrj-65577	28	7	cuervo	cuervo	PROPN
esrj-65577	28	8	,	,	PUNCT
esrj-65577	28	9	jorge	jorge	PROPN
esrj-65577	28	10	alberto	alberto	PROPN
esrj-65577	28	11	achcar	achcar	PROPN
esrj-65577	28	12	,	,	PUNCT
esrj-65577	28	13	marinho	marinho	PROPN
esrj-65577	28	14	g.	g.	PROPN
esrj-65577	28	15	andrade	andrade	PROPN
esrj-65577	29	1	1	1	X
esrj-65577	29	2	.	.	PUNCT
esrj-65577	29	3	introduction	introduction	NOUN
esrj-65577	29	4	time	time	NOUN
esrj-65577	29	5	series	series	PROPN
esrj-65577	29	6	models	model	NOUN
esrj-65577	29	7	are	be	AUX
esrj-65577	29	8	often	often	ADV
esrj-65577	29	9	used	use	VERB
esrj-65577	29	10	in	in	ADP
esrj-65577	29	11	hydrology	hydrology	NOUN
esrj-65577	29	12	studies	study	NOUN
esrj-65577	29	13	to	to	PART
esrj-65577	29	14	model	model	VERB
esrj-65577	29	15	streamflow	streamflow	PROPN
esrj-65577	29	16	series	series	PROPN
esrj-65577	29	17	in	in	ADP
esrj-65577	29	18	order	order	NOUN
esrj-65577	29	19	to	to	PART
esrj-65577	29	20	make	make	VERB
esrj-65577	29	21	predictions	prediction	NOUN
esrj-65577	29	22	and	and	CCONJ
esrj-65577	29	23	to	to	PART
esrj-65577	29	24	generate	generate	VERB
esrj-65577	29	25	synthetic	synthetic	ADJ
esrj-65577	29	26	series	series	NOUN
esrj-65577	29	27	which	which	PRON
esrj-65577	29	28	are	be	AUX
esrj-65577	29	29	inputs	input	NOUN
esrj-65577	29	30	for	for	ADP
esrj-65577	29	31	the	the	DET
esrj-65577	29	32	analysis	analysis	NOUN
esrj-65577	29	33	of	of	ADP
esrj-65577	29	34	complex	complex	ADJ
esrj-65577	29	35	water	water	NOUN
esrj-65577	29	36	resources	resource	NOUN
esrj-65577	29	37	systems	system	NOUN
esrj-65577	29	38	(	(	PUNCT
esrj-65577	29	39	see	see	VERB
esrj-65577	29	40	,	,	PUNCT
esrj-65577	29	41	for	for	ADP
esrj-65577	29	42	example	example	NOUN
esrj-65577	29	43	,	,	PUNCT
esrj-65577	29	44	salas	salas	PROPN
esrj-65577	29	45	et	et	NOUN
esrj-65577	29	46	al	al	PROPN
esrj-65577	29	47	.	.	PROPN
esrj-65577	29	48	,	,	PUNCT
esrj-65577	29	49	1980	1980	NUM
esrj-65577	29	50	,	,	PUNCT
esrj-65577	29	51	1982	1982	NUM
esrj-65577	29	52	;	;	PUNCT
esrj-65577	29	53	hosking	hosking	PROPN
esrj-65577	29	54	,	,	PUNCT
esrj-65577	29	55	1984	1984	NUM
esrj-65577	29	56	;	;	PUNCT
esrj-65577	29	57	hipel	hipel	PROPN
esrj-65577	29	58	&	&	CCONJ
esrj-65577	29	59	mcleod	mcleod	PROPN
esrj-65577	29	60	,	,	PUNCT
esrj-65577	29	61	1994	1994	NUM
esrj-65577	29	62	;	;	PUNCT
esrj-65577	29	63	montanari	montanari	PROPN
esrj-65577	29	64	et	et	PROPN
esrj-65577	29	65	al	al	PROPN
esrj-65577	29	66	.	.	PROPN
esrj-65577	29	67	,	,	PUNCT
esrj-65577	29	68	1997	1997	NUM
esrj-65577	29	69	;	;	PUNCT
esrj-65577	29	70	hasebe	hasebe	PROPN
esrj-65577	29	71	et	et	PROPN
esrj-65577	29	72	al	al	PROPN
esrj-65577	29	73	.	.	PROPN
esrj-65577	29	74	,	,	PUNCT
esrj-65577	29	75	2000	2000	NUM
esrj-65577	29	76	)	)	PUNCT
esrj-65577	29	77	.	.	PUNCT
esrj-65577	30	1	in	in	ADP
esrj-65577	30	2	many	many	ADJ
esrj-65577	30	3	studies	study	NOUN
esrj-65577	30	4	,	,	PUNCT
esrj-65577	30	5	hydrologists	hydrologist	NOUN
esrj-65577	30	6	also	also	ADV
esrj-65577	30	7	use	use	VERB
esrj-65577	30	8	time	time	NOUN
esrj-65577	30	9	series	series	PROPN
esrj-65577	30	10	data	datum	NOUN
esrj-65577	30	11	to	to	PART
esrj-65577	30	12	display	display	VERB
esrj-65577	30	13	the	the	DET
esrj-65577	30	14	amount	amount	NOUN
esrj-65577	30	15	of	of	ADP
esrj-65577	30	16	rainfall	rainfall	NOUN
esrj-65577	30	17	that	that	PRON
esrj-65577	30	18	has	have	AUX
esrj-65577	30	19	fallen	fall	VERB
esrj-65577	30	20	in	in	ADP
esrj-65577	30	21	a	a	DET
esrj-65577	30	22	region	region	NOUN
esrj-65577	30	23	for	for	ADP
esrj-65577	30	24	the	the	DET
esrj-65577	30	25	past	past	ADJ
esrj-65577	30	26	day	day	NOUN
esrj-65577	30	27	,	,	PUNCT
esrj-65577	30	28	year	year	NOUN
esrj-65577	30	29	or	or	CCONJ
esrj-65577	30	30	a	a	DET
esrj-65577	30	31	period	period	NOUN
esrj-65577	30	32	of	of	ADP
esrj-65577	30	33	10	10	NUM
esrj-65577	30	34	years	year	NOUN
esrj-65577	30	35	(	(	PUNCT
esrj-65577	30	36	see	see	VERB
esrj-65577	30	37	for	for	ADP
esrj-65577	30	38	example	example	NOUN
esrj-65577	30	39	,	,	PUNCT
esrj-65577	30	40	guimaraes	guimaraes	PROPN
esrj-65577	30	41	&	&	CCONJ
esrj-65577	30	42	santos	santos	PROPN
esrj-65577	30	43	,	,	PUNCT
esrj-65577	30	44	2011	2011	NUM
esrj-65577	30	45	,	,	PUNCT
esrj-65577	30	46	and	and	CCONJ
esrj-65577	30	47	lee	lee	PROPN
esrj-65577	30	48	&	&	CCONJ
esrj-65577	30	49	lee	lee	PROPN
esrj-65577	30	50	,	,	PUNCT
esrj-65577	30	51	2000	2000	NUM
esrj-65577	30	52	)	)	PUNCT
esrj-65577	30	53	.	.	PUNCT
esrj-65577	31	1	modeling	model	VERB
esrj-65577	31	2	hydrological	hydrological	ADJ
esrj-65577	31	3	variability	variability	NOUN
esrj-65577	31	4	is	be	AUX
esrj-65577	31	5	very	very	ADV
esrj-65577	31	6	important	important	ADJ
esrj-65577	31	7	in	in	ADP
esrj-65577	31	8	the	the	DET
esrj-65577	31	9	planning	planning	NOUN
esrj-65577	31	10	and	and	CCONJ
esrj-65577	31	11	management	management	NOUN
esrj-65577	31	12	of	of	ADP
esrj-65577	31	13	water	water	NOUN
esrj-65577	31	14	resources	resource	NOUN
esrj-65577	31	15	.	.	PUNCT
esrj-65577	32	1	many	many	ADJ
esrj-65577	32	2	aspects	aspect	NOUN
esrj-65577	32	3	of	of	ADP
esrj-65577	32	4	the	the	DET
esrj-65577	32	5	hydrologic	hydrologic	ADJ
esrj-65577	32	6	cycle	cycle	NOUN
esrj-65577	32	7	could	could	AUX
esrj-65577	32	8	be	be	AUX
esrj-65577	32	9	described	describe	VERB
esrj-65577	32	10	by	by	ADP
esrj-65577	32	11	time	time	NOUN
esrj-65577	32	12	series	series	PROPN
esrj-65577	32	13	data	data	PROPN
esrj-65577	32	14	.	.	PUNCT
esrj-65577	33	1	researchers	researcher	NOUN
esrj-65577	33	2	,	,	PUNCT
esrj-65577	33	3	usually	usually	ADV
esrj-65577	33	4	use	use	VERB
esrj-65577	33	5	time	time	NOUN
esrj-65577	33	6	series	series	PROPN
esrj-65577	33	7	data	datum	NOUN
esrj-65577	33	8	to	to	PART
esrj-65577	33	9	evaluate	evaluate	VERB
esrj-65577	33	10	the	the	DET
esrj-65577	33	11	resources	resource	NOUN
esrj-65577	33	12	of	of	ADP
esrj-65577	33	13	a	a	DET
esrj-65577	33	14	water	water	NOUN
esrj-65577	33	15	basin	basin	NOUN
esrj-65577	33	16	.	.	PUNCT
esrj-65577	34	1	important	important	ADJ
esrj-65577	34	2	variables	variable	NOUN
esrj-65577	34	3	related	relate	VERB
esrj-65577	34	4	to	to	ADP
esrj-65577	34	5	streamflow	streamflow	NOUN
esrj-65577	34	6	and	and	CCONJ
esrj-65577	34	7	watershed	watershed	PROPN
esrj-65577	34	8	describes	describe	VERB
esrj-65577	34	9	streamflow	streamflow	NOUN
esrj-65577	34	10	properties	property	NOUN
esrj-65577	34	11	such	such	ADJ
esrj-65577	34	12	as	as	ADP
esrj-65577	34	13	monthly	monthly	ADJ
esrj-65577	34	14	flows	flow	NOUN
esrj-65577	34	15	or	or	CCONJ
esrj-65577	34	16	streamflow	streamflow	NOUN
esrj-65577	34	17	parameters	parameter	NOUN
esrj-65577	34	18	.	.	PUNCT
esrj-65577	35	1	assuming	assume	VERB
esrj-65577	35	2	a	a	DET
esrj-65577	35	3	specified	specify	VERB
esrj-65577	35	4	time	time	NOUN
esrj-65577	35	5	series	series	PROPN
esrj-65577	35	6	model	model	PROPN
esrj-65577	35	7	,	,	PUNCT
esrj-65577	35	8	we	we	PRON
esrj-65577	35	9	usually	usually	ADV
esrj-65577	35	10	could	could	AUX
esrj-65577	35	11	estimate	estimate	VERB
esrj-65577	35	12	the	the	DET
esrj-65577	35	13	streamflow	streamflow	NOUN
esrj-65577	35	14	parameters	parameter	NOUN
esrj-65577	35	15	using	use	VERB
esrj-65577	35	16	a	a	DET
esrj-65577	35	17	classical	classical	ADJ
esrj-65577	35	18	or	or	CCONJ
esrj-65577	35	19	a	a	DET
esrj-65577	35	20	bayesian	bayesian	NOUN
esrj-65577	35	21	inference	inference	NOUN
esrj-65577	35	22	approach	approach	NOUN
esrj-65577	35	23	.	.	PUNCT
esrj-65577	36	1	different	different	ADJ
esrj-65577	36	2	time	time	NOUN
esrj-65577	36	3	series	series	PROPN
esrj-65577	36	4	models	model	NOUN
esrj-65577	36	5	as	as	ADP
esrj-65577	36	6	arma	arma	NOUN
esrj-65577	36	7	and	and	CCONJ
esrj-65577	36	8	higher	high	ADJ
esrj-65577	36	9	orders	order	NOUN
esrj-65577	36	10	of	of	ADP
esrj-65577	36	11	ma	ma	PROPN
esrj-65577	36	12	models	model	NOUN
esrj-65577	36	13	have	have	AUX
esrj-65577	36	14	been	be	AUX
esrj-65577	36	15	used	use	VERB
esrj-65577	36	16	by	by	ADP
esrj-65577	36	17	some	some	DET
esrj-65577	36	18	authors	author	NOUN
esrj-65577	36	19	when	when	SCONJ
esrj-65577	36	20	considering	consider	VERB
esrj-65577	36	21	hydrologic	hydrologic	ADJ
esrj-65577	36	22	regionalization	regionalization	NOUN
esrj-65577	36	23	of	of	ADP
esrj-65577	36	24	watersheds	watershed	NOUN
esrj-65577	36	25	(	(	PUNCT
esrj-65577	36	26	see	see	VERB
esrj-65577	36	27	for	for	ADP
esrj-65577	36	28	example	example	NOUN
esrj-65577	36	29	,	,	PUNCT
esrj-65577	36	30	chiang	chiang	PROPN
esrj-65577	36	31	et	et	PROPN
esrj-65577	36	32	al	al	PROPN
esrj-65577	36	33	.	.	PROPN
esrj-65577	36	34	,	,	PUNCT
esrj-65577	36	35	2002	2002	NUM
esrj-65577	36	36	a	a	PRON
esrj-65577	36	37	,	,	PUNCT
esrj-65577	36	38	b	b	NOUN
esrj-65577	36	39	;	;	PUNCT
esrj-65577	36	40	wang	wang	PROPN
esrj-65577	36	41	et	et	PROPN
esrj-65577	36	42	al	al	PROPN
esrj-65577	36	43	.	.	PROPN
esrj-65577	36	44	,	,	PUNCT
esrj-65577	36	45	2015	2015	NUM
esrj-65577	36	46	)	)	PUNCT
esrj-65577	36	47	.	.	PUNCT
esrj-65577	37	1	valipour	valipour	NUM
esrj-65577	37	2	et	et	PROPN
esrj-65577	37	3	al.(2013	al.(2013	PROPN
esrj-65577	37	4	)	)	PUNCT
esrj-65577	37	5	studied	study	VERB
esrj-65577	37	6	annual	annual	ADJ
esrj-65577	37	7	runoff	runoff	NOUN
esrj-65577	37	8	time	time	NOUN
esrj-65577	37	9	series	series	PROPN
esrj-65577	37	10	in	in	ADP
esrj-65577	37	11	dahuofang	dahuofang	PROPN
esrj-65577	37	12	reservoir	reservoir	PROPN
esrj-65577	37	13	,	,	PUNCT
esrj-65577	37	14	in	in	ADP
esrj-65577	37	15	northeast	northeast	ADJ
esrj-65577	37	16	china	china	PROPN
esrj-65577	37	17	,	,	PUNCT
esrj-65577	37	18	using	use	VERB
esrj-65577	37	19	autoregressive	autoregressive	ADJ
esrj-65577	37	20	integrated	integrated	ADJ
esrj-65577	37	21	moving	move	VERB
esrj-65577	37	22	average	average	ADJ
esrj-65577	37	23	(	(	PUNCT
esrj-65577	37	24	arima	arima	NOUN
esrj-65577	37	25	)	)	PUNCT
esrj-65577	37	26	models	model	NOUN
esrj-65577	37	27	coupled	couple	VERB
esrj-65577	37	28	with	with	ADP
esrj-65577	37	29	ensemble	ensemble	ADJ
esrj-65577	37	30	empirical	empirical	ADJ
esrj-65577	37	31	mode	mode	NOUN
esrj-65577	37	32	decomposition	decomposition	NOUN
esrj-65577	37	33	(	(	PUNCT
esrj-65577	37	34	wu	wu	PROPN
esrj-65577	37	35	,	,	PUNCT
esrj-65577	37	36	z.	z.	PROPN
esrj-65577	37	37	,	,	PUNCT
esrj-65577	37	38	&	&	CCONJ
esrj-65577	37	39	huang	huang	PROPN
esrj-65577	37	40	,	,	PUNCT
esrj-65577	37	41	n.	n.	PROPN
esrj-65577	37	42	e.	e.	PROPN
esrj-65577	37	43	,	,	PUNCT
esrj-65577	37	44	2009	2009	NUM
esrj-65577	37	45	)	)	PUNCT
esrj-65577	37	46	.	.	PUNCT
esrj-65577	38	1	spectral	spectral	ADJ
esrj-65577	38	2	analysis	analysis	NOUN
esrj-65577	38	3	and	and	CCONJ
esrj-65577	38	4	forecasting	forecasting	NOUN
esrj-65577	38	5	of	of	ADP
esrj-65577	38	6	hydrological	hydrological	ADJ
esrj-65577	38	7	time	time	NOUN
esrj-65577	38	8	series	series	PROPN
esrj-65577	38	9	has	have	AUX
esrj-65577	38	10	also	also	ADV
esrj-65577	38	11	been	be	AUX
esrj-65577	38	12	considered	consider	VERB
esrj-65577	38	13	(	(	PUNCT
esrj-65577	38	14	marques	marques	X
esrj-65577	38	15	et	et	PROPN
esrj-65577	38	16	al	al	PROPN
esrj-65577	38	17	.	.	PROPN
esrj-65577	38	18	,	,	PUNCT
esrj-65577	38	19	2006	2006	NUM
esrj-65577	38	20	)	)	PUNCT
esrj-65577	38	21	,	,	PUNCT
esrj-65577	38	22	including	include	VERB
esrj-65577	38	23	geostatistical	geostatistical	ADJ
esrj-65577	38	24	applications	application	NOUN
esrj-65577	38	25	(	(	PUNCT
esrj-65577	38	26	robin	robin	PROPN
esrj-65577	38	27	et	et	PROPN
esrj-65577	38	28	al	al	PROPN
esrj-65577	38	29	.	.	PROPN
esrj-65577	38	30	,	,	PUNCT
esrj-65577	38	31	1993	1993	NUM
esrj-65577	38	32	)	)	PUNCT
esrj-65577	38	33	and	and	CCONJ
esrj-65577	38	34	climate	climate	NOUN
esrj-65577	38	35	change	change	NOUN
esrj-65577	38	36	investigations	investigation	NOUN
esrj-65577	38	37	(	(	PUNCT
esrj-65577	38	38	lall	lall	PROPN
esrj-65577	38	39	and	and	CCONJ
esrj-65577	38	40	mann	mann	PROPN
esrj-65577	38	41	,	,	PUNCT
esrj-65577	38	42	1995	1995	NUM
esrj-65577	38	43	)	)	PUNCT
esrj-65577	38	44	.	.	PUNCT
esrj-65577	39	1	considering	consider	VERB
esrj-65577	39	2	hydrological	hydrological	ADJ
esrj-65577	39	3	time	time	NOUN
esrj-65577	39	4	series	series	PROPN
esrj-65577	39	5	,	,	PUNCT
esrj-65577	39	6	the	the	DET
esrj-65577	39	7	monthly	monthly	ADJ
esrj-65577	39	8	streamflow	streamflow	PROPN
esrj-65577	39	9	series	series	NOUN
esrj-65577	39	10	typically	typically	ADV
esrj-65577	39	11	have	have	VERB
esrj-65577	39	12	a	a	DET
esrj-65577	39	13	periodic	periodic	ADJ
esrj-65577	39	14	behavior	behavior	NOUN
esrj-65577	39	15	in	in	ADP
esrj-65577	39	16	the	the	DET
esrj-65577	39	17	mean	mean	NOUN
esrj-65577	39	18	and	and	CCONJ
esrj-65577	39	19	variance	variance	NOUN
esrj-65577	39	20	and	and	CCONJ
esrj-65577	39	21	in	in	ADP
esrj-65577	39	22	general	general	ADJ
esrj-65577	39	23	,	,	PUNCT
esrj-65577	39	24	periodic	periodic	ADJ
esrj-65577	39	25	autoregressive	autoregressive	ADJ
esrj-65577	39	26	models	model	NOUN
esrj-65577	39	27	are	be	AUX
esrj-65577	39	28	used	use	VERB
esrj-65577	39	29	in	in	ADP
esrj-65577	39	30	de	de	ADP
esrj-65577	39	31	analysis	analysis	NOUN
esrj-65577	39	32	of	of	ADP
esrj-65577	39	33	the	the	DET
esrj-65577	39	34	data	datum	NOUN
esrj-65577	39	35	(	(	PUNCT
esrj-65577	39	36	see	see	VERB
esrj-65577	39	37	,	,	PUNCT
esrj-65577	39	38	for	for	ADP
esrj-65577	39	39	example	example	NOUN
esrj-65577	39	40	,	,	PUNCT
esrj-65577	39	41	modal	modal	NOUN
esrj-65577	39	42	&	&	CCONJ
esrj-65577	39	43	wasimi	wasimi	NOUN
esrj-65577	39	44	,	,	PUNCT
esrj-65577	39	45	2006	2006	NUM
esrj-65577	39	46	)	)	PUNCT
esrj-65577	39	47	.	.	PUNCT
esrj-65577	40	1	in	in	ADP
esrj-65577	40	2	this	this	DET
esrj-65577	40	3	situation	situation	NOUN
esrj-65577	40	4	,	,	PUNCT
esrj-65577	40	5	usually	usually	ADV
esrj-65577	40	6	it	it	PRON
esrj-65577	40	7	is	be	AUX
esrj-65577	40	8	assumed	assume	VERB
esrj-65577	40	9	that	that	SCONJ
esrj-65577	40	10	the	the	DET
esrj-65577	40	11	series	series	NOUN
esrj-65577	40	12	flow	flow	NOUN
esrj-65577	40	13	has	have	VERB
esrj-65577	40	14	a	a	DET
esrj-65577	40	15	normal	normal	ADJ
esrj-65577	40	16	or	or	CCONJ
esrj-65577	40	17	log	log	NOUN
esrj-65577	40	18	-	-	PUNCT
esrj-65577	40	19	normal	normal	ADJ
esrj-65577	40	20	distribution	distribution	NOUN
esrj-65577	40	21	(	(	PUNCT
esrj-65577	40	22	see	see	VERB
esrj-65577	40	23	for	for	ADP
esrj-65577	40	24	example	example	NOUN
esrj-65577	40	25	,	,	PUNCT
esrj-65577	40	26	tesfaye	tesfaye	VERB
esrj-65577	40	27	et	et	PROPN
esrj-65577	40	28	al	al	PROPN
esrj-65577	40	29	.	.	PROPN
esrj-65577	40	30	,	,	PUNCT
esrj-65577	40	31	2006	2006	NUM
esrj-65577	40	32	;	;	PUNCT
esrj-65577	40	33	wang	wang	PROPN
esrj-65577	40	34	et	et	PROPN
esrj-65577	40	35	al	al	PROPN
esrj-65577	40	36	.	.	PROPN
esrj-65577	40	37	,	,	PUNCT
esrj-65577	40	38	2009	2009	NUM
esrj-65577	40	39	)	)	PUNCT
esrj-65577	40	40	.	.	PUNCT
esrj-65577	41	1	the	the	DET
esrj-65577	41	2	behavior	behavior	NOUN
esrj-65577	41	3	of	of	ADP
esrj-65577	41	4	meteorological	meteorological	ADJ
esrj-65577	41	5	time	time	NOUN
esrj-65577	41	6	series	series	NOUN
esrj-65577	41	7	is	be	AUX
esrj-65577	41	8	similar	similar	ADJ
esrj-65577	41	9	to	to	ADP
esrj-65577	41	10	the	the	DET
esrj-65577	41	11	behavior	behavior	NOUN
esrj-65577	41	12	of	of	ADP
esrj-65577	41	13	hydrological	hydrological	ADJ
esrj-65577	41	14	time	time	NOUN
esrj-65577	41	15	series	series	NOUN
esrj-65577	41	16	.	.	PUNCT
esrj-65577	42	1	in	in	ADP
esrj-65577	42	2	this	this	DET
esrj-65577	42	3	case	case	NOUN
esrj-65577	42	4	,	,	PUNCT
esrj-65577	42	5	given	give	VERB
esrj-65577	42	6	that	that	SCONJ
esrj-65577	42	7	the	the	DET
esrj-65577	42	8	relative	relative	ADJ
esrj-65577	42	9	air	air	NOUN
esrj-65577	42	10	humidity	humidity	NOUN
esrj-65577	42	11	is	be	AUX
esrj-65577	42	12	a	a	DET
esrj-65577	42	13	random	random	ADJ
esrj-65577	42	14	variable	variable	NOUN
esrj-65577	42	15	with	with	ADP
esrj-65577	42	16	values	value	NOUN
esrj-65577	42	17	given	give	VERB
esrj-65577	42	18	in	in	ADP
esrj-65577	42	19	the	the	DET
esrj-65577	42	20	open	open	ADJ
esrj-65577	42	21	interval	interval	NOUN
esrj-65577	42	22	(	(	PUNCT
esrj-65577	42	23	0	0	NUM
esrj-65577	42	24	,	,	PUNCT
esrj-65577	42	25	1	1	NUM
esrj-65577	42	26	)	)	PUNCT
esrj-65577	42	27	,	,	PUNCT
esrj-65577	42	28	we	we	PRON
esrj-65577	42	29	could	could	AUX
esrj-65577	42	30	assume	assume	VERB
esrj-65577	42	31	a	a	DET
esrj-65577	42	32	beta	beta	ADJ
esrj-65577	42	33	distribution	distribution	NOUN
esrj-65577	42	34	to	to	PART
esrj-65577	42	35	analyze	analyze	VERB
esrj-65577	42	36	the	the	DET
esrj-65577	42	37	data	datum	NOUN
esrj-65577	42	38	.	.	PUNCT
esrj-65577	43	1	another	another	DET
esrj-65577	43	2	possibility	possibility	NOUN
esrj-65577	43	3	to	to	PART
esrj-65577	43	4	analyze	analyze	VERB
esrj-65577	43	5	the	the	DET
esrj-65577	43	6	data	datum	NOUN
esrj-65577	43	7	set	set	VERB
esrj-65577	43	8	is	be	AUX
esrj-65577	43	9	to	to	PART
esrj-65577	43	10	consider	consider	VERB
esrj-65577	43	11	a	a	DET
esrj-65577	43	12	transformation	transformation	NOUN
esrj-65577	43	13	of	of	ADP
esrj-65577	43	14	the	the	DET
esrj-65577	43	15	data	datum	NOUN
esrj-65577	43	16	and	and	CCONJ
esrj-65577	43	17	to	to	PART
esrj-65577	43	18	assume	assume	VERB
esrj-65577	43	19	a	a	DET
esrj-65577	43	20	normal	normal	ADJ
esrj-65577	43	21	distribution	distribution	NOUN
esrj-65577	43	22	for	for	ADP
esrj-65577	43	23	the	the	DET
esrj-65577	43	24	transformed	transform	VERB
esrj-65577	43	25	data	datum	NOUN
esrj-65577	43	26	.	.	PUNCT
esrj-65577	44	1	as	as	ADP
esrj-65577	44	2	a	a	DET
esrj-65577	44	3	special	special	ADJ
esrj-65577	44	4	case	case	NOUN
esrj-65577	44	5	,	,	PUNCT
esrj-65577	44	6	we	we	PRON
esrj-65577	44	7	could	could	AUX
esrj-65577	44	8	assume	assume	VERB
esrj-65577	44	9	a	a	DET
esrj-65577	44	10	logistic	logistic	ADJ
esrj-65577	44	11	transformation	transformation	NOUN
esrj-65577	44	12	.	.	PUNCT
esrj-65577	45	1	in	in	ADP
esrj-65577	45	2	this	this	DET
esrj-65577	45	3	paper	paper	NOUN
esrj-65577	45	4	,	,	PUNCT
esrj-65577	45	5	a	a	DET
esrj-65577	45	6	more	more	ADV
esrj-65577	45	7	general	general	ADJ
esrj-65577	45	8	model	model	NOUN
esrj-65577	45	9	is	be	AUX
esrj-65577	45	10	considered	consider	VERB
esrj-65577	45	11	in	in	ADP
esrj-65577	45	12	the	the	DET
esrj-65577	45	13	analysis	analysis	NOUN
esrj-65577	45	14	of	of	ADP
esrj-65577	45	15	the	the	DET
esrj-65577	45	16	hydrological	hydrological	ADJ
esrj-65577	45	17	or	or	CCONJ
esrj-65577	45	18	meteorological	meteorological	ADJ
esrj-65577	45	19	time	time	NOUN
esrj-65577	45	20	series	series	NOUN
esrj-65577	45	21	conditional	conditional	ADJ
esrj-65577	45	22	to	to	ADP
esrj-65577	45	23	the	the	DET
esrj-65577	45	24	historical	historical	ADJ
esrj-65577	45	25	available	available	ADJ
esrj-65577	45	26	information	information	NOUN
esrj-65577	45	27	:	:	PUNCT
esrj-65577	45	28	it	it	PRON
esrj-65577	45	29	is	be	AUX
esrj-65577	45	30	assumed	assume	VERB
esrj-65577	45	31	that	that	SCONJ
esrj-65577	45	32	the	the	DET
esrj-65577	45	33	data	datum	NOUN
esrj-65577	45	34	is	be	AUX
esrj-65577	45	35	generated	generate	VERB
esrj-65577	45	36	from	from	ADP
esrj-65577	45	37	a	a	DET
esrj-65577	45	38	normal	normal	ADJ
esrj-65577	45	39	,	,	PUNCT
esrj-65577	45	40	a	a	DET
esrj-65577	45	41	gamma	gamma	NOUN
esrj-65577	45	42	or	or	CCONJ
esrj-65577	45	43	a	a	DET
esrj-65577	45	44	beta	beta	ADJ
esrj-65577	45	45	distribution	distribution	NOUN
esrj-65577	45	46	,	,	PUNCT
esrj-65577	45	47	with	with	ADP
esrj-65577	45	48	conditional	conditional	ADJ
esrj-65577	45	49	mean	mean	NOUN
esrj-65577	45	50	and	and	CCONJ
esrj-65577	45	51	variance	variance	NOUN
esrj-65577	45	52	,	,	PUNCT
esrj-65577	45	53	given	give	VERB
esrj-65577	45	54	respectively	respectively	ADV
esrj-65577	45	55	,	,	PUNCT
esrj-65577	45	56	by	by	ADP
esrj-65577	45	57	e	e	PROPN
esrj-65577	46	1	[	[	X
esrj-65577	46	2	yt|yt-1	yt|yt-1	X
esrj-65577	46	3	]	]	X
esrj-65577	46	4	and	and	CCONJ
esrj-65577	46	5	v	v	X
esrj-65577	47	1	[	[	X
esrj-65577	47	2	yt|	yt|	NOUN
esrj-65577	47	3	yt-1	yt-1	NOUN
esrj-65577	47	4	]	]	PUNCT
esrj-65577	47	5	,	,	PUNCT
esrj-65577	47	6	where	where	SCONJ
esrj-65577	47	7	the	the	DET
esrj-65577	47	8	index	index	NOUN
esrj-65577	47	9	tis	tis	PROPN
esrj-65577	47	10	related	relate	VERB
esrj-65577	47	11	to	to	ADP
esrj-65577	47	12	time	time	NOUN
esrj-65577	47	13	.	.	PUNCT
esrj-65577	48	1	thus	thus	ADV
esrj-65577	48	2	a	a	DET
esrj-65577	48	3	general	general	ADJ
esrj-65577	48	4	model	model	NOUN
esrj-65577	48	5	is	be	AUX
esrj-65577	48	6	proposed	propose	VERB
esrj-65577	48	7	to	to	PART
esrj-65577	48	8	analyze	analyze	VERB
esrj-65577	48	9	hydrological	hydrological	ADJ
esrj-65577	48	10	or	or	CCONJ
esrj-65577	48	11	meteorological	meteorological	ADJ
esrj-65577	48	12	time	time	NOUN
esrj-65577	48	13	series	series	NOUN
esrj-65577	48	14	,	,	PUNCT
esrj-65577	48	15	assuming	assume	VERB
esrj-65577	48	16	that	that	SCONJ
esrj-65577	48	17	the	the	DET
esrj-65577	48	18	observations	observation	NOUN
esrj-65577	48	19	are	be	AUX
esrj-65577	48	20	generated	generate	VERB
esrj-65577	48	21	from	from	ADP
esrj-65577	48	22	a	a	DET
esrj-65577	48	23	continuous	continuous	ADJ
esrj-65577	48	24	biparametric	biparametric	ADJ
esrj-65577	48	25	exponential	exponential	ADJ
esrj-65577	48	26	family	family	NOUN
esrj-65577	48	27	of	of	ADP
esrj-65577	48	28	distributions	distribution	NOUN
esrj-65577	48	29	.	.	PUNCT
esrj-65577	49	1	as	as	ADP
esrj-65577	49	2	an	an	DET
esrj-65577	49	3	illustration	illustration	NOUN
esrj-65577	49	4	and	and	CCONJ
esrj-65577	49	5	motivation	motivation	NOUN
esrj-65577	49	6	for	for	ADP
esrj-65577	49	7	the	the	DET
esrj-65577	49	8	use	use	NOUN
esrj-65577	49	9	of	of	ADP
esrj-65577	49	10	the	the	DET
esrj-65577	49	11	proposed	propose	VERB
esrj-65577	49	12	models	model	NOUN
esrj-65577	49	13	,	,	PUNCT
esrj-65577	49	14	we	we	PRON
esrj-65577	49	15	first	first	ADV
esrj-65577	49	16	consider	consider	VERB
esrj-65577	49	17	as	as	ADP
esrj-65577	49	18	a	a	DET
esrj-65577	49	19	first	first	ADJ
esrj-65577	49	20	example	example	NOUN
esrj-65577	49	21	,	,	PUNCT
esrj-65577	49	22	a	a	DET
esrj-65577	49	23	data	data	NOUN
esrj-65577	49	24	set	set	VERB
esrj-65577	49	25	consisting	consist	VERB
esrj-65577	49	26	of	of	ADP
esrj-65577	49	27	the	the	DET
esrj-65577	49	28	time	time	NOUN
esrj-65577	49	29	series	series	NOUN
esrj-65577	49	30	of	of	ADP
esrj-65577	49	31	monthly	monthly	ADJ
esrj-65577	49	32	averages	average	NOUN
esrj-65577	49	33	of	of	ADP
esrj-65577	49	34	natural	natural	ADJ
esrj-65577	49	35	streamflows	streamflow	NOUN
esrj-65577	49	36	,	,	PUNCT
esrj-65577	49	37	measured	measure	VERB
esrj-65577	49	38	in	in	ADP
esrj-65577	49	39	the	the	DET
esrj-65577	49	40	year	year	NOUN
esrj-65577	49	41	period	period	NOUN
esrj-65577	49	42	ranging	range	VERB
esrj-65577	49	43	from	from	ADP
esrj-65577	49	44	1931	1931	NUM
esrj-65577	49	45	to	to	ADP
esrj-65577	49	46	2010	2010	NUM
esrj-65577	49	47	,	,	PUNCT
esrj-65577	49	48	in	in	ADP
esrj-65577	49	49	furnas	furnas	PROPN
esrj-65577	49	50	hydroelectric	hydroelectric	PROPN
esrj-65577	49	51	dam	dam	PROPN
esrj-65577	49	52	,	,	PUNCT
esrj-65577	49	53	located	locate	VERB
esrj-65577	49	54	in	in	ADP
esrj-65577	49	55	southeastern	southeastern	ADJ
esrj-65577	49	56	brazil	brazil	PROPN
esrj-65577	49	57	.	.	PUNCT
esrj-65577	50	1	this	this	DET
esrj-65577	50	2	time	time	NOUN
esrj-65577	50	3	series	series	NOUN
esrj-65577	50	4	is	be	AUX
esrj-65577	50	5	shown	show	VERB
esrj-65577	50	6	in	in	ADP
esrj-65577	50	7	figure	figure	NOUN
esrj-65577	50	8	1	1	NUM
esrj-65577	50	9	.	.	PUNCT
esrj-65577	50	10	from	from	ADP
esrj-65577	50	11	this	this	DET
esrj-65577	50	12	figure	figure	NOUN
esrj-65577	50	13	,	,	PUNCT
esrj-65577	50	14	we	we	PRON
esrj-65577	50	15	observe	observe	VERB
esrj-65577	50	16	that	that	SCONJ
esrj-65577	50	17	the	the	DET
esrj-65577	50	18	streamflow	streamflow	PROPN
esrj-65577	50	19	series	series	PROPN
esrj-65577	50	20	have	have	VERB
esrj-65577	50	21	a	a	DET
esrj-65577	50	22	periodic	periodic	ADJ
esrj-65577	50	23	behavior	behavior	NOUN
esrj-65577	50	24	in	in	ADP
esrj-65577	50	25	the	the	DET
esrj-65577	50	26	mean	mean	NOUN
esrj-65577	50	27	and	and	CCONJ
esrj-65577	50	28	variance	variance	NOUN
esrj-65577	50	29	and	and	CCONJ
esrj-65577	50	30	in	in	ADP
esrj-65577	50	31	this	this	DET
esrj-65577	50	32	case	case	NOUN
esrj-65577	50	33	,	,	PUNCT
esrj-65577	50	34	general	general	ADJ
esrj-65577	50	35	periodic	periodic	ADJ
esrj-65577	50	36	autoregressive	autoregressive	ADJ
esrj-65577	50	37	models	model	NOUN
esrj-65577	50	38	are	be	AUX
esrj-65577	50	39	usually	usually	ADV
esrj-65577	50	40	assumed	assume	VERB
esrj-65577	50	41	in	in	ADP
esrj-65577	50	42	the	the	DET
esrj-65577	50	43	analysis	analysis	NOUN
esrj-65577	50	44	of	of	ADP
esrj-65577	50	45	the	the	DET
esrj-65577	50	46	time	time	NOUN
esrj-65577	50	47	series	series	PROPN
esrj-65577	50	48	data	data	PROPN
esrj-65577	50	49	(	(	PUNCT
esrj-65577	50	50	modal	modal	NOUN
esrj-65577	50	51	&	&	CCONJ
esrj-65577	50	52	wasimi	wasimi	NOUN
esrj-65577	50	53	,	,	PUNCT
esrj-65577	50	54	2006	2006	NUM
esrj-65577	50	55	)	)	PUNCT
esrj-65577	50	56	.	.	PUNCT
esrj-65577	51	1	to	to	PART
esrj-65577	51	2	take	take	VERB
esrj-65577	51	3	into	into	ADP
esrj-65577	51	4	account	account	NOUN
esrj-65577	51	5	the	the	DET
esrj-65577	51	6	heteroscedasticity	heteroscedasticity	NOUN
esrj-65577	51	7	in	in	ADP
esrj-65577	51	8	the	the	DET
esrj-65577	51	9	time	time	NOUN
esrj-65577	51	10	series	series	NOUN
esrj-65577	51	11	of	of	ADP
esrj-65577	51	12	streamflows	streamflow	NOUN
esrj-65577	51	13	showed	show	VERB
esrj-65577	51	14	in	in	ADP
esrj-65577	51	15	this	this	DET
esrj-65577	51	16	first	first	ADJ
esrj-65577	51	17	example	example	NOUN
esrj-65577	51	18	,	,	PUNCT
esrj-65577	51	19	we	we	PRON
esrj-65577	51	20	propose	propose	VERB
esrj-65577	51	21	a	a	DET
esrj-65577	51	22	new	new	ADJ
esrj-65577	51	23	model	model	NOUN
esrj-65577	51	24	which	which	PRON
esrj-65577	51	25	assumes	assume	VERB
esrj-65577	51	26	seasonal	seasonal	ADJ
esrj-65577	51	27	and	and	CCONJ
esrj-65577	51	28	autoregressive	autoregressive	ADJ
esrj-65577	51	29	terms	term	NOUN
esrj-65577	51	30	in	in	ADP
esrj-65577	51	31	the	the	DET
esrj-65577	51	32	modeling	modeling	NOUN
esrj-65577	51	33	of	of	ADP
esrj-65577	51	34	the	the	DET
esrj-65577	51	35	mean	mean	ADJ
esrj-65577	51	36	and	and	CCONJ
esrj-65577	51	37	variance	variance	NOUN
esrj-65577	51	38	parameters	parameter	NOUN
esrj-65577	51	39	.	.	PUNCT
esrj-65577	52	1	in	in	ADP
esrj-65577	52	2	this	this	DET
esrj-65577	52	3	way	way	NOUN
esrj-65577	52	4	,	,	PUNCT
esrj-65577	52	5	we	we	PRON
esrj-65577	52	6	propose	propose	VERB
esrj-65577	52	7	a	a	DET
esrj-65577	52	8	periodic	periodic	ADJ
esrj-65577	52	9	and	and	CCONJ
esrj-65577	52	10	heteroscedastic	heteroscedastic	ADJ
esrj-65577	52	11	model	model	NOUN
esrj-65577	52	12	,	,	PUNCT
esrj-65577	52	13	in	in	ADP
esrj-65577	52	14	which	which	PRON
esrj-65577	52	15	the	the	DET
esrj-65577	52	16	variance	variance	NOUN
esrj-65577	52	17	also	also	ADV
esrj-65577	52	18	presents	present	VERB
esrj-65577	52	19	an	an	DET
esrj-65577	52	20	autoregressive	autoregressive	ADJ
esrj-65577	52	21	structure	structure	NOUN
esrj-65577	52	22	.	.	PUNCT
esrj-65577	53	1	as	as	ADP
esrj-65577	53	2	a	a	DET
esrj-65577	53	3	second	second	ADJ
esrj-65577	53	4	example	example	NOUN
esrj-65577	53	5	,	,	PUNCT
esrj-65577	53	6	we	we	PRON
esrj-65577	53	7	consider	consider	VERB
esrj-65577	53	8	another	another	DET
esrj-65577	53	9	time	time	NOUN
esrj-65577	53	10	series	series	NOUN
esrj-65577	53	11	with	with	ADP
esrj-65577	53	12	behavior	behavior	NOUN
esrj-65577	53	13	similar	similar	ADJ
esrj-65577	53	14	to	to	ADP
esrj-65577	53	15	the	the	DET
esrj-65577	53	16	assumed	assumed	ADJ
esrj-65577	53	17	hydrological	hydrological	ADJ
esrj-65577	53	18	time	time	NOUN
esrj-65577	53	19	series	series	PROPN
esrj-65577	53	20	presented	present	VERB
esrj-65577	53	21	in	in	ADP
esrj-65577	53	22	the	the	DET
esrj-65577	53	23	first	first	ADJ
esrj-65577	53	24	example	example	NOUN
esrj-65577	53	25	,	,	PUNCT
esrj-65577	53	26	consisting	consist	VERB
esrj-65577	53	27	of	of	ADP
esrj-65577	53	28	a	a	DET
esrj-65577	53	29	meteorological	meteorological	ADJ
esrj-65577	53	30	time	time	NOUN
esrj-65577	53	31	series	series	NOUN
esrj-65577	53	32	given	give	VERB
esrj-65577	53	33	by	by	ADP
esrj-65577	53	34	weekly	weekly	ADJ
esrj-65577	53	35	averages	average	NOUN
esrj-65577	53	36	of	of	ADP
esrj-65577	53	37	air	air	NOUN
esrj-65577	53	38	humidity	humidity	NOUN
esrj-65577	53	39	,	,	PUNCT
esrj-65577	53	40	measured	measure	VERB
esrj-65577	53	41	in	in	ADP
esrj-65577	53	42	the	the	DET
esrj-65577	53	43	city	city	NOUN
esrj-65577	53	44	of	of	ADP
esrj-65577	53	45	rio	rio	PROPN
esrj-65577	53	46	claro	claro	PROPN
esrj-65577	53	47	,	,	PUNCT
esrj-65577	53	48	são	são	PROPN
esrj-65577	53	49	paulo	paulo	PROPN
esrj-65577	53	50	state	state	PROPN
esrj-65577	53	51	,	,	PUNCT
esrj-65577	53	52	brazil	brazil	PROPN
esrj-65577	53	53	(	(	PUNCT
esrj-65577	53	54	figure	figure	NOUN
esrj-65577	53	55	2	2	NUM
esrj-65577	53	56	)	)	PUNCT
esrj-65577	53	57	.	.	PUNCT
esrj-65577	54	1	in	in	ADP
esrj-65577	54	2	this	this	DET
esrj-65577	54	3	case	case	NOUN
esrj-65577	54	4	,	,	PUNCT
esrj-65577	54	5	given	give	VERB
esrj-65577	54	6	that	that	SCONJ
esrj-65577	54	7	the	the	DET
esrj-65577	54	8	relative	relative	ADJ
esrj-65577	54	9	air	air	NOUN
esrj-65577	54	10	humidity	humidity	NOUN
esrj-65577	54	11	is	be	AUX
esrj-65577	54	12	a	a	DET
esrj-65577	54	13	random	random	ADJ
esrj-65577	54	14	variable	variable	NOUN
esrj-65577	54	15	with	with	ADP
esrj-65577	54	16	values	value	NOUN
esrj-65577	54	17	in	in	ADP
esrj-65577	54	18	the	the	DET
esrj-65577	54	19	open	open	ADJ
esrj-65577	54	20	interval	interval	NOUN
esrj-65577	54	21	(	(	PUNCT
esrj-65577	54	22	0	0	NUM
esrj-65577	54	23	,	,	PUNCT
esrj-65577	54	24	1	1	NUM
esrj-65577	54	25	)	)	PUNCT
esrj-65577	54	26	,	,	PUNCT
esrj-65577	54	27	it	it	PRON
esrj-65577	54	28	is	be	AUX
esrj-65577	54	29	assumed	assume	VERB
esrj-65577	54	30	a	a	DET
esrj-65577	54	31	beta	beta	ADJ
esrj-65577	54	32	distribution	distribution	NOUN
esrj-65577	54	33	in	in	ADP
esrj-65577	54	34	the	the	DET
esrj-65577	54	35	analysis	analysis	NOUN
esrj-65577	54	36	of	of	ADP
esrj-65577	54	37	the	the	DET
esrj-65577	54	38	data	datum	NOUN
esrj-65577	54	39	.	.	PUNCT
esrj-65577	55	1	in	in	ADP
esrj-65577	55	2	this	this	DET
esrj-65577	55	3	case	case	NOUN
esrj-65577	55	4	,	,	PUNCT
esrj-65577	55	5	we	we	PRON
esrj-65577	55	6	propose	propose	VERB
esrj-65577	55	7	a	a	DET
esrj-65577	55	8	jointly	jointly	ADV
esrj-65577	55	9	modeling	modeling	NOUN
esrj-65577	55	10	for	for	ADP
esrj-65577	55	11	the	the	DET
esrj-65577	55	12	mean	mean	NOUN
esrj-65577	55	13	and	and	CCONJ
esrj-65577	55	14	for	for	ADP
esrj-65577	55	15	the	the	DET
esrj-65577	55	16	variance	variance	NOUN
esrj-65577	55	17	of	of	ADP
esrj-65577	55	18	the	the	DET
esrj-65577	55	19	data	datum	NOUN
esrj-65577	55	20	considering	consider	VERB
esrj-65577	55	21	beta	beta	ADJ
esrj-65577	55	22	regression	regression	NOUN
esrj-65577	55	23	models	model	NOUN
esrj-65577	55	24	,	,	PUNCT
esrj-65577	55	25	including	include	VERB
esrj-65577	55	26	seasonal	seasonal	ADJ
esrj-65577	55	27	and	and	CCONJ
esrj-65577	55	28	autoregressive	autoregressive	ADJ
esrj-65577	55	29	terms	term	NOUN
esrj-65577	55	30	in	in	ADP
esrj-65577	55	31	both	both	DET
esrj-65577	55	32	regression	regression	NOUN
esrj-65577	55	33	models	model	NOUN
esrj-65577	55	34	figure	figure	VERB
esrj-65577	55	35	1	1	NUM
esrj-65577	55	36	.	.	NOUN
esrj-65577	55	37	time	time	NOUN
esrj-65577	55	38	series	series	NOUN
esrj-65577	55	39	of	of	ADP
esrj-65577	55	40	monthly	monthly	ADJ
esrj-65577	55	41	averages	average	NOUN
esrj-65577	55	42	of	of	ADP
esrj-65577	55	43	natural	natural	ADJ
esrj-65577	55	44	streamflows	streamflow	NOUN
esrj-65577	55	45	.	.	PUNCT
esrj-65577	56	1	figure	figure	NOUN
esrj-65577	56	2	2	2	NUM
esrj-65577	56	3	.	.	NOUN
esrj-65577	56	4	air	air	PROPN
esrj-65577	56	5	humidity	humidity	PROPN
esrj-65577	56	6	time	time	PROPN
esrj-65577	56	7	series	series	PROPN
esrj-65577	56	8	data	data	PROPN
esrj-65577	56	9	.	.	PUNCT
esrj-65577	57	1	the	the	DET
esrj-65577	57	2	paper	paper	NOUN
esrj-65577	57	3	is	be	AUX
esrj-65577	57	4	structured	structure	VERB
esrj-65577	57	5	as	as	SCONJ
esrj-65577	57	6	follows	follow	VERB
esrj-65577	57	7	:	:	PUNCT
esrj-65577	57	8	in	in	ADP
esrj-65577	57	9	section	section	NOUN
esrj-65577	57	10	2	2	NUM
esrj-65577	57	11	,	,	PUNCT
esrj-65577	57	12	it	it	PRON
esrj-65577	57	13	is	be	AUX
esrj-65577	57	14	introduced	introduce	VERB
esrj-65577	57	15	the	the	DET
esrj-65577	57	16	seasonality	seasonality	NOUN
esrj-65577	57	17	analysis	analysis	NOUN
esrj-65577	57	18	of	of	ADP
esrj-65577	57	19	the	the	DET
esrj-65577	57	20	time	time	NOUN
esrj-65577	57	21	series	series	NOUN
esrj-65577	57	22	.	.	PUNCT
esrj-65577	58	1	in	in	ADP
esrj-65577	58	2	section	section	NOUN
esrj-65577	58	3	3	3	NUM
esrj-65577	58	4	,	,	PUNCT
esrj-65577	58	5	it	it	PRON
esrj-65577	58	6	is	be	AUX
esrj-65577	58	7	proposed	propose	VERB
esrj-65577	58	8	seasonal	seasonal	ADJ
esrj-65577	58	9	autoregressive	autoregressive	ADJ
esrj-65577	58	10	models	model	NOUN
esrj-65577	58	11	.	.	PUNCT
esrj-65577	59	1	in	in	ADP
esrj-65577	59	2	section	section	NOUN
esrj-65577	59	3	4	4	NUM
esrj-65577	59	4	,	,	PUNCT
esrj-65577	59	5	it	it	PRON
esrj-65577	59	6	is	be	AUX
esrj-65577	59	7	presented	present	VERB
esrj-65577	59	8	the	the	DET
esrj-65577	59	9	results	result	NOUN
esrj-65577	59	10	of	of	ADP
esrj-65577	59	11	the	the	DET
esrj-65577	59	12	analysis	analysis	NOUN
esrj-65577	59	13	of	of	ADP
esrj-65577	59	14	the	the	DET
esrj-65577	59	15	hydrological	hydrological	ADJ
esrj-65577	59	16	time	time	NOUN
esrj-65577	59	17	series	series	PROPN
esrj-65577	59	18	obtained	obtain	VERB
esrj-65577	59	19	using	use	VERB
esrj-65577	59	20	the	the	DET
esrj-65577	59	21	proposed	propose	VERB
esrj-65577	59	22	models	model	NOUN
esrj-65577	59	23	assuming	assume	VERB
esrj-65577	59	24	normal	normal	ADJ
esrj-65577	59	25	and	and	CCONJ
esrj-65577	59	26	gamma	gamma	NOUN
esrj-65577	59	27	distributions	distribution	NOUN
esrj-65577	59	28	.	.	PUNCT
esrj-65577	60	1	in	in	ADP
esrj-65577	60	2	section	section	NOUN
esrj-65577	60	3	5	5	NUM
esrj-65577	60	4	,	,	PUNCT
esrj-65577	60	5	it	it	PRON
esrj-65577	60	6	is	be	AUX
esrj-65577	60	7	presented	present	VERB
esrj-65577	60	8	the	the	DET
esrj-65577	60	9	results	result	NOUN
esrj-65577	60	10	of	of	ADP
esrj-65577	60	11	the	the	DET
esrj-65577	60	12	analysis	analysis	NOUN
esrj-65577	60	13	of	of	ADP
esrj-65577	60	14	air	air	NOUN
esrj-65577	60	15	humidity	humidity	NOUN
esrj-65577	60	16	time	time	NOUN
esrj-65577	60	17	series	series	PROPN
esrj-65577	60	18	.	.	PUNCT
esrj-65577	61	1	finally	finally	ADV
esrj-65577	61	2	,	,	PUNCT
esrj-65577	61	3	in	in	ADP
esrj-65577	61	4	section	section	NOUN
esrj-65577	61	5	6	6	NUM
esrj-65577	61	6	it	it	PRON
esrj-65577	61	7	is	be	AUX
esrj-65577	61	8	presented	present	VERB
esrj-65577	61	9	some	some	DET
esrj-65577	61	10	conclusions	conclusion	NOUN
esrj-65577	61	11	and	and	CCONJ
esrj-65577	61	12	future	future	ADJ
esrj-65577	61	13	research	research	NOUN
esrj-65577	61	14	topics	topic	NOUN
esrj-65577	61	15	.	.	PUNCT
esrj-65577	62	1	85seasonal	85seasonal	ADJ
esrj-65577	62	2	hydrological	hydrological	ADJ
esrj-65577	62	3	and	and	CCONJ
esrj-65577	62	4	meteorological	meteorological	ADJ
esrj-65577	62	5	time	time	NOUN
esrj-65577	62	6	series	series	NOUN
esrj-65577	62	7	(	(	PUNCT
esrj-65577	62	8	1	1	NUM
esrj-65577	62	9	)	)	PUNCT
esrj-65577	62	10	(	(	PUNCT
esrj-65577	62	11	2	2	NUM
esrj-65577	62	12	)	)	PUNCT
esrj-65577	62	13	(	(	PUNCT
esrj-65577	62	14	6	6	NUM
esrj-65577	62	15	)	)	PUNCT
esrj-65577	62	16	(	(	PUNCT
esrj-65577	62	17	7	7	NUM
esrj-65577	62	18	)	)	PUNCT
esrj-65577	62	19	(	(	PUNCT
esrj-65577	62	20	3	3	X
esrj-65577	62	21	)	)	PUNCT
esrj-65577	62	22	(	(	PUNCT
esrj-65577	62	23	4	4	NUM
esrj-65577	62	24	)	)	PUNCT
esrj-65577	62	25	(	(	PUNCT
esrj-65577	62	26	5	5	NUM
esrj-65577	62	27	)	)	PUNCT
esrj-65577	62	28	2	2	NUM
esrj-65577	62	29	.	.	X
esrj-65577	62	30	a	a	DET
esrj-65577	62	31	period	period	NOUN
esrj-65577	62	32	model	model	NOUN
esrj-65577	62	33	in	in	ADP
esrj-65577	62	34	this	this	DET
esrj-65577	62	35	section	section	NOUN
esrj-65577	62	36	,	,	PUNCT
esrj-65577	62	37	we	we	PRON
esrj-65577	62	38	introduce	introduce	VERB
esrj-65577	62	39	a	a	DET
esrj-65577	62	40	new	new	ADJ
esrj-65577	62	41	modeling	modeling	NOUN
esrj-65577	62	42	approach	approach	NOUN
esrj-65577	62	43	including	include	VERB
esrj-65577	62	44	seasonality	seasonality	NOUN
esrj-65577	62	45	terms	term	NOUN
esrj-65577	62	46	in	in	ADP
esrj-65577	62	47	the	the	DET
esrj-65577	62	48	model	model	NOUN
esrj-65577	62	49	which	which	PRON
esrj-65577	62	50	better	well	ADV
esrj-65577	62	51	describes	describe	VERB
esrj-65577	62	52	time	time	NOUN
esrj-65577	62	53	series	series	NOUN
esrj-65577	62	54	of	of	ADP
esrj-65577	62	55	monthly	monthly	ADJ
esrj-65577	62	56	averages	average	NOUN
esrj-65577	62	57	of	of	ADP
esrj-65577	62	58	natural	natural	ADJ
esrj-65577	62	59	stream	stream	NOUN
esrj-65577	62	60	flows	flow	NOUN
esrj-65577	62	61	,	,	PUNCT
esrj-65577	62	62	denoted	denote	VERB
esrj-65577	62	63	by	by	ADP
esrj-65577	62	64	yt	yt	NOUN
esrj-65577	62	65	.	.	PUNCT
esrj-65577	63	1	in	in	ADP
esrj-65577	63	2	the	the	DET
esrj-65577	63	3	first	first	ADJ
esrj-65577	63	4	case	case	NOUN
esrj-65577	63	5	,	,	PUNCT
esrj-65577	63	6	we	we	PRON
esrj-65577	63	7	consider	consider	VERB
esrj-65577	63	8	the	the	DET
esrj-65577	63	9	time	time	NOUN
esrj-65577	63	10	series	series	PROPN
esrj-65577	63	11	data	datum	NOUN
esrj-65577	63	12	related	relate	VERB
esrj-65577	63	13	to	to	ADP
esrj-65577	63	14	the	the	DET
esrj-65577	63	15	monthly	monthly	ADJ
esrj-65577	63	16	averages	average	NOUN
esrj-65577	63	17	of	of	ADP
esrj-65577	63	18	natural	natural	ADJ
esrj-65577	63	19	streamflows	streamflow	NOUN
esrj-65577	63	20	in	in	ADP
esrj-65577	63	21	furnas	furnas	PROPN
esrj-65577	63	22	hydroelectric	hydroelectric	PROPN
esrj-65577	63	23	dam	dam	NOUN
esrj-65577	63	24	(	(	PUNCT
esrj-65577	63	25	figure	figure	NOUN
esrj-65577	63	26	1	1	NUM
esrj-65577	63	27	)	)	PUNCT
esrj-65577	63	28	.	.	PUNCT
esrj-65577	64	1	a	a	DET
esrj-65577	64	2	preliminary	preliminary	ADJ
esrj-65577	64	3	spectral	spectral	ADJ
esrj-65577	64	4	analysis	analysis	NOUN
esrj-65577	64	5	is	be	AUX
esrj-65577	64	6	developed	develop	VERB
esrj-65577	64	7	for	for	ADP
esrj-65577	64	8	this	this	DET
esrj-65577	64	9	time	time	NOUN
esrj-65577	64	10	series	series	NOUN
esrj-65577	64	11	to	to	PART
esrj-65577	64	12	determine	determine	VERB
esrj-65577	64	13	the	the	DET
esrj-65577	64	14	time	time	NOUN
esrj-65577	64	15	periods	period	NOUN
esrj-65577	64	16	to	to	PART
esrj-65577	64	17	be	be	AUX
esrj-65577	64	18	considered	consider	VERB
esrj-65577	64	19	in	in	ADP
esrj-65577	64	20	the	the	DET
esrj-65577	64	21	mean	mean	ADJ
esrj-65577	64	22	and	and	CCONJ
esrj-65577	64	23	variance	variance	NOUN
esrj-65577	64	24	model	model	NOUN
esrj-65577	64	25	formulations	formulation	NOUN
esrj-65577	64	26	.	.	PUNCT
esrj-65577	65	1	thus	thus	ADV
esrj-65577	65	2	,	,	PUNCT
esrj-65577	65	3	if	if	SCONJ
esrj-65577	65	4	in	in	ADP
esrj-65577	65	5	the	the	DET
esrj-65577	65	6	spectral	spectral	ADJ
esrj-65577	65	7	analysis	analysis	NOUN
esrj-65577	65	8	,	,	PUNCT
esrj-65577	65	9	the	the	DET
esrj-65577	65	10	number	number	NOUN
esrj-65577	65	11	of	of	ADP
esrj-65577	65	12	observations	observation	NOUN
esrj-65577	65	13	is	be	AUX
esrj-65577	65	14	t	t	NOUN
esrj-65577	65	15	=	=	SYM
esrj-65577	65	16	2q	2q	NOUN
esrj-65577	66	1	+	+	ADJ
esrj-65577	66	2	1	1	NUM
esrj-65577	66	3	,	,	PUNCT
esrj-65577	66	4	where	where	SCONJ
esrj-65577	66	5	q	q	NOUN
esrj-65577	66	6	is	be	AUX
esrj-65577	66	7	a	a	DET
esrj-65577	66	8	positive	positive	ADJ
esrj-65577	66	9	integer	integer	NOUN
esrj-65577	66	10	number	number	NOUN
esrj-65577	66	11	,	,	PUNCT
esrj-65577	66	12	the	the	DET
esrj-65577	66	13	fourier	fourier	ADJ
esrj-65577	66	14	time	time	NOUN
esrj-65577	66	15	series	series	PROPN
esrj-65577	66	16	model	model	NOUN
esrj-65577	66	17	given	give	VERB
esrj-65577	66	18	by	by	ADP
esrj-65577	66	19	:	:	PUNCT
esrj-65577	66	20	is	be	AUX
esrj-65577	66	21	to	to	PART
esrj-65577	66	22	be	be	AUX
esrj-65577	66	23	fitted	fit	VERB
esrj-65577	66	24	by	by	ADP
esrj-65577	66	25	the	the	DET
esrj-65577	66	26	data	datum	NOUN
esrj-65577	66	27	,	,	PUNCT
esrj-65577	66	28	where	where	SCONJ
esrj-65577	66	29	fi	fi	NOUN
esrj-65577	66	30	=	=	NOUN
esrj-65577	66	31	i	i	PROPN
esrj-65577	66	32	/	/	SYM
esrj-65577	66	33	t	t	PROPN
esrj-65577	66	34	is	be	AUX
esrj-65577	66	35	the	the	DET
esrj-65577	66	36	ith	ith	PROPN
esrj-65577	66	37	harmonic	harmonic	NOUN
esrj-65577	66	38	of	of	ADP
esrj-65577	66	39	the	the	DET
esrj-65577	66	40	fundamental	fundamental	ADJ
esrj-65577	66	41	frequency	frequency	NOUN
esrj-65577	66	42	1	1	NUM
esrj-65577	66	43	/	/	SYM
esrj-65577	66	44	t	t	PROPN
esrj-65577	66	45	and	and	CCONJ
esrj-65577	66	46	,	,	PUNCT
esrj-65577	66	47	α1,i	α1,i	PROPN
esrj-65577	66	48	and	and	CCONJ
esrj-65577	66	49	α2,i	α2,i	PROPN
esrj-65577	66	50	,	,	PUNCT
esrj-65577	66	51	i	i	PRON
esrj-65577	66	52	=	=	NOUN
esrj-65577	66	53	1,	1,	NUM
esrj-65577	66	54	...	...	PUNCT
esrj-65577	66	55	,q	,q	PUNCT
esrj-65577	66	56	,	,	PUNCT
esrj-65577	66	57	are	be	AUX
esrj-65577	66	58	the	the	DET
esrj-65577	66	59	related	related	ADJ
esrj-65577	66	60	coefficients	coefficient	NOUN
esrj-65577	66	61	and	and	CCONJ
esrj-65577	66	62	et	et	NOUN
esrj-65577	66	63	is	be	AUX
esrj-65577	66	64	an	an	DET
esrj-65577	66	65	error	error	NOUN
esrj-65577	66	66	term	term	NOUN
esrj-65577	66	67	assumed	assume	VERB
esrj-65577	66	68	to	to	PART
esrj-65577	66	69	have	have	VERB
esrj-65577	66	70	the	the	DET
esrj-65577	66	71	first	first	ADJ
esrj-65577	66	72	and	and	CCONJ
esrj-65577	66	73	second	second	ADJ
esrj-65577	66	74	moments	moment	NOUN
esrj-65577	66	75	given	give	VERB
esrj-65577	66	76	respectively	respectively	ADV
esrj-65577	66	77	by	by	ADP
esrj-65577	66	78	e(et	e(et	NOUN
esrj-65577	66	79	)	)	PUNCT
esrj-65577	66	80	=	=	SYM
esrj-65577	66	81	0	0	NUM
esrj-65577	66	82	,	,	PUNCT
esrj-65577	66	83	e	e	X
esrj-65577	66	84	(	(	PUNCT
esrj-65577	66	85	et	et	NOUN
esrj-65577	66	86	2	2	NUM
esrj-65577	66	87	)	)	PUNCT
esrj-65577	66	88	=	=	SYM
esrj-65577	66	89	σ2	σ2	NOUN
esrj-65577	66	90	and	and	CCONJ
esrj-65577	66	91	to	to	PART
esrj-65577	66	92	be	be	AUX
esrj-65577	66	93	uncorrelated	uncorrelate	VERB
esrj-65577	66	94	,	,	PUNCT
esrj-65577	66	95	that	that	ADV
esrj-65577	66	96	is	is	ADV
esrj-65577	66	97	,	,	PUNCT
esrj-65577	66	98	e(et	e(et	PROPN
esrj-65577	66	99	et+k	et+k	PROPN
esrj-65577	66	100	)	)	PUNCT
esrj-65577	66	101	=	=	SYM
esrj-65577	66	102	0	0	NUM
esrj-65577	66	103	for	for	ADP
esrj-65577	66	104	k	k	PROPN
esrj-65577	66	105	≠	≠	PROPN
esrj-65577	66	106	0	0	NUM
esrj-65577	66	107	.	.	PUNCT
esrj-65577	67	1	considering	consider	VERB
esrj-65577	67	2	the	the	DET
esrj-65577	67	3	n	n	PRON
esrj-65577	67	4	observations	observation	NOUN
esrj-65577	67	5	of	of	ADP
esrj-65577	67	6	the	the	DET
esrj-65577	67	7	time	time	NOUN
esrj-65577	67	8	series	series	NOUN
esrj-65577	67	9	,	,	PUNCT
esrj-65577	67	10	the	the	DET
esrj-65577	67	11	least	least	ADJ
esrj-65577	67	12	square	square	ADJ
esrj-65577	67	13	estimates	estimate	NOUN
esrj-65577	67	14	of	of	ADP
esrj-65577	67	15	the	the	DET
esrj-65577	67	16	coefficients	coefficient	NOUN
esrj-65577	67	17	α0	α0	ADJ
esrj-65577	67	18	and	and	CCONJ
esrj-65577	67	19	(	(	PUNCT
esrj-65577	67	20	α1,i	α1,i	PROPN
esrj-65577	67	21	,	,	PUNCT
esrj-65577	67	22	α2,i	α2,i	PROPN
esrj-65577	67	23	)	)	PUNCT
esrj-65577	67	24	,	,	PUNCT
esrj-65577	67	25	i	i	PRON
esrj-65577	67	26	=	=	NOUN
esrj-65577	67	27	1,	1,	NUM
esrj-65577	67	28	...	...	PUNCT
esrj-65577	67	29	q	q	NOUN
esrj-65577	67	30	,	,	PUNCT
esrj-65577	67	31	are	be	AUX
esrj-65577	67	32	obtained	obtain	VERB
esrj-65577	67	33	from	from	ADP
esrj-65577	67	34	the	the	DET
esrj-65577	67	35	equations	equation	NOUN
esrj-65577	67	36	:	:	PUNCT
esrj-65577	67	37	based	base	VERB
esrj-65577	67	38	on	on	ADP
esrj-65577	67	39	these	these	DET
esrj-65577	67	40	estimates	estimate	NOUN
esrj-65577	67	41	,	,	PUNCT
esrj-65577	67	42	the	the	DET
esrj-65577	67	43	intensity	intensity	NOUN
esrj-65577	67	44	of	of	ADP
esrj-65577	67	45	each	each	DET
esrj-65577	67	46	frequency	frequency	NOUN
esrj-65577	67	47	is	be	AUX
esrj-65577	67	48	calculated	calculate	VERB
esrj-65577	67	49	by	by	ADP
esrj-65577	67	50	:	:	PUNCT
esrj-65577	67	51	observe	observe	VERB
esrj-65577	67	52	that	that	SCONJ
esrj-65577	67	53	the	the	DET
esrj-65577	67	54	highest	high	ADJ
esrj-65577	67	55	frequency	frequency	NOUN
esrj-65577	67	56	is	be	AUX
esrj-65577	67	57	0.5	0.5	NUM
esrj-65577	67	58	cycle	cycle	NOUN
esrj-65577	67	59	per	per	ADP
esrj-65577	67	60	month	month	NOUN
esrj-65577	67	61	(	(	PUNCT
esrj-65577	67	62	time	time	NOUN
esrj-65577	67	63	interval	interval	NOUN
esrj-65577	67	64	)	)	PUNCT
esrj-65577	67	65	since	since	SCONJ
esrj-65577	67	66	the	the	DET
esrj-65577	67	67	smallest	small	ADJ
esrj-65577	67	68	period	period	NOUN
esrj-65577	67	69	is	be	AUX
esrj-65577	67	70	2	2	NUM
esrj-65577	67	71	months	month	NOUN
esrj-65577	67	72	.	.	PUNCT
esrj-65577	68	1	this	this	DET
esrj-65577	68	2	preliminary	preliminary	ADJ
esrj-65577	68	3	analysis	analysis	NOUN
esrj-65577	68	4	of	of	ADP
esrj-65577	68	5	the	the	DET
esrj-65577	68	6	intensities	intensity	NOUN
esrj-65577	68	7	of	of	ADP
esrj-65577	68	8	frequencies	frequency	NOUN
esrj-65577	68	9	allows	allow	VERB
esrj-65577	68	10	us	we	PRON
esrj-65577	68	11	to	to	PART
esrj-65577	68	12	reduce	reduce	VERB
esrj-65577	68	13	the	the	DET
esrj-65577	68	14	number	number	NOUN
esrj-65577	68	15	of	of	ADP
esrj-65577	68	16	harmonics	harmonic	NOUN
esrj-65577	68	17	considered	consider	VERB
esrj-65577	68	18	in	in	ADP
esrj-65577	68	19	the	the	DET
esrj-65577	68	20	time	time	NOUN
esrj-65577	68	21	series	series	PROPN
esrj-65577	68	22	included	include	VERB
esrj-65577	68	23	in	in	ADP
esrj-65577	68	24	the	the	DET
esrj-65577	68	25	model	model	NOUN
esrj-65577	68	26	,	,	PUNCT
esrj-65577	68	27	considering	consider	VERB
esrj-65577	68	28	only	only	ADV
esrj-65577	68	29	those	those	DET
esrj-65577	68	30	frequencies	frequency	NOUN
esrj-65577	68	31	that	that	PRON
esrj-65577	68	32	have	have	VERB
esrj-65577	68	33	higher	high	ADJ
esrj-65577	68	34	intensities	intensity	NOUN
esrj-65577	68	35	(	(	PUNCT
esrj-65577	68	36	marques	marques	X
esrj-65577	68	37	et	et	PROPN
esrj-65577	68	38	al	al	PROPN
esrj-65577	68	39	.	.	PROPN
esrj-65577	68	40	,	,	PUNCT
esrj-65577	68	41	2006	2006	NUM
esrj-65577	68	42	)	)	PUNCT
esrj-65577	68	43	.	.	PUNCT
esrj-65577	69	1	for	for	ADP
esrj-65577	69	2	a	a	DET
esrj-65577	69	3	series	series	NOUN
esrj-65577	69	4	consisting	consist	VERB
esrj-65577	69	5	of	of	ADP
esrj-65577	69	6	80	80	NUM
esrj-65577	69	7	years	year	NOUN
esrj-65577	69	8	of	of	ADP
esrj-65577	69	9	observations	observation	NOUN
esrj-65577	69	10	(	(	PUNCT
esrj-65577	69	11	that	that	PRON
esrj-65577	69	12	is	be	AUX
esrj-65577	69	13	960	960	NUM
esrj-65577	69	14	months	month	NOUN
esrj-65577	69	15	)	)	PUNCT
esrj-65577	70	1	we	we	PRON
esrj-65577	70	2	would	would	AUX
esrj-65577	70	3	have	have	VERB
esrj-65577	70	4	480	480	NUM
esrj-65577	70	5	harmonics	harmonic	NOUN
esrj-65577	70	6	,	,	PUNCT
esrj-65577	70	7	but	but	CCONJ
esrj-65577	70	8	considering	consider	VERB
esrj-65577	70	9	this	this	DET
esrj-65577	70	10	preliminary	preliminary	ADJ
esrj-65577	70	11	analysis	analysis	NOUN
esrj-65577	70	12	,	,	PUNCT
esrj-65577	70	13	we	we	PRON
esrj-65577	70	14	could	could	AUX
esrj-65577	70	15	reduce	reduce	VERB
esrj-65577	70	16	the	the	DET
esrj-65577	70	17	number	number	NOUN
esrj-65577	70	18	of	of	ADP
esrj-65577	70	19	harmonics	harmonic	NOUN
esrj-65577	70	20	to	to	ADP
esrj-65577	70	21	three	three	NUM
esrj-65577	70	22	or	or	CCONJ
esrj-65577	70	23	four	four	NUM
esrj-65577	70	24	.	.	PUNCT
esrj-65577	71	1	usually	usually	ADV
esrj-65577	71	2	,	,	PUNCT
esrj-65577	71	3	in	in	ADP
esrj-65577	71	4	the	the	DET
esrj-65577	71	5	case	case	NOUN
esrj-65577	71	6	of	of	ADP
esrj-65577	71	7	monthly	monthly	ADJ
esrj-65577	71	8	time	time	NOUN
esrj-65577	71	9	series	series	NOUN
esrj-65577	71	10	,	,	PUNCT
esrj-65577	71	11	these	these	DET
esrj-65577	71	12	periods	period	NOUN
esrj-65577	71	13	are	be	AUX
esrj-65577	71	14	given	give	VERB
esrj-65577	71	15	by	by	ADP
esrj-65577	71	16	periods	period	NOUN
esrj-65577	71	17	of	of	ADP
esrj-65577	71	18	6	6	NUM
esrj-65577	71	19	and	and	CCONJ
esrj-65577	71	20	12	12	NUM
esrj-65577	71	21	months	month	NOUN
esrj-65577	71	22	.	.	PUNCT
esrj-65577	72	1	these	these	DET
esrj-65577	72	2	periods	period	NOUN
esrj-65577	72	3	will	will	AUX
esrj-65577	72	4	be	be	AUX
esrj-65577	72	5	discussed	discuss	VERB
esrj-65577	72	6	in	in	ADP
esrj-65577	72	7	section	section	NOUN
esrj-65577	72	8	4	4	NUM
esrj-65577	72	9	,	,	PUNCT
esrj-65577	72	10	where	where	SCONJ
esrj-65577	72	11	the	the	DET
esrj-65577	72	12	specification	specification	NOUN
esrj-65577	72	13	of	of	ADP
esrj-65577	72	14	the	the	DET
esrj-65577	72	15	parameters	parameter	NOUN
esrj-65577	72	16	related	relate	VERB
esrj-65577	72	17	to	to	ADP
esrj-65577	72	18	the	the	DET
esrj-65577	72	19	periods	period	NOUN
esrj-65577	72	20	is	be	AUX
esrj-65577	72	21	made	make	VERB
esrj-65577	72	22	simultaneously	simultaneously	ADV
esrj-65577	72	23	with	with	ADP
esrj-65577	72	24	the	the	DET
esrj-65577	72	25	specification	specification	NOUN
esrj-65577	72	26	of	of	ADP
esrj-65577	72	27	the	the	DET
esrj-65577	72	28	parameters	parameter	NOUN
esrj-65577	72	29	for	for	ADP
esrj-65577	72	30	the	the	DET
esrj-65577	72	31	autoregressive	autoregressive	ADJ
esrj-65577	72	32	models	model	NOUN
esrj-65577	72	33	assumed	assume	VERB
esrj-65577	72	34	for	for	ADP
esrj-65577	72	35	the	the	DET
esrj-65577	72	36	mean	mean	NOUN
esrj-65577	72	37	and	and	CCONJ
esrj-65577	72	38	variance	variance	NOUN
esrj-65577	72	39	in	in	ADP
esrj-65577	72	40	the	the	DET
esrj-65577	72	41	time	time	NOUN
esrj-65577	72	42	series	series	PROPN
esrj-65577	72	43	formulations	formulation	NOUN
esrj-65577	72	44	to	to	PART
esrj-65577	72	45	be	be	AUX
esrj-65577	72	46	introduced	introduce	VERB
esrj-65577	72	47	in	in	ADP
esrj-65577	72	48	section	section	NOUN
esrj-65577	72	49	3	3	NUM
esrj-65577	72	50	.	.	PUNCT
esrj-65577	73	1	if	if	SCONJ
esrj-65577	73	2	some	some	PRON
esrj-65577	73	3	of	of	ADP
esrj-65577	73	4	these	these	DET
esrj-65577	73	5	parameters	parameter	NOUN
esrj-65577	73	6	show	show	VERB
esrj-65577	73	7	to	to	PART
esrj-65577	73	8	be	be	AUX
esrj-65577	73	9	not	not	PART
esrj-65577	73	10	significant	significant	ADJ
esrj-65577	73	11	after	after	ADP
esrj-65577	73	12	a	a	DET
esrj-65577	73	13	preliminary	preliminary	ADJ
esrj-65577	73	14	statistical	statistical	ADJ
esrj-65577	73	15	analysis	analysis	NOUN
esrj-65577	73	16	,	,	PUNCT
esrj-65577	73	17	the	the	DET
esrj-65577	73	18	terms	term	NOUN
esrj-65577	73	19	related	relate	VERB
esrj-65577	73	20	to	to	ADP
esrj-65577	73	21	these	these	DET
esrj-65577	73	22	parameters	parameter	NOUN
esrj-65577	73	23	are	be	AUX
esrj-65577	73	24	deleted	delete	VERB
esrj-65577	73	25	from	from	ADP
esrj-65577	73	26	the	the	DET
esrj-65577	73	27	model	model	NOUN
esrj-65577	73	28	to	to	PART
esrj-65577	73	29	develop	develop	VERB
esrj-65577	73	30	a	a	DET
esrj-65577	73	31	further	further	ADJ
esrj-65577	73	32	analysis	analysis	NOUN
esrj-65577	73	33	.	.	PUNCT
esrj-65577	74	1	the	the	DET
esrj-65577	74	2	final	final	ADJ
esrj-65577	74	3	decision	decision	NOUN
esrj-65577	74	4	on	on	ADP
esrj-65577	74	5	which	which	PRON
esrj-65577	74	6	harmonics	harmonic	NOUN
esrj-65577	74	7	should	should	AUX
esrj-65577	74	8	be	be	AUX
esrj-65577	74	9	included	include	VERB
esrj-65577	74	10	in	in	ADP
esrj-65577	74	11	the	the	DET
esrj-65577	74	12	model	model	NOUN
esrj-65577	74	13	must	must	AUX
esrj-65577	74	14	be	be	AUX
esrj-65577	74	15	made	make	VERB
esrj-65577	74	16	considering	consider	VERB
esrj-65577	74	17	some	some	DET
esrj-65577	74	18	criteria	criterion	NOUN
esrj-65577	74	19	for	for	ADP
esrj-65577	74	20	model	model	NOUN
esrj-65577	74	21	selection	selection	NOUN
esrj-65577	74	22	or	or	CCONJ
esrj-65577	74	23	hypothesis	hypothesis	NOUN
esrj-65577	74	24	test	test	NOUN
esrj-65577	74	25	on	on	ADP
esrj-65577	74	26	the	the	DET
esrj-65577	74	27	fitted	fit	VERB
esrj-65577	74	28	coefficients	coefficient	NOUN
esrj-65577	74	29	α1,i	α1,i	PROPN
esrj-65577	74	30	and	and	CCONJ
esrj-65577	74	31	α2,i	α2,i	PROPN
esrj-65577	74	32	.	.	PROPN
esrj-65577	75	1	3	3	X
esrj-65577	75	2	.	.	PUNCT
esrj-65577	76	1	the	the	DET
esrj-65577	76	2	proposed	propose	VERB
esrj-65577	76	3	seasonal	seasonal	ADJ
esrj-65577	76	4	autoregressive	autoregressive	ADJ
esrj-65577	76	5	model	model	NOUN
esrj-65577	76	6	in	in	ADP
esrj-65577	76	7	hydrological	hydrological	ADJ
esrj-65577	76	8	or	or	CCONJ
esrj-65577	76	9	meteorological	meteorological	ADJ
esrj-65577	76	10	time	time	NOUN
esrj-65577	76	11	series	series	NOUN
esrj-65577	76	12	,	,	PUNCT
esrj-65577	76	13	we	we	PRON
esrj-65577	76	14	usually	usually	ADV
esrj-65577	76	15	assume	assume	VERB
esrj-65577	76	16	that	that	SCONJ
esrj-65577	76	17	the	the	DET
esrj-65577	76	18	observations	observation	NOUN
esrj-65577	76	19	of	of	ADP
esrj-65577	76	20	interest	interest	NOUN
esrj-65577	76	21	are	be	AUX
esrj-65577	76	22	generated	generate	VERB
esrj-65577	76	23	from	from	ADP
esrj-65577	76	24	a	a	DET
esrj-65577	76	25	conditional	conditional	ADJ
esrj-65577	76	26	continuous	continuous	ADJ
esrj-65577	76	27	probability	probability	NOUN
esrj-65577	76	28	distribution	distribution	NOUN
esrj-65577	76	29	function	function	NOUN
esrj-65577	76	30	.	.	PUNCT
esrj-65577	77	1	as	as	ADP
esrj-65577	77	2	special	special	ADJ
esrj-65577	77	3	cases	case	NOUN
esrj-65577	77	4	,	,	PUNCT
esrj-65577	77	5	we	we	PRON
esrj-65577	77	6	could	could	AUX
esrj-65577	77	7	assume	assume	VERB
esrj-65577	77	8	that	that	SCONJ
esrj-65577	77	9	the	the	DET
esrj-65577	77	10	observations	observation	NOUN
esrj-65577	77	11	are	be	AUX
esrj-65577	77	12	generated	generate	VERB
esrj-65577	77	13	from	from	ADP
esrj-65577	77	14	standard	standard	ADJ
esrj-65577	77	15	normal	normal	ADJ
esrj-65577	77	16	,	,	PUNCT
esrj-65577	77	17	gamma	gamma	NOUN
esrj-65577	77	18	,	,	PUNCT
esrj-65577	77	19	beta	beta	NOUN
esrj-65577	77	20	or	or	CCONJ
esrj-65577	77	21	exponential	exponential	ADJ
esrj-65577	77	22	conditional	conditional	ADJ
esrj-65577	77	23	density	density	NOUN
esrj-65577	77	24	functions	function	NOUN
esrj-65577	77	25	,	,	PUNCT
esrj-65577	77	26	denoted	denote	VERB
esrj-65577	77	27	by	by	ADP
esrj-65577	77	28	f	f	PROPN
esrj-65577	77	29	(	(	PUNCT
esrj-65577	77	30	yt	yt	PROPN
esrj-65577	77	31	│	│	NUM
esrj-65577	77	32	ht-1	ht-1	NUM
esrj-65577	77	33	)	)	PUNCT
esrj-65577	77	34	,	,	PUNCT
esrj-65577	77	35	t	t	PROPN
esrj-65577	77	36	=	=	SYM
esrj-65577	77	37	1,2,	1,2,	NUM
esrj-65577	77	38	...	...	PUNCT
esrj-65577	77	39	,t	,t	PUNCT
esrj-65577	77	40	,	,	PUNCT
esrj-65577	77	41	where	where	SCONJ
esrj-65577	77	42	ht-1	ht-1	PRON
esrj-65577	77	43	is	be	AUX
esrj-65577	77	44	the	the	DET
esrj-65577	77	45	available	available	ADJ
esrj-65577	77	46	information	information	NOUN
esrj-65577	77	47	up	up	ADP
esrj-65577	77	48	to	to	ADP
esrj-65577	77	49	time	time	NOUN
esrj-65577	77	50	t	t	PROPN
esrj-65577	77	51	1	1	NUM
esrj-65577	77	52	and	and	CCONJ
esrj-65577	77	53	thus	thus	ADV
esrj-65577	77	54	yt	yt	PRON
esrj-65577	77	55	has	have	VERB
esrj-65577	77	56	conditional	conditional	ADJ
esrj-65577	77	57	means	mean	NOUN
esrj-65577	77	58	and	and	CCONJ
esrj-65577	77	59	variances	variance	NOUN
esrj-65577	77	60	given	give	VERB
esrj-65577	77	61	respectively	respectively	ADV
esrj-65577	77	62	by	by	ADP
esrj-65577	77	63	µt	µt	PROPN
esrj-65577	77	64	=	=	SYM
esrj-65577	77	65	e	e	X
esrj-65577	77	66	(	(	PUNCT
esrj-65577	77	67	yt	yt	PROPN
esrj-65577	77	68	|ht-1	|ht-1	PROPN
esrj-65577	77	69	)	)	PUNCT
esrj-65577	77	70	and	and	CCONJ
esrj-65577	77	71	ht	ht	PROPN
esrj-65577	77	72	=	=	NOUN
esrj-65577	77	73	var(yt	var(yt	X
esrj-65577	77	74	|ht-1	|ht-1	NOUN
esrj-65577	77	75	)	)	PUNCT
esrj-65577	77	76	,	,	PUNCT
esrj-65577	77	77	following	follow	VERB
esrj-65577	77	78	the	the	DET
esrj-65577	77	79	models	model	NOUN
esrj-65577	77	80	:	:	PUNCT
esrj-65577	77	81	where	where	SCONJ
esrj-65577	77	82	β	β	X
esrj-65577	77	83	=	=	PUNCT
esrj-65577	77	84	{	{	PUNCT
esrj-65577	77	85	α0	α0	ADJ
esrj-65577	77	86	,	,	PUNCT
esrj-65577	77	87	α1,1	α1,1	INTJ
esrj-65577	77	88	,	,	PUNCT
esrj-65577	77	89	...	...	PUNCT
esrj-65577	77	90	,	,	PUNCT
esrj-65577	77	91	α1,q	α1,q	PROPN
esrj-65577	77	92	,	,	PUNCT
esrj-65577	77	93	α2,1	α2,1	PROPN
esrj-65577	77	94	,	,	PUNCT
esrj-65577	77	95	...	...	PUNCT
esrj-65577	77	96	,	,	PUNCT
esrj-65577	77	97	α2,q	α2,q	PROPN
esrj-65577	77	98	,	,	PUNCT
esrj-65577	77	99	ϕ1,	ϕ1,	ADJ
esrj-65577	77	100	...	...	PUNCT
esrj-65577	77	101	,ϕp	,ϕp	PUNCT
esrj-65577	77	102	,	,	PUNCT
esrj-65577	77	103	}	}	PUNCT
esrj-65577	77	104	,	,	PUNCT
esrj-65577	77	105	is	be	AUX
esrj-65577	77	106	the	the	DET
esrj-65577	77	107	vector	vector	NOUN
esrj-65577	77	108	of	of	ADP
esrj-65577	77	109	parameters	parameter	NOUN
esrj-65577	77	110	for	for	ADP
esrj-65577	77	111	the	the	DET
esrj-65577	77	112	mean	mean	ADJ
esrj-65577	77	113	model	model	NOUN
esrj-65577	77	114	and	and	CCONJ
esrj-65577	77	115	γ	γ	X
esrj-65577	77	116	=	=	SYM
esrj-65577	77	117	{	{	PUNCT
esrj-65577	77	118	λ0	λ0	NOUN
esrj-65577	77	119	,	,	PUNCT
esrj-65577	77	120	λ1,1	λ1,1	NOUN
esrj-65577	77	121	,	,	PUNCT
esrj-65577	77	122	...	...	PUNCT
esrj-65577	77	123	,	,	PUNCT
esrj-65577	77	124	λ1,s	λ1,s	PROPN
esrj-65577	77	125	,	,	PUNCT
esrj-65577	77	126	λ2,1	λ2,1	PROPN
esrj-65577	77	127	,	,	PUNCT
esrj-65577	77	128	...	...	PUNCT
esrj-65577	77	129	,	,	PUNCT
esrj-65577	77	130	λ2,s	λ2,s	PROPN
esrj-65577	77	131	,	,	PUNCT
esrj-65577	77	132	θ1,	θ1,	NOUN
esrj-65577	77	133	...	...	PUNCT
esrj-65577	77	134	,θr	,θr	PUNCT
esrj-65577	77	135	}	}	PUNCT
esrj-65577	77	136	is	be	AUX
esrj-65577	77	137	the	the	DET
esrj-65577	77	138	vector	vector	NOUN
esrj-65577	77	139	of	of	ADP
esrj-65577	77	140	the	the	DET
esrj-65577	77	141	parameters	parameter	NOUN
esrj-65577	77	142	for	for	ADP
esrj-65577	77	143	the	the	DET
esrj-65577	77	144	variance	variance	NOUN
esrj-65577	77	145	model	model	NOUN
esrj-65577	77	146	,	,	PUNCT
esrj-65577	77	147	fi	fi	NOUN
esrj-65577	78	1	=	=	PUNCT
esrj-65577	78	2	i	i	PROPN
esrj-65577	78	3	/	/	SYM
esrj-65577	78	4	t	t	PROPN
esrj-65577	78	5	the	the	DET
esrj-65577	78	6	ith	ith	PROPN
esrj-65577	78	7	harmonic	harmonic	NOUN
esrj-65577	78	8	of	of	ADP
esrj-65577	78	9	the	the	DET
esrj-65577	78	10	fundamental	fundamental	ADJ
esrj-65577	78	11	frequency	frequency	NOUN
esrj-65577	78	12	1	1	NUM
esrj-65577	78	13	/	/	SYM
esrj-65577	78	14	t.	t.	NOUN
esrj-65577	78	15	in	in	ADP
esrj-65577	78	16	this	this	DET
esrj-65577	78	17	paper	paper	NOUN
esrj-65577	78	18	,	,	PUNCT
esrj-65577	78	19	the	the	DET
esrj-65577	78	20	parameters	parameter	NOUN
esrj-65577	78	21	of	of	ADP
esrj-65577	78	22	the	the	DET
esrj-65577	78	23	proposed	propose	VERB
esrj-65577	78	24	models	model	NOUN
esrj-65577	78	25	are	be	AUX
esrj-65577	78	26	estimated	estimate	VERB
esrj-65577	78	27	under	under	ADP
esrj-65577	78	28	a	a	DET
esrj-65577	78	29	bayesian	bayesian	NOUN
esrj-65577	78	30	approach	approach	NOUN
esrj-65577	78	31	.	.	PUNCT
esrj-65577	79	1	in	in	ADP
esrj-65577	79	2	order	order	NOUN
esrj-65577	79	3	to	to	PART
esrj-65577	79	4	illustrate	illustrate	VERB
esrj-65577	79	5	the	the	DET
esrj-65577	79	6	proposed	propose	VERB
esrj-65577	79	7	methodology	methodology	NOUN
esrj-65577	79	8	,	,	PUNCT
esrj-65577	79	9	we	we	PRON
esrj-65577	79	10	also	also	ADV
esrj-65577	79	11	include	include	VERB
esrj-65577	79	12	the	the	DET
esrj-65577	79	13	regression	regression	NOUN
esrj-65577	79	14	equations	equation	NOUN
esrj-65577	79	15	relating	relate	VERB
esrj-65577	79	16	the	the	DET
esrj-65577	79	17	mean	mean	ADJ
esrj-65577	79	18	and	and	CCONJ
esrj-65577	79	19	variance	variance	NOUN
esrj-65577	79	20	parameters	parameter	NOUN
esrj-65577	79	21	to	to	ADP
esrj-65577	79	22	the	the	DET
esrj-65577	79	23	assumed	assume	VERB
esrj-65577	79	24	covariates	covariate	NOUN
esrj-65577	79	25	assuming	assume	VERB
esrj-65577	79	26	gamma	gamma	NOUN
esrj-65577	79	27	and	and	CCONJ
esrj-65577	79	28	beta	beta	ADJ
esrj-65577	79	29	distributions	distribution	NOUN
esrj-65577	79	30	for	for	ADP
esrj-65577	79	31	the	the	DET
esrj-65577	79	32	data	datum	NOUN
esrj-65577	79	33	.	.	PUNCT
esrj-65577	80	1	in	in	ADP
esrj-65577	80	2	this	this	DET
esrj-65577	80	3	way	way	NOUN
esrj-65577	80	4	,	,	PUNCT
esrj-65577	80	5	we	we	PRON
esrj-65577	80	6	have	have	VERB
esrj-65577	80	7	,	,	PUNCT
esrj-65577	80	8	the	the	DET
esrj-65577	80	9	following	follow	VERB
esrj-65577	80	10	modeling	model	VERB
esrj-65577	80	11	steps	step	NOUN
esrj-65577	80	12	:	:	PUNCT
esrj-65577	81	1	1	1	X
esrj-65577	81	2	.	.	X
esrj-65577	81	3	if	if	SCONJ
esrj-65577	81	4	yt	yt	PROPN
esrj-65577	81	5	,	,	PUNCT
esrj-65577	81	6	t	t	PROPN
esrj-65577	81	7	=	=	SYM
esrj-65577	81	8	1,2,	1,2,	NUM
esrj-65577	81	9	...	...	PUNCT
esrj-65577	81	10	,t	,t	PUNCT
esrj-65577	81	11	,	,	PUNCT
esrj-65577	81	12	follows	follow	VERB
esrj-65577	81	13	a	a	DET
esrj-65577	81	14	gamma	gamma	NOUN
esrj-65577	81	15	conditional	conditional	ADJ
esrj-65577	81	16	distribution	distribution	NOUN
esrj-65577	81	17	g(pt	g(pt	PROPN
esrj-65577	81	18	,	,	PUNCT
esrj-65577	81	19	qt	qt	PROPN
esrj-65577	81	20	)	)	PUNCT
esrj-65577	81	21	,	,	PUNCT
esrj-65577	81	22	where	where	SCONJ
esrj-65577	81	23	g(p	g(p	PROPN
esrj-65577	81	24	,	,	PUNCT
esrj-65577	81	25	q	q	NOUN
esrj-65577	81	26	)	)	PUNCT
esrj-65577	81	27	denotes	denote	VERB
esrj-65577	81	28	a	a	DET
esrj-65577	81	29	gamma	gamma	NOUN
esrj-65577	81	30	distribution	distribution	NOUN
esrj-65577	81	31	with	with	ADP
esrj-65577	81	32	mean	mean	PROPN
esrj-65577	81	33	pq	pq	NOUN
esrj-65577	81	34	and	and	CCONJ
esrj-65577	81	35	variance	variance	NOUN
esrj-65577	81	36	pq2	pq2	NOUN
esrj-65577	81	37	,	,	PUNCT
esrj-65577	81	38	the	the	DET
esrj-65577	81	39	conditional	conditional	ADJ
esrj-65577	81	40	mean	mean	NOUN
esrj-65577	81	41	and	and	CCONJ
esrj-65577	81	42	variance	variance	NOUN
esrj-65577	81	43	are	be	AUX
esrj-65577	81	44	related	relate	VERB
esrj-65577	81	45	to	to	ADP
esrj-65577	81	46	the	the	DET
esrj-65577	81	47	original	original	ADJ
esrj-65577	81	48	parameters	parameter	NOUN
esrj-65577	81	49	by	by	ADP
esrj-65577	81	50	the	the	DET
esrj-65577	81	51	equations	equation	NOUN
esrj-65577	81	52	µt=	µt=	VERB
esrj-65577	81	53	pt	pt	PROPN
esrj-65577	81	54	qt	qt	NOUN
esrj-65577	81	55	and	and	CCONJ
esrj-65577	81	56	ht	ht	PROPN
esrj-65577	82	1	=	=	NOUN
esrj-65577	82	2	µt	µt	PRON
esrj-65577	82	3	qt	qt	NOUN
esrj-65577	82	4	.	.	PROPN
esrj-65577	83	1	2	2	X
esrj-65577	83	2	.	.	X
esrj-65577	84	1	if	if	SCONJ
esrj-65577	84	2	yt	yt	PROPN
esrj-65577	84	3	,	,	PUNCT
esrj-65577	84	4	t	t	PROPN
esrj-65577	84	5	=	=	SYM
esrj-65577	84	6	1,2,	1,2,	NUM
esrj-65577	84	7	...	...	PUNCT
esrj-65577	84	8	,t	,t	PUNCT
esrj-65577	84	9	,	,	PUNCT
esrj-65577	84	10	follows	follow	VERB
esrj-65577	84	11	a	a	DET
esrj-65577	84	12	beta	beta	ADJ
esrj-65577	84	13	distribution	distribution	NOUN
esrj-65577	84	14	function	function	NOUN
esrj-65577	84	15	b(pt	b(pt	NOUN
esrj-65577	84	16	,	,	PUNCT
esrj-65577	84	17	qt	qt	NOUN
esrj-65577	84	18	)	)	PUNCT
esrj-65577	84	19	,	,	PUNCT
esrj-65577	84	20	we	we	PRON
esrj-65577	84	21	consider	consider	VERB
esrj-65577	84	22	a	a	DET
esrj-65577	84	23	reparameterization	reparameterization	NOUN
esrj-65577	84	24	of	of	ADP
esrj-65577	84	25	the	the	DET
esrj-65577	84	26	beta	beta	ADJ
esrj-65577	84	27	distribution	distribution	NOUN
esrj-65577	84	28	density	density	NOUN
esrj-65577	84	29	as	as	ADP
esrj-65577	84	30	a	a	DET
esrj-65577	84	31	function	function	NOUN
esrj-65577	84	32	of	of	ADP
esrj-65577	84	33	the	the	DET
esrj-65577	84	34	mean	mean	NOUN
esrj-65577	84	35	and	and	CCONJ
esrj-65577	84	36	precision	precision	NOUN
esrj-65577	84	37	,	,	PUNCT
esrj-65577	84	38	ϕt	ϕt	ADV
esrj-65577	84	39	=	=	SYM
esrj-65577	84	40	pt	pt	PROPN
esrj-65577	84	41	+	+	NUM
esrj-65577	84	42	qt	qt	PROPN
esrj-65577	84	43	,	,	PUNCT
esrj-65577	84	44	which	which	PRON
esrj-65577	84	45	results	result	VERB
esrj-65577	84	46	to	to	PART
esrj-65577	84	47	be	be	AUX
esrj-65577	84	48	appropriate	appropriate	ADJ
esrj-65577	84	49	in	in	ADP
esrj-65577	84	50	order	order	NOUN
esrj-65577	84	51	to	to	PART
esrj-65577	84	52	define	define	VERB
esrj-65577	84	53	the	the	DET
esrj-65577	84	54	joint	joint	ADJ
esrj-65577	84	55	mean	mean	NOUN
esrj-65577	84	56	and	and	CCONJ
esrj-65577	84	57	precision	precision	NOUN
esrj-65577	84	58	beta	beta	NOUN
esrj-65577	84	59	regression	regression	NOUN
esrj-65577	84	60	models	model	NOUN
esrj-65577	84	61	as	as	SCONJ
esrj-65577	84	62	introduced	introduce	VERB
esrj-65577	84	63	by	by	ADP
esrj-65577	84	64	cepeda	cepeda	PROPN
esrj-65577	84	65	(	(	PUNCT
esrj-65577	84	66	2001	2001	NUM
esrj-65577	84	67	)	)	PUNCT
esrj-65577	84	68	.	.	PUNCT
esrj-65577	85	1	this	this	DET
esrj-65577	85	2	reparameterization	reparameterization	NOUN
esrj-65577	85	3	,	,	PUNCT
esrj-65577	85	4	where	where	SCONJ
esrj-65577	85	5	ϕ	ϕ	NOUN
esrj-65577	85	6	=	=	PUNCT
esrj-65577	85	7	p	p	X
esrj-65577	85	8	+	+	CCONJ
esrj-65577	85	9	q	q	ADJ
esrj-65577	85	10	,	,	PUNCT
esrj-65577	85	11	p	p	X
esrj-65577	85	12	=	=	X
esrj-65577	85	13	µϕ	µϕ	ADJ
esrj-65577	85	14	and	and	CCONJ
esrj-65577	85	15	q	q	PROPN
esrj-65577	85	16	=	=	SYM
esrj-65577	85	17	ϕ(1	ϕ(1	PROPN
esrj-65577	85	18	µ	µ	NUM
esrj-65577	85	19	)	)	PUNCT
esrj-65577	85	20	,	,	PUNCT
esrj-65577	85	21	has	have	AUX
esrj-65577	85	22	been	be	AUX
esrj-65577	85	23	extensively	extensively	ADV
esrj-65577	85	24	used	use	VERB
esrj-65577	85	25	in	in	ADP
esrj-65577	85	26	the	the	DET
esrj-65577	85	27	literature	literature	NOUN
esrj-65577	85	28	following	follow	VERB
esrj-65577	85	29	the	the	DET
esrj-65577	85	30	joint	joint	ADJ
esrj-65577	85	31	modeling	modeling	NOUN
esrj-65577	85	32	approach	approach	NOUN
esrj-65577	85	33	for	for	ADP
esrj-65577	85	34	the	the	DET
esrj-65577	85	35	mean	mean	ADJ
esrj-65577	85	36	and	and	CCONJ
esrj-65577	85	37	precision	precision	NOUN
esrj-65577	85	38	beta	beta	NOUN
esrj-65577	85	39	parameters	parameter	NOUN
esrj-65577	85	40	introduced	introduce	VERB
esrj-65577	85	41	by	by	ADP
esrj-65577	85	42	cepeda	cepeda	PROPN
esrj-65577	85	43	(	(	PUNCT
esrj-65577	85	44	2001	2001	NUM
esrj-65577	85	45	)	)	PUNCT
esrj-65577	85	46	and	and	CCONJ
esrj-65577	85	47	cepeda	cepeda	PROPN
esrj-65577	85	48	and	and	CCONJ
esrj-65577	85	49	gamerman	gamerman	NOUN
esrj-65577	85	50	(	(	PUNCT
esrj-65577	85	51	2005	2005	NUM
esrj-65577	85	52	)	)	PUNCT
esrj-65577	85	53	,	,	PUNCT
esrj-65577	85	54	under	under	ADP
esrj-65577	85	55	a	a	DET
esrj-65577	85	56	bayesian	bayesian	NOUN
esrj-65577	85	57	approach	approach	NOUN
esrj-65577	85	58	.	.	PUNCT
esrj-65577	86	1	it	it	PRON
esrj-65577	86	2	is	be	AUX
esrj-65577	86	3	important	important	ADJ
esrj-65577	86	4	to	to	PART
esrj-65577	86	5	point	point	VERB
esrj-65577	86	6	out	out	ADP
esrj-65577	86	7	that	that	SCONJ
esrj-65577	86	8	ferrari	ferrari	PROPN
esrj-65577	86	9	and	and	CCONJ
esrj-65577	86	10	cribarineto	cribarineto	PROPN
esrj-65577	86	11	(	(	PUNCT
esrj-65577	86	12	2004	2004	NUM
esrj-65577	86	13	)	)	PUNCT
esrj-65577	86	14	also	also	ADV
esrj-65577	86	15	introduced	introduce	VERB
esrj-65577	86	16	a	a	DET
esrj-65577	86	17	beta	beta	NOUN
esrj-65577	86	18	modeling	modeling	NOUN
esrj-65577	86	19	approach	approach	NOUN
esrj-65577	86	20	for	for	ADP
esrj-65577	86	21	the	the	DET
esrj-65577	86	22	mean	mean	NOUN
esrj-65577	86	23	but	but	CCONJ
esrj-65577	86	24	assuming	assume	VERB
esrj-65577	86	25	constant	constant	ADJ
esrj-65577	86	26	precision	precision	NOUN
esrj-65577	86	27	parameters	parameter	NOUN
esrj-65577	86	28	,	,	PUNCT
esrj-65577	86	29	under	under	ADP
esrj-65577	86	30	a	a	DET
esrj-65577	86	31	classical	classical	ADJ
esrj-65577	86	32	approach	approach	NOUN
esrj-65577	86	33	.	.	PUNCT
esrj-65577	87	1	in	in	ADP
esrj-65577	87	2	all	all	PRON
esrj-65577	87	3	of	of	ADP
esrj-65577	87	4	these	these	DET
esrj-65577	87	5	cases	case	NOUN
esrj-65577	87	6	,	,	PUNCT
esrj-65577	87	7	ϕ	ϕ	PROPN
esrj-65577	87	8	can	can	AUX
esrj-65577	87	9	be	be	AUX
esrj-65577	87	10	interpreted	interpret	VERB
esrj-65577	87	11	as	as	ADP
esrj-65577	87	12	a	a	DET
esrj-65577	87	13	precision	precision	NOUN
esrj-65577	87	14	parameter	parameter	NOUN
esrj-65577	87	15	in	in	ADP
esrj-65577	87	16	the	the	DET
esrj-65577	87	17	sense	sense	NOUN
esrj-65577	87	18	that	that	SCONJ
esrj-65577	87	19	,	,	PUNCT
esrj-65577	87	20	for	for	ADP
esrj-65577	87	21	fixed	fix	VERB
esrj-65577	87	22	values	value	NOUN
esrj-65577	87	23	of	of	ADP
esrj-65577	87	24	µ	µ	NOUN
esrj-65577	87	25	,	,	PUNCT
esrj-65577	87	26	larger	large	ADJ
esrj-65577	87	27	values	value	NOUN
esrj-65577	87	28	of	of	ADP
esrj-65577	87	29	ϕ	ϕ	PROPN
esrj-65577	87	30	correspond	correspond	NOUN
esrj-65577	87	31	to	to	ADP
esrj-65577	87	32	smaller	small	ADJ
esrj-65577	87	33	values	value	NOUN
esrj-65577	87	34	for	for	ADP
esrj-65577	87	35	the	the	DET
esrj-65577	87	36	variance	variance	NOUN
esrj-65577	87	37	of	of	ADP
esrj-65577	87	38	y.	y.	NOUN
esrj-65577	87	39	this	this	DET
esrj-65577	87	40	interpretation	interpretation	NOUN
esrj-65577	87	41	could	could	AUX
esrj-65577	87	42	be	be	AUX
esrj-65577	87	43	not	not	PART
esrj-65577	87	44	so	so	ADV
esrj-65577	87	45	simple	simple	ADJ
esrj-65577	87	46	.	.	PUNCT
esrj-65577	88	1	in	in	ADP
esrj-65577	88	2	this	this	DET
esrj-65577	88	3	paper	paper	NOUN
esrj-65577	88	4	,	,	PUNCT
esrj-65577	88	5	we	we	PRON
esrj-65577	88	6	use	use	VERB
esrj-65577	88	7	the	the	DET
esrj-65577	88	8	mean	mean	ADJ
esrj-65577	88	9	and	and	CCONJ
esrj-65577	88	10	variance	variance	NOUN
esrj-65577	88	11	reparameterization	reparameterization	NOUN
esrj-65577	88	12	of	of	ADP
esrj-65577	88	13	the	the	DET
esrj-65577	88	14	probability	probability	NOUN
esrj-65577	88	15	beta	beta	NOUN
esrj-65577	88	16	distribution	distribution	NOUN
esrj-65577	88	17	in	in	ADP
esrj-65577	88	18	the	the	DET
esrj-65577	88	19	definition	definition	NOUN
esrj-65577	88	20	of	of	ADP
esrj-65577	88	21	joint	joint	ADJ
esrj-65577	88	22	mean	mean	NOUN
esrj-65577	88	23	and	and	CCONJ
esrj-65577	88	24	variance	variance	VERB
esrj-65577	88	25	beta	beta	NOUN
esrj-65577	88	26	regression	regression	NOUN
esrj-65577	88	27	models	model	NOUN
esrj-65577	88	28	(	(	PUNCT
esrj-65577	88	29	cepeda	cepeda	PROPN
esrj-65577	88	30	-	-	PUNCT
esrj-65577	88	31	cuervo	cuervo	PROPN
esrj-65577	88	32	,	,	PUNCT
esrj-65577	88	33	2015	2015	NUM
esrj-65577	88	34	)	)	PUNCT
esrj-65577	88	35	,	,	PUNCT
esrj-65577	88	36	taking	take	VERB
esrj-65577	88	37	into	into	ADP
esrj-65577	88	38	account	account	NOUN
esrj-65577	88	39	that	that	SCONJ
esrj-65577	88	40	µ(1	µ(1	PROPN
esrj-65577	88	41	µ	µ	PROPN
esrj-65577	88	42	)	)	PUNCT
esrj-65577	88	43	>	>	X
esrj-65577	88	44	σ2	σ2	PROPN
esrj-65577	88	45	;	;	PUNCT
esrj-65577	88	46	in	in	ADP
esrj-65577	88	47	this	this	DET
esrj-65577	88	48	way	way	NOUN
esrj-65577	88	49	,	,	PUNCT
esrj-65577	88	50	samples	sample	NOUN
esrj-65577	88	51	of	of	ADP
esrj-65577	88	52	the	the	DET
esrj-65577	88	53	joint	joint	ADJ
esrj-65577	88	54	posterior	posterior	ADJ
esrj-65577	88	55	distribution	distribution	NOUN
esrj-65577	88	56	for	for	ADP
esrj-65577	88	57	the	the	DET
esrj-65577	88	58	regression	regression	NOUN
esrj-65577	88	59	parameters	parameter	NOUN
esrj-65577	88	60	should	should	AUX
esrj-65577	88	61	be	be	AUX
esrj-65577	88	62	simulated	simulate	VERB
esrj-65577	88	63	in	in	ADP
esrj-65577	88	64	the	the	DET
esrj-65577	88	65	subspace	subspace	NOUN
esrj-65577	88	66	of	of	ADP
esrj-65577	88	67	parameters	parameter	NOUN
esrj-65577	88	68	that	that	PRON
esrj-65577	88	69	satisfy	satisfy	VERB
esrj-65577	88	70	this	this	DET
esrj-65577	88	71	property	property	NOUN
esrj-65577	88	72	.	.	PUNCT
esrj-65577	89	1	although	although	SCONJ
esrj-65577	89	2	this	this	DET
esrj-65577	89	3	reparameterization	reparameterization	NOUN
esrj-65577	89	4	results	result	VERB
esrj-65577	89	5	in	in	ADP
esrj-65577	89	6	a	a	DET
esrj-65577	89	7	86	86	NUM
esrj-65577	89	8	edilberto	edilberto	PROPN
esrj-65577	89	9	cepeda	cepeda	PROPN
esrj-65577	89	10	cuervo	cuervo	PROPN
esrj-65577	89	11	,	,	PUNCT
esrj-65577	89	12	jorge	jorge	PROPN
esrj-65577	89	13	alberto	alberto	PROPN
esrj-65577	89	14	achcar	achcar	PROPN
esrj-65577	89	15	,	,	PUNCT
esrj-65577	89	16	marinho	marinho	PROPN
esrj-65577	89	17	g.	g.	PROPN
esrj-65577	89	18	andrade	andrade	PROPN
esrj-65577	89	19	complex	complex	ADJ
esrj-65577	89	20	expression	expression	NOUN
esrj-65577	89	21	for	for	ADP
esrj-65577	89	22	the	the	DET
esrj-65577	89	23	beta	beta	ADJ
esrj-65577	89	24	distribution	distribution	NOUN
esrj-65577	89	25	,	,	PUNCT
esrj-65577	89	26	it	it	PRON
esrj-65577	89	27	leads	lead	VERB
esrj-65577	89	28	to	to	ADP
esrj-65577	89	29	a	a	DET
esrj-65577	89	30	best	good	ADJ
esrj-65577	89	31	and	and	CCONJ
esrj-65577	89	32	more	more	ADV
esrj-65577	89	33	easily	easily	ADV
esrj-65577	89	34	interpretation	interpretation	NOUN
esrj-65577	89	35	for	for	ADP
esrj-65577	89	36	the	the	DET
esrj-65577	89	37	statistical	statistical	ADJ
esrj-65577	89	38	analysis	analysis	NOUN
esrj-65577	89	39	results	result	NOUN
esrj-65577	89	40	in	in	ADP
esrj-65577	89	41	the	the	DET
esrj-65577	89	42	applications	application	NOUN
esrj-65577	89	43	.	.	PUNCT
esrj-65577	90	1	(	(	PUNCT
esrj-65577	90	2	8)	8)	NUM
esrj-65577	90	3	(	(	PUNCT
esrj-65577	90	4	10	10	NUM
esrj-65577	90	5	)	)	PUNCT
esrj-65577	90	6	(	(	PUNCT
esrj-65577	90	7	11	11	NUM
esrj-65577	90	8	)	)	PUNCT
esrj-65577	90	9	(	(	PUNCT
esrj-65577	90	10	9	9	NUM
esrj-65577	90	11	)	)	PUNCT
esrj-65577	90	12	in	in	ADP
esrj-65577	90	13	this	this	DET
esrj-65577	90	14	reparameterization	reparameterization	NOUN
esrj-65577	90	15	,	,	PUNCT
esrj-65577	90	16	where	where	SCONJ
esrj-65577	90	17	the	the	DET
esrj-65577	90	18	autoregressive	autoregressive	ADJ
esrj-65577	90	19	seasonal	seasonal	ADJ
esrj-65577	90	20	beta	beta	NOUN
esrj-65577	90	21	regression	regression	NOUN
esrj-65577	90	22	models	model	NOUN
esrj-65577	90	23	have	have	VERB
esrj-65577	90	24	the	the	DET
esrj-65577	90	25	conditional	conditional	ADJ
esrj-65577	90	26	mean	mean	NOUN
esrj-65577	90	27	and	and	CCONJ
esrj-65577	90	28	variance	variance	NOUN
esrj-65577	90	29	model	model	NOUN
esrj-65577	90	30	given	give	VERB
esrj-65577	90	31	by	by	ADP
esrj-65577	90	32	the	the	DET
esrj-65577	90	33	equations	equation	NOUN
esrj-65577	90	34	(	(	PUNCT
esrj-65577	90	35	6	6	NUM
esrj-65577	90	36	)	)	PUNCT
esrj-65577	90	37	and	and	CCONJ
esrj-65577	90	38	(	(	PUNCT
esrj-65577	90	39	7	7	NUM
esrj-65577	90	40	)	)	PUNCT
esrj-65577	90	41	.	.	PUNCT
esrj-65577	91	1	special	special	ADJ
esrj-65577	91	2	cases	case	NOUN
esrj-65577	91	3	of	of	ADP
esrj-65577	91	4	this	this	DET
esrj-65577	91	5	model	model	NOUN
esrj-65577	91	6	could	could	AUX
esrj-65577	91	7	be	be	AUX
esrj-65577	91	8	easily	easily	ADV
esrj-65577	91	9	obtained	obtain	VERB
esrj-65577	91	10	from	from	ADP
esrj-65577	91	11	this	this	DET
esrj-65577	91	12	general	general	ADJ
esrj-65577	91	13	model	model	NOUN
esrj-65577	91	14	.	.	PUNCT
esrj-65577	92	1	a	a	DET
esrj-65577	92	2	first	first	ADJ
esrj-65577	92	3	model	model	NOUN
esrj-65577	92	4	is	be	AUX
esrj-65577	92	5	given	give	VERB
esrj-65577	92	6	by	by	ADP
esrj-65577	92	7	a	a	DET
esrj-65577	92	8	seasonal	seasonal	ADJ
esrj-65577	92	9	regression	regression	NOUN
esrj-65577	92	10	mean	mean	NOUN
esrj-65577	92	11	model	model	NOUN
esrj-65577	92	12	,	,	PUNCT
esrj-65577	92	13	with	with	ADP
esrj-65577	92	14	mean	mean	NOUN
esrj-65577	92	15	given	give	VERB
esrj-65577	92	16	by	by	ADP
esrj-65577	92	17	(	(	PUNCT
esrj-65577	92	18	6	6	NUM
esrj-65577	92	19	)	)	PUNCT
esrj-65577	92	20	and	and	CCONJ
esrj-65577	92	21	autoregressive	autoregressive	ADJ
esrj-65577	92	22	variance	variance	NOUN
esrj-65577	92	23	not	not	PART
esrj-65577	92	24	considering	consider	VERB
esrj-65577	92	25	the	the	DET
esrj-65577	92	26	presence	presence	NOUN
esrj-65577	92	27	of	of	ADP
esrj-65577	92	28	seasonal	seasonal	ADJ
esrj-65577	92	29	terms	term	NOUN
esrj-65577	92	30	.	.	PUNCT
esrj-65577	93	1	a	a	DET
esrj-65577	93	2	second	second	ADJ
esrj-65577	93	3	model	model	NOUN
esrj-65577	93	4	,	,	PUNCT
esrj-65577	93	5	also	also	ADV
esrj-65577	93	6	a	a	DET
esrj-65577	93	7	seasonal	seasonal	ADJ
esrj-65577	93	8	mean	mean	NOUN
esrj-65577	93	9	model	model	NOUN
esrj-65577	93	10	,	,	PUNCT
esrj-65577	93	11	is	be	AUX
esrj-65577	93	12	given	give	VERB
esrj-65577	93	13	assuming	assume	VERB
esrj-65577	93	14	the	the	DET
esrj-65577	93	15	mean	mean	NOUN
esrj-65577	93	16	given	give	VERB
esrj-65577	93	17	by	by	ADP
esrj-65577	93	18	(	(	PUNCT
esrj-65577	93	19	6	6	NUM
esrj-65577	93	20	)	)	PUNCT
esrj-65577	93	21	and	and	CCONJ
esrj-65577	93	22	a	a	DET
esrj-65577	93	23	seasonal	seasonal	ADJ
esrj-65577	93	24	variance	variance	NOUN
esrj-65577	93	25	model	model	NOUN
esrj-65577	93	26	not	not	PART
esrj-65577	93	27	considering	consider	VERB
esrj-65577	93	28	the	the	DET
esrj-65577	93	29	presence	presence	NOUN
esrj-65577	93	30	of	of	ADP
esrj-65577	93	31	autoregressive	autoregressive	ADJ
esrj-65577	93	32	terms	term	NOUN
esrj-65577	93	33	.	.	PUNCT
esrj-65577	94	1	a	a	DET
esrj-65577	94	2	third	third	ADJ
esrj-65577	94	3	model	model	NOUN
esrj-65577	94	4	,	,	PUNCT
esrj-65577	94	5	is	be	AUX
esrj-65577	94	6	given	give	VERB
esrj-65577	94	7	by	by	ADP
esrj-65577	94	8	an	an	DET
esrj-65577	94	9	autoregressive	autoregressive	ADJ
esrj-65577	94	10	mean	mean	NOUN
esrj-65577	94	11	model	model	NOUN
esrj-65577	94	12	and	and	CCONJ
esrj-65577	94	13	a	a	DET
esrj-65577	94	14	variance	variance	NOUN
esrj-65577	94	15	model	model	NOUN
esrj-65577	94	16	,	,	PUNCT
esrj-65577	94	17	not	not	PART
esrj-65577	94	18	considering	consider	VERB
esrj-65577	94	19	the	the	DET
esrj-65577	94	20	presence	presence	NOUN
esrj-65577	94	21	of	of	ADP
esrj-65577	94	22	seasonal	seasonal	ADJ
esrj-65577	94	23	terms	term	NOUN
esrj-65577	94	24	in	in	ADP
esrj-65577	94	25	the	the	DET
esrj-65577	94	26	mean	mean	NOUN
esrj-65577	94	27	and	and	CCONJ
esrj-65577	94	28	in	in	ADP
esrj-65577	94	29	the	the	DET
esrj-65577	94	30	variance	variance	NOUN
esrj-65577	94	31	.	.	PUNCT
esrj-65577	95	1	a	a	DET
esrj-65577	95	2	fourth	fourth	ADJ
esrj-65577	95	3	model	model	NOUN
esrj-65577	95	4	,	,	PUNCT
esrj-65577	95	5	is	be	AUX
esrj-65577	95	6	given	give	VERB
esrj-65577	95	7	by	by	ADP
esrj-65577	95	8	an	an	DET
esrj-65577	95	9	autoregressive	autoregressive	ADJ
esrj-65577	95	10	model	model	NOUN
esrj-65577	95	11	,	,	PUNCT
esrj-65577	95	12	with	with	ADP
esrj-65577	95	13	constant	constant	ADJ
esrj-65577	95	14	variance	variance	NOUN
esrj-65577	95	15	.	.	PUNCT
esrj-65577	96	1	4	4	X
esrj-65577	96	2	.	.	NOUN
esrj-65577	96	3	hydrological	hydrological	ADJ
esrj-65577	96	4	time	time	NOUN
esrj-65577	96	5	series	series	PROPN
esrj-65577	96	6	in	in	ADP
esrj-65577	96	7	this	this	DET
esrj-65577	96	8	section	section	NOUN
esrj-65577	96	9	we	we	PRON
esrj-65577	96	10	consider	consider	VERB
esrj-65577	96	11	an	an	DET
esrj-65577	96	12	analysis	analysis	NOUN
esrj-65577	96	13	of	of	ADP
esrj-65577	96	14	the	the	DET
esrj-65577	96	15	furnas	furnas	PROPN
esrj-65577	96	16	dam	dam	PROPN
esrj-65577	96	17	hydroelectric	hydroelectric	ADJ
esrj-65577	96	18	hydrological	hydrological	ADJ
esrj-65577	96	19	time	time	NOUN
esrj-65577	96	20	series	series	PROPN
esrj-65577	96	21	dataset	dataset	PROPN
esrj-65577	96	22	,	,	PUNCT
esrj-65577	96	23	introduced	introduce	VERB
esrj-65577	96	24	in	in	ADP
esrj-65577	96	25	section	section	NOUN
esrj-65577	96	26	1	1	NUM
esrj-65577	96	27	,	,	PUNCT
esrj-65577	96	28	assuming	assume	VERB
esrj-65577	96	29	seasonal	seasonal	ADJ
esrj-65577	96	30	autoregressive	autoregressive	ADJ
esrj-65577	96	31	conditional	conditional	ADJ
esrj-65577	96	32	heteroscedastic	heteroscedastic	ADJ
esrj-65577	96	33	models	model	NOUN
esrj-65577	96	34	.	.	PUNCT
esrj-65577	97	1	the	the	DET
esrj-65577	97	2	first	first	ADJ
esrj-65577	97	3	step	step	NOUN
esrj-65577	97	4	in	in	ADP
esrj-65577	97	5	the	the	DET
esrj-65577	97	6	proposed	propose	VERB
esrj-65577	97	7	analysis	analysis	NOUN
esrj-65577	97	8	is	be	AUX
esrj-65577	97	9	to	to	PART
esrj-65577	97	10	determine	determine	VERB
esrj-65577	97	11	the	the	DET
esrj-65577	97	12	period	period	NOUN
esrj-65577	97	13	for	for	ADP
esrj-65577	97	14	the	the	DET
esrj-65577	97	15	harmonics	harmonic	NOUN
esrj-65577	97	16	of	of	ADP
esrj-65577	97	17	higher	high	ADJ
esrj-65577	97	18	intensity	intensity	NOUN
esrj-65577	97	19	in	in	ADP
esrj-65577	97	20	the	the	DET
esrj-65577	97	21	spectral	spectral	ADJ
esrj-65577	97	22	analysis	analysis	NOUN
esrj-65577	97	23	of	of	ADP
esrj-65577	97	24	the	the	DET
esrj-65577	97	25	streamflows	streamflow	NOUN
esrj-65577	97	26	data	datum	NOUN
esrj-65577	97	27	.	.	PUNCT
esrj-65577	98	1	in	in	ADP
esrj-65577	98	2	this	this	DET
esrj-65577	98	3	way	way	NOUN
esrj-65577	98	4	,	,	PUNCT
esrj-65577	98	5	we	we	PRON
esrj-65577	98	6	note	note	VERB
esrj-65577	98	7	in	in	ADP
esrj-65577	98	8	figure	figure	NOUN
esrj-65577	98	9	3	3	NUM
esrj-65577	98	10	that	that	SCONJ
esrj-65577	98	11	the	the	DET
esrj-65577	98	12	harmonics	harmonic	NOUN
esrj-65577	98	13	of	of	ADP
esrj-65577	98	14	higher	high	ADJ
esrj-65577	98	15	intensity	intensity	NOUN
esrj-65577	98	16	(	(	PUNCT
esrj-65577	98	17	i	i	NOUN
esrj-65577	98	18	)	)	PUNCT
esrj-65577	98	19	corresponds	correspond	VERB
esrj-65577	98	20	to	to	ADP
esrj-65577	98	21	the	the	DET
esrj-65577	98	22	cycle	cycle	NOUN
esrj-65577	98	23	(	(	PUNCT
esrj-65577	98	24	1	1	NUM
esrj-65577	98	25	/	/	SYM
esrj-65577	98	26	fi	fi	NOUN
esrj-65577	98	27	)	)	PUNCT
esrj-65577	98	28	of	of	ADP
esrj-65577	98	29	6	6	NUM
esrj-65577	98	30	and	and	CCONJ
esrj-65577	98	31	12	12	NUM
esrj-65577	98	32	months	month	NOUN
esrj-65577	98	33	,	,	PUNCT
esrj-65577	98	34	given	give	VERB
esrj-65577	98	35	that	that	SCONJ
esrj-65577	98	36	the	the	DET
esrj-65577	98	37	periodogram	periodogram	NOUN
esrj-65577	98	38	shows	show	VERB
esrj-65577	98	39	that	that	SCONJ
esrj-65577	98	40	this	this	DET
esrj-65577	98	41	time	time	NOUN
esrj-65577	98	42	series	series	PROPN
esrj-65577	98	43	contains	contain	VERB
esrj-65577	98	44	two	two	NUM
esrj-65577	98	45	cosinesine	cosinesine	ADJ
esrj-65577	98	46	peaks	peak	NOUN
esrj-65577	98	47	at	at	ADP
esrj-65577	98	48	these	these	DET
esrj-65577	98	49	frequencies	frequency	NOUN
esrj-65577	98	50	.	.	PUNCT
esrj-65577	99	1	there	there	PRON
esrj-65577	99	2	are	be	VERB
esrj-65577	99	3	other	other	ADJ
esrj-65577	99	4	very	very	ADV
esrj-65577	99	5	small	small	ADJ
esrj-65577	99	6	peaks	peak	NOUN
esrj-65577	99	7	in	in	ADP
esrj-65577	99	8	this	this	DET
esrj-65577	99	9	periodogram	periodogram	NOUN
esrj-65577	99	10	,	,	PUNCT
esrj-65577	99	11	possibly	possibly	ADV
esrj-65577	99	12	caused	cause	VERB
esrj-65577	99	13	by	by	ADP
esrj-65577	99	14	noise	noise	NOUN
esrj-65577	99	15	components	component	NOUN
esrj-65577	99	16	.	.	PUNCT
esrj-65577	100	1	thus	thus	ADV
esrj-65577	100	2	,	,	PUNCT
esrj-65577	100	3	the	the	DET
esrj-65577	100	4	seasonal	seasonal	ADJ
esrj-65577	100	5	terms	term	NOUN
esrj-65577	100	6	to	to	PART
esrj-65577	100	7	be	be	AUX
esrj-65577	100	8	included	include	VERB
esrj-65577	100	9	in	in	ADP
esrj-65577	100	10	the	the	DET
esrj-65577	100	11	mean	mean	ADJ
esrj-65577	100	12	equation	equation	NOUN
esrj-65577	100	13	model	model	NOUN
esrj-65577	100	14	of	of	ADP
esrj-65577	100	15	the	the	DET
esrj-65577	100	16	streamflow	streamflow	PROPN
esrj-65577	100	17	series	series	NOUN
esrj-65577	100	18	are	be	AUX
esrj-65577	100	19	given	give	VERB
esrj-65577	100	20	by	by	ADP
esrj-65577	100	21	cos(2πt/6	cos(2πt/6	PROPN
esrj-65577	100	22	)	)	PUNCT
esrj-65577	100	23	,	,	PUNCT
esrj-65577	100	24	sin(2πt/6	sin(2πt/6	PROPN
esrj-65577	100	25	)	)	PUNCT
esrj-65577	100	26	,	,	PUNCT
esrj-65577	100	27	cos(2πt/12	cos(2πt/12	PROPN
esrj-65577	100	28	)	)	PUNCT
esrj-65577	100	29	and	and	CCONJ
esrj-65577	100	30	sin(2πt/12	sin(2πt/12	PROPN
esrj-65577	100	31	)	)	PUNCT
esrj-65577	100	32	.	.	PUNCT
esrj-65577	101	1	the	the	DET
esrj-65577	101	2	periodogram	periodogram	NOUN
esrj-65577	101	3	of	of	ADP
esrj-65577	101	4	a	a	DET
esrj-65577	101	5	time	time	NOUN
esrj-65577	101	6	series	series	NOUN
esrj-65577	101	7	can	can	AUX
esrj-65577	101	8	be	be	AUX
esrj-65577	101	9	obtained	obtain	VERB
esrj-65577	101	10	using	use	VERB
esrj-65577	101	11	the	the	DET
esrj-65577	101	12	r	r	NOUN
esrj-65577	101	13	-	-	PUNCT
esrj-65577	101	14	function	function	NOUN
esrj-65577	101	15	periodogram	periodogram	NOUN
esrj-65577	101	16	(	(	PUNCT
esrj-65577	101	17	x	x	NOUN
esrj-65577	101	18	,	,	PUNCT
esrj-65577	101	19	method	method	NOUN
esrj-65577	101	20	,	,	PUNCT
esrj-65577	101	21	..	..	PUNCT
esrj-65577	101	22	)	)	PUNCT
esrj-65577	101	23	of	of	ADP
esrj-65577	101	24	the	the	DET
esrj-65577	101	25	library	library	NOUN
esrj-65577	101	26	"	"	PUNCT
esrj-65577	101	27	genecycle	genecycle	PROPN
esrj-65577	101	28	"	"	PUNCT
esrj-65577	101	29	(	(	PUNCT
esrj-65577	101	30	ahdesmaki	ahdesmaki	VERB
esrj-65577	101	31	et	et	PROPN
esrj-65577	101	32	al	al	PROPN
esrj-65577	101	33	.	.	PROPN
esrj-65577	101	34	,	,	PUNCT
esrj-65577	101	35	2012	2012	NUM
esrj-65577	101	36	)	)	PUNCT
esrj-65577	101	37	.	.	PUNCT
esrj-65577	102	1	other	other	ADJ
esrj-65577	102	2	statistical	statistical	ADJ
esrj-65577	102	3	software	software	NOUN
esrj-65577	102	4	can	can	AUX
esrj-65577	102	5	be	be	AUX
esrj-65577	102	6	used	use	VERB
esrj-65577	102	7	to	to	PART
esrj-65577	102	8	estimate	estimate	VERB
esrj-65577	102	9	the	the	DET
esrj-65577	102	10	periodogram	periodogram	NOUN
esrj-65577	102	11	of	of	ADP
esrj-65577	102	12	a	a	DET
esrj-65577	102	13	seasonal	seasonal	ADJ
esrj-65577	102	14	time	time	NOUN
esrj-65577	102	15	series	series	NOUN
esrj-65577	102	16	,	,	PUNCT
esrj-65577	102	17	for	for	ADP
esrj-65577	102	18	example	example	NOUN
esrj-65577	102	19	,	,	PUNCT
esrj-65577	102	20	mathlab	mathlab	NOUN
esrj-65577	102	21	or	or	CCONJ
esrj-65577	102	22	the	the	DET
esrj-65577	102	23	statistical	statistical	ADJ
esrj-65577	102	24	software	software	NOUN
esrj-65577	102	25	excel	excel	NOUN
esrj-65577	102	26	-	-	PUNCT
esrj-65577	102	27	xlstat	xlstat	NOUN
esrj-65577	102	28	.	.	PUNCT
esrj-65577	103	1	figure	figure	VERB
esrj-65577	103	2	3	3	NUM
esrj-65577	103	3	.	.	PUNCT
esrj-65577	103	4	periodogram	periodogram	PROPN
esrj-65577	103	5	of	of	ADP
esrj-65577	103	6	natural	natural	ADJ
esrj-65577	103	7	streamflows	streamflow	NOUN
esrj-65577	103	8	time	time	NOUN
esrj-65577	103	9	series	series	NOUN
esrj-65577	103	10	.	.	PUNCT
esrj-65577	104	1	many	many	ADJ
esrj-65577	104	2	autoregressive	autoregressive	ADJ
esrj-65577	104	3	models	model	NOUN
esrj-65577	104	4	could	could	AUX
esrj-65577	104	5	be	be	AUX
esrj-65577	104	6	assumed	assume	VERB
esrj-65577	104	7	to	to	PART
esrj-65577	104	8	analyze	analyze	VERB
esrj-65577	104	9	this	this	DET
esrj-65577	104	10	data	datum	NOUN
esrj-65577	104	11	set	set	VERB
esrj-65577	104	12	.	.	PUNCT
esrj-65577	105	1	as	as	ADP
esrj-65577	105	2	special	special	ADJ
esrj-65577	105	3	cases	case	NOUN
esrj-65577	105	4	,	,	PUNCT
esrj-65577	105	5	we	we	PRON
esrj-65577	105	6	will	will	AUX
esrj-65577	105	7	assume	assume	VERB
esrj-65577	105	8	,	,	PUNCT
esrj-65577	105	9	in	in	ADP
esrj-65577	105	10	section	section	NOUN
esrj-65577	105	11	4.1	4.1	NUM
esrj-65577	105	12	,	,	PUNCT
esrj-65577	105	13	a	a	DET
esrj-65577	105	14	seasonal	seasonal	ADJ
esrj-65577	105	15	conditional	conditional	ADJ
esrj-65577	105	16	normal	normal	ADJ
esrj-65577	105	17	distribution	distribution	NOUN
esrj-65577	105	18	for	for	ADP
esrj-65577	105	19	the	the	DET
esrj-65577	105	20	data	datum	NOUN
esrj-65577	105	21	and	and	CCONJ
esrj-65577	105	22	,	,	PUNCT
esrj-65577	105	23	in	in	ADP
esrj-65577	105	24	section	section	NOUN
esrj-65577	105	25	4.2	4.2	NUM
esrj-65577	105	26	,	,	PUNCT
esrj-65577	105	27	a	a	DET
esrj-65577	105	28	seasonal	seasonal	ADJ
esrj-65577	105	29	conditional	conditional	ADJ
esrj-65577	105	30	gamma	gamma	NOUN
esrj-65577	105	31	distribution	distribution	NOUN
esrj-65577	105	32	for	for	ADP
esrj-65577	105	33	the	the	DET
esrj-65577	105	34	data	datum	NOUN
esrj-65577	105	35	.	.	PUNCT
esrj-65577	106	1	in	in	ADP
esrj-65577	106	2	order	order	NOUN
esrj-65577	106	3	to	to	PART
esrj-65577	106	4	apply	apply	VERB
esrj-65577	106	5	the	the	DET
esrj-65577	106	6	bayesian	bayesian	NOUN
esrj-65577	106	7	methodology	methodology	NOUN
esrj-65577	106	8	,	,	PUNCT
esrj-65577	106	9	independent	independent	ADJ
esrj-65577	106	10	normal	normal	ADJ
esrj-65577	106	11	prior	prior	ADJ
esrj-65577	106	12	distributions	distribution	NOUN
esrj-65577	106	13	n(0,10k	n(0,10k	NOUN
esrj-65577	106	14	)	)	PUNCT
esrj-65577	106	15	,	,	PUNCT
esrj-65577	106	16	with	with	ADP
esrj-65577	106	17	k	k	PROPN
esrj-65577	106	18	=	=	SYM
esrj-65577	106	19	2	2	NUM
esrj-65577	106	20	,	,	PUNCT
esrj-65577	106	21	are	be	AUX
esrj-65577	106	22	assumed	assume	VERB
esrj-65577	106	23	for	for	ADP
esrj-65577	106	24	the	the	DET
esrj-65577	106	25	regression	regression	NOUN
esrj-65577	106	26	parameters	parameter	NOUN
esrj-65577	106	27	associated	associate	VERB
esrj-65577	106	28	with	with	ADP
esrj-65577	106	29	the	the	DET
esrj-65577	106	30	seasonal	seasonal	ADJ
esrj-65577	106	31	terms	term	NOUN
esrj-65577	106	32	.	.	PUNCT
esrj-65577	107	1	for	for	ADP
esrj-65577	107	2	the	the	DET
esrj-65577	107	3	other	other	ADJ
esrj-65577	107	4	parameters	parameter	NOUN
esrj-65577	107	5	of	of	ADP
esrj-65577	107	6	the	the	DET
esrj-65577	107	7	model	model	NOUN
esrj-65577	107	8	,	,	PUNCT
esrj-65577	107	9	we	we	PRON
esrj-65577	107	10	assume	assume	VERB
esrj-65577	107	11	independent	independent	ADJ
esrj-65577	107	12	normal	normal	ADJ
esrj-65577	107	13	prior	prior	ADJ
esrj-65577	107	14	distributions	distribution	NOUN
esrj-65577	107	15	n(0,10k	n(0,10k	NOUN
esrj-65577	107	16	)	)	PUNCT
esrj-65577	107	17	,	,	PUNCT
esrj-65577	107	18	with	with	ADP
esrj-65577	107	19	k	k	PROPN
esrj-65577	107	20	=	=	SYM
esrj-65577	107	21	5	5	X
esrj-65577	107	22	.	.	PUNCT
esrj-65577	108	1	it	it	PRON
esrj-65577	108	2	is	be	AUX
esrj-65577	108	3	important	important	ADJ
esrj-65577	108	4	,	,	PUNCT
esrj-65577	108	5	to	to	PART
esrj-65577	108	6	point	point	VERB
esrj-65577	108	7	out	out	ADP
esrj-65577	108	8	that	that	SCONJ
esrj-65577	108	9	non	non	ADJ
esrj-65577	108	10	-	-	ADJ
esrj-65577	108	11	informative	informative	ADJ
esrj-65577	108	12	prior	prior	ADV
esrj-65577	108	13	could	could	AUX
esrj-65577	108	14	be	be	AUX
esrj-65577	108	15	used	use	VERB
esrj-65577	108	16	(	(	PUNCT
esrj-65577	108	17	see	see	VERB
esrj-65577	108	18	,	,	PUNCT
esrj-65577	108	19	for	for	ADP
esrj-65577	108	20	example	example	NOUN
esrj-65577	108	21	,	,	PUNCT
esrj-65577	108	22	geman	geman	NOUN
esrj-65577	108	23	,	,	PUNCT
esrj-65577	108	24	2006	2006	NUM
esrj-65577	108	25	)	)	PUNCT
esrj-65577	108	26	,	,	PUNCT
esrj-65577	108	27	but	but	CCONJ
esrj-65577	108	28	in	in	ADP
esrj-65577	108	29	our	our	PRON
esrj-65577	108	30	case	case	NOUN
esrj-65577	108	31	,	,	PUNCT
esrj-65577	108	32	the	the	DET
esrj-65577	108	33	obtained	obtain	VERB
esrj-65577	108	34	results	result	NOUN
esrj-65577	108	35	are	be	AUX
esrj-65577	108	36	very	very	ADV
esrj-65577	108	37	similar	similar	ADJ
esrj-65577	108	38	.	.	PUNCT
esrj-65577	109	1	since	since	SCONJ
esrj-65577	109	2	we	we	PRON
esrj-65577	109	3	are	be	AUX
esrj-65577	109	4	using	use	VERB
esrj-65577	109	5	the	the	DET
esrj-65577	109	6	free	free	ADJ
esrj-65577	109	7	available	available	ADJ
esrj-65577	109	8	software	software	NOUN
esrj-65577	109	9	winbugs	winbug	NOUN
esrj-65577	109	10	to	to	PART
esrj-65577	109	11	simulate	simulate	VERB
esrj-65577	109	12	samples	sample	NOUN
esrj-65577	109	13	for	for	ADP
esrj-65577	109	14	the	the	DET
esrj-65577	109	15	joint	joint	ADJ
esrj-65577	109	16	posterior	posterior	ADJ
esrj-65577	109	17	distribution	distribution	NOUN
esrj-65577	109	18	of	of	ADP
esrj-65577	109	19	interest	interest	NOUN
esrj-65577	109	20	in	in	ADP
esrj-65577	109	21	all	all	DET
esrj-65577	109	22	assumed	assume	VERB
esrj-65577	109	23	models	model	NOUN
esrj-65577	109	24	,	,	PUNCT
esrj-65577	109	25	which	which	PRON
esrj-65577	109	26	only	only	ADV
esrj-65577	109	27	requires	require	VERB
esrj-65577	109	28	the	the	DET
esrj-65577	109	29	introduction	introduction	NOUN
esrj-65577	109	30	of	of	ADP
esrj-65577	109	31	the	the	DET
esrj-65577	109	32	joint	joint	ADJ
esrj-65577	109	33	distribution	distribution	NOUN
esrj-65577	109	34	for	for	ADP
esrj-65577	109	35	the	the	DET
esrj-65577	109	36	data	datum	NOUN
esrj-65577	109	37	and	and	CCONJ
esrj-65577	109	38	the	the	DET
esrj-65577	109	39	prior	prior	ADJ
esrj-65577	109	40	distributions	distribution	NOUN
esrj-65577	109	41	for	for	ADP
esrj-65577	109	42	all	all	DET
esrj-65577	109	43	parameters	parameter	NOUN
esrj-65577	109	44	of	of	ADP
esrj-65577	109	45	the	the	DET
esrj-65577	109	46	model	model	NOUN
esrj-65577	109	47	,	,	PUNCT
esrj-65577	109	48	we	we	PRON
esrj-65577	109	49	will	will	AUX
esrj-65577	109	50	not	not	PART
esrj-65577	109	51	present	present	VERB
esrj-65577	109	52	in	in	ADP
esrj-65577	109	53	this	this	DET
esrj-65577	109	54	paper	paper	NOUN
esrj-65577	109	55	the	the	DET
esrj-65577	109	56	required	require	VERB
esrj-65577	109	57	full	full	ADJ
esrj-65577	109	58	conditional	conditional	ADJ
esrj-65577	109	59	posterior	posterior	ADJ
esrj-65577	109	60	distributions	distribution	NOUN
esrj-65577	109	61	for	for	ADP
esrj-65577	109	62	all	all	DET
esrj-65577	109	63	parameters	parameter	NOUN
esrj-65577	109	64	needed	need	VERB
esrj-65577	109	65	in	in	ADP
esrj-65577	109	66	the	the	DET
esrj-65577	109	67	gibbs	gibbs	PROPN
esrj-65577	109	68	sampling	sampling	NOUN
esrj-65577	109	69	or	or	CCONJ
esrj-65577	109	70	the	the	DET
esrj-65577	109	71	metropolis	metropolis	PROPN
esrj-65577	109	72	-	-	PUNCT
esrj-65577	109	73	hastings	hasting	NOUN
esrj-65577	109	74	algorithms	algorithm	NOUN
esrj-65577	109	75	.	.	PUNCT
esrj-65577	110	1	4.1	4.1	NUM
esrj-65577	110	2	.	.	PUNCT
esrj-65577	110	3	normal	normal	ADJ
esrj-65577	110	4	seasonal	seasonal	ADJ
esrj-65577	110	5	time	time	NOUN
esrj-65577	110	6	series	series	NOUN
esrj-65577	110	7	in	in	ADP
esrj-65577	110	8	this	this	DET
esrj-65577	110	9	section	section	NOUN
esrj-65577	110	10	,	,	PUNCT
esrj-65577	110	11	we	we	PRON
esrj-65577	110	12	present	present	VERB
esrj-65577	110	13	the	the	DET
esrj-65577	110	14	results	result	NOUN
esrj-65577	110	15	of	of	ADP
esrj-65577	110	16	the	the	DET
esrj-65577	110	17	bayesian	bayesian	NOUN
esrj-65577	110	18	analysis	analysis	NOUN
esrj-65577	110	19	for	for	ADP
esrj-65577	110	20	the	the	DET
esrj-65577	110	21	time	time	NOUN
esrj-65577	110	22	series	series	NOUN
esrj-65577	110	23	of	of	ADP
esrj-65577	110	24	monthly	monthly	ADJ
esrj-65577	110	25	averages	average	NOUN
esrj-65577	110	26	of	of	ADP
esrj-65577	110	27	natural	natural	ADJ
esrj-65577	110	28	streamflows	streamflow	NOUN
esrj-65577	110	29	,	,	PUNCT
esrj-65577	110	30	measured	measure	VERB
esrj-65577	110	31	in	in	ADP
esrj-65577	110	32	the	the	DET
esrj-65577	110	33	period	period	NOUN
esrj-65577	110	34	ranging	range	VERB
esrj-65577	110	35	from	from	ADP
esrj-65577	110	36	1931	1931	NUM
esrj-65577	110	37	to	to	ADP
esrj-65577	110	38	2010	2010	NUM
esrj-65577	110	39	,	,	PUNCT
esrj-65577	110	40	considering	consider	VERB
esrj-65577	110	41	the	the	DET
esrj-65577	110	42	dataset	dataset	NOUN
esrj-65577	110	43	related	relate	VERB
esrj-65577	110	44	to	to	ADP
esrj-65577	110	45	a	a	DET
esrj-65577	110	46	hydroelectric	hydroelectric	ADJ
esrj-65577	110	47	dam	dam	NOUN
esrj-65577	110	48	introduced	introduce	VERB
esrj-65577	110	49	in	in	ADP
esrj-65577	110	50	section	section	NOUN
esrj-65577	110	51	1	1	NUM
esrj-65577	110	52	,	,	PUNCT
esrj-65577	110	53	assuming	assume	VERB
esrj-65577	110	54	jointly	jointly	ADV
esrj-65577	110	55	modeling	modeling	NOUN
esrj-65577	110	56	for	for	ADP
esrj-65577	110	57	the	the	DET
esrj-65577	110	58	mean	mean	NOUN
esrj-65577	110	59	and	and	CCONJ
esrj-65577	110	60	variance	variance	NOUN
esrj-65577	110	61	,	,	PUNCT
esrj-65577	110	62	assuming	assume	VERB
esrj-65577	110	63	a	a	DET
esrj-65577	110	64	normal	normal	ADJ
esrj-65577	110	65	model	model	NOUN
esrj-65577	110	66	for	for	ADP
esrj-65577	110	67	the	the	DET
esrj-65577	110	68	data	datum	NOUN
esrj-65577	110	69	.	.	PUNCT
esrj-65577	111	1	from	from	ADP
esrj-65577	111	2	the	the	DET
esrj-65577	111	3	model	model	NOUN
esrj-65577	111	4	given	give	VERB
esrj-65577	111	5	by	by	ADP
esrj-65577	111	6	equations	equation	NOUN
esrj-65577	111	7	(	(	PUNCT
esrj-65577	111	8	6	6	NUM
esrj-65577	111	9	)	)	PUNCT
esrj-65577	111	10	and	and	CCONJ
esrj-65577	111	11	(	(	PUNCT
esrj-65577	111	12	7	7	NUM
esrj-65577	111	13	)	)	PUNCT
esrj-65577	111	14	,	,	PUNCT
esrj-65577	111	15	many	many	ADJ
esrj-65577	111	16	autoregressive	autoregressive	ADJ
esrj-65577	111	17	models	model	NOUN
esrj-65577	111	18	were	be	AUX
esrj-65577	111	19	considered	consider	VERB
esrj-65577	111	20	in	in	ADP
esrj-65577	111	21	the	the	DET
esrj-65577	111	22	analysis	analysis	NOUN
esrj-65577	111	23	of	of	ADP
esrj-65577	111	24	the	the	DET
esrj-65577	111	25	data	datum	NOUN
esrj-65577	111	26	,	,	PUNCT
esrj-65577	111	27	and	and	CCONJ
esrj-65577	111	28	the	the	DET
esrj-65577	111	29	model	model	NOUN
esrj-65577	111	30	with	with	ADP
esrj-65577	111	31	smallest	small	ADJ
esrj-65577	111	32	dic	dic	ADJ
esrj-65577	111	33	(	(	PUNCT
esrj-65577	111	34	deviance	deviance	NOUN
esrj-65577	111	35	information	information	NOUN
esrj-65577	111	36	criterion	criterion	NOUN
esrj-65577	111	37	,	,	PUNCT
esrj-65577	111	38	introduced	introduce	VERB
esrj-65577	111	39	by	by	ADP
esrj-65577	111	40	spiegelhalter	spiegelhalter	NOUN
esrj-65577	111	41	et	et	PROPN
esrj-65577	111	42	al	al	PROPN
esrj-65577	111	43	,	,	PUNCT
esrj-65577	111	44	2002	2002	NUM
esrj-65577	111	45	)	)	PUNCT
esrj-65577	111	46	value	value	NOUN
esrj-65577	111	47	was	be	AUX
esrj-65577	111	48	given	give	VERB
esrj-65577	111	49	by	by	ADP
esrj-65577	111	50	the	the	DET
esrj-65577	111	51	heteroscedastic	heteroscedastic	ADJ
esrj-65577	111	52	normal	normal	ADJ
esrj-65577	111	53	regression	regression	NOUN
esrj-65577	111	54	model	model	NOUN
esrj-65577	111	55	with	with	ADP
esrj-65577	111	56	conditional	conditional	ADJ
esrj-65577	111	57	mean	mean	NOUN
esrj-65577	111	58	and	and	CCONJ
esrj-65577	111	59	variance	variance	NOUN
esrj-65577	111	60	structures	structure	NOUN
esrj-65577	111	61	given	give	VERB
esrj-65577	111	62	respectively	respectively	ADV
esrj-65577	111	63	by	by	ADP
esrj-65577	111	64	,	,	PUNCT
esrj-65577	111	65	samples	sample	NOUN
esrj-65577	111	66	of	of	ADP
esrj-65577	111	67	the	the	DET
esrj-65577	111	68	joint	joint	ADJ
esrj-65577	111	69	posterior	posterior	ADJ
esrj-65577	111	70	distribution	distribution	NOUN
esrj-65577	111	71	of	of	ADP
esrj-65577	111	72	interest	interest	NOUN
esrj-65577	111	73	were	be	AUX
esrj-65577	111	74	simulated	simulate	VERB
esrj-65577	111	75	using	use	VERB
esrj-65577	111	76	standard	standard	ADJ
esrj-65577	111	77	mcmc	mcmc	PROPN
esrj-65577	111	78	(	(	PUNCT
esrj-65577	111	79	markov	markov	PROPN
esrj-65577	111	80	chain	chain	NOUN
esrj-65577	111	81	monte	monte	PROPN
esrj-65577	111	82	carlo	carlo	PROPN
esrj-65577	111	83	)	)	PUNCT
esrj-65577	111	84	methods	method	NOUN
esrj-65577	111	85	and	and	CCONJ
esrj-65577	111	86	the	the	DET
esrj-65577	111	87	free	free	ADJ
esrj-65577	111	88	available	available	ADJ
esrj-65577	111	89	winbugssoftware	winbugssoftware	NOUN
esrj-65577	111	90	(	(	PUNCT
esrj-65577	111	91	spiegelhalter	spiegelhalter	VERB
esrj-65577	111	92	et	et	PROPN
esrj-65577	111	93	al	al	PROPN
esrj-65577	111	94	,	,	PUNCT
esrj-65577	111	95	2003	2003	NUM
esrj-65577	111	96	)	)	PUNCT
esrj-65577	111	97	.	.	PUNCT
esrj-65577	112	1	in	in	ADP
esrj-65577	112	2	each	each	PRON
esrj-65577	112	3	of	of	ADP
esrj-65577	112	4	the	the	DET
esrj-65577	112	5	cases	case	NOUN
esrj-65577	112	6	,	,	PUNCT
esrj-65577	112	7	many	many	ADJ
esrj-65577	112	8	samples	sample	NOUN
esrj-65577	112	9	were	be	AUX
esrj-65577	112	10	generated	generate	VERB
esrj-65577	112	11	starting	start	VERB
esrj-65577	112	12	from	from	ADP
esrj-65577	112	13	different	different	ADJ
esrj-65577	112	14	initial	initial	ADJ
esrj-65577	112	15	values	value	NOUN
esrj-65577	112	16	.	.	PUNCT
esrj-65577	113	1	all	all	PRON
esrj-65577	113	2	of	of	ADP
esrj-65577	113	3	them	they	PRON
esrj-65577	113	4	showed	show	VERB
esrj-65577	113	5	the	the	DET
esrj-65577	113	6	same	same	ADJ
esrj-65577	113	7	behavior	behavior	NOUN
esrj-65577	113	8	,	,	PUNCT
esrj-65577	113	9	after	after	ADP
esrj-65577	113	10	a	a	DET
esrj-65577	113	11	small	small	ADJ
esrj-65577	113	12	burn	burn	NOUN
esrj-65577	113	13	-	-	PUNCT
esrj-65577	113	14	in	in	ADP
esrj-65577	113	15	period	period	NOUN
esrj-65577	113	16	consisting	consist	VERB
esrj-65577	113	17	of	of	ADP
esrj-65577	113	18	3,000	3,000	NUM
esrj-65577	113	19	or	or	CCONJ
esrj-65577	113	20	5,000	5,000	NUM
esrj-65577	113	21	generated	generate	VERB
esrj-65577	113	22	samples	sample	NOUN
esrj-65577	113	23	.	.	PUNCT
esrj-65577	114	1	convergence	convergence	NOUN
esrj-65577	114	2	of	of	ADP
esrj-65577	114	3	the	the	DET
esrj-65577	114	4	simulation	simulation	NOUN
esrj-65577	114	5	algorithm	algorithm	NOUN
esrj-65577	114	6	was	be	AUX
esrj-65577	114	7	observed	observe	VERB
esrj-65577	114	8	from	from	ADP
esrj-65577	114	9	trace	trace	NOUN
esrj-65577	114	10	plots	plot	NOUN
esrj-65577	114	11	of	of	ADP
esrj-65577	114	12	the	the	DET
esrj-65577	114	13	generated	generate	VERB
esrj-65577	114	14	gibbs	gibbs	PROPN
esrj-65577	114	15	samples	sample	NOUN
esrj-65577	114	16	.	.	PUNCT
esrj-65577	115	1	for	for	ADP
esrj-65577	115	2	the	the	DET
esrj-65577	115	3	model	model	NOUN
esrj-65577	115	4	given	give	VERB
esrj-65577	115	5	by	by	ADP
esrj-65577	115	6	equations	equation	NOUN
esrj-65577	115	7	(	(	PUNCT
esrj-65577	115	8	10	10	NUM
esrj-65577	115	9	)	)	PUNCT
esrj-65577	115	10	and	and	CCONJ
esrj-65577	115	11	(	(	PUNCT
esrj-65577	115	12	11	11	NUM
esrj-65577	115	13	)	)	PUNCT
esrj-65577	115	14	,	,	PUNCT
esrj-65577	115	15	the	the	DET
esrj-65577	115	16	value	value	NOUN
esrj-65577	115	17	of	of	ADP
esrj-65577	115	18	the	the	DET
esrj-65577	115	19	logarithm	logarithm	NOUN
esrj-65577	115	20	of	of	ADP
esrj-65577	115	21	the	the	DET
esrj-65577	115	22	likelihood	likelihood	NOUN
esrj-65577	115	23	function	function	NOUN
esrj-65577	115	24	evaluated	evaluate	VERB
esrj-65577	115	25	at	at	ADP
esrj-65577	115	26	the	the	DET
esrj-65577	115	27	obtained	obtain	VERB
esrj-65577	115	28	estimates	estimate	NOUN
esrj-65577	115	29	for	for	ADP
esrj-65577	115	30	the	the	DET
esrj-65577	115	31	parameters	parameter	NOUN
esrj-65577	115	32	of	of	ADP
esrj-65577	115	33	the	the	DET
esrj-65577	115	34	model	model	NOUN
esrj-65577	115	35	was	be	AUX
esrj-65577	115	36	given	give	VERB
esrj-65577	115	37	by	by	ADP
esrj-65577	115	38	−2logl=10479.200	−2logl=10479.200	NOUN
esrj-65577	115	39	and	and	CCONJ
esrj-65577	115	40	the	the	DET
esrj-65577	115	41	obtained	obtain	VERB
esrj-65577	115	42	dic	dic	PROPN
esrj-65577	115	43	value	value	NOUN
esrj-65577	115	44	was	be	AUX
esrj-65577	115	45	dic=10876.500	dic=10876.500	PRON
esrj-65577	115	46	.	.	PUNCT
esrj-65577	116	1	monte	monte	PROPN
esrj-65577	116	2	carlo	carlo	PROPN
esrj-65577	116	3	estimates	estimate	NOUN
esrj-65577	116	4	of	of	ADP
esrj-65577	116	5	the	the	DET
esrj-65577	116	6	posterior	posterior	ADJ
esrj-65577	116	7	means	mean	VERB
esrj-65577	116	8	for	for	ADP
esrj-65577	116	9	each	each	DET
esrj-65577	116	10	parameter	parameter	NOUN
esrj-65577	116	11	based	base	VERB
esrj-65577	116	12	on	on	ADP
esrj-65577	116	13	the	the	DET
esrj-65577	116	14	generated	generate	VERB
esrj-65577	116	15	gibbs	gibbs	PROPN
esrj-65577	116	16	samples	sample	NOUN
esrj-65577	116	17	and	and	CCONJ
esrj-65577	116	18	their	their	PRON
esrj-65577	116	19	respective	respective	ADJ
esrj-65577	116	20	standard	standard	ADJ
esrj-65577	116	21	deviations	deviation	NOUN
esrj-65577	116	22	are	be	AUX
esrj-65577	116	23	given	give	VERB
esrj-65577	116	24	in	in	ADP
esrj-65577	116	25	tables	table	NOUN
esrj-65577	116	26	1	1	NUM
esrj-65577	116	27	and	and	CCONJ
esrj-65577	116	28	2	2	NUM
esrj-65577	116	29	,	,	PUNCT
esrj-65577	116	30	including	include	VERB
esrj-65577	116	31	both	both	CCONJ
esrj-65577	116	32	autoregressive	autoregressive	ADJ
esrj-65577	116	33	and	and	CCONJ
esrj-65577	116	34	seasonal	seasonal	ADJ
esrj-65577	116	35	terms	term	NOUN
esrj-65577	116	36	in	in	ADP
esrj-65577	116	37	the	the	DET
esrj-65577	116	38	conditional	conditional	ADJ
esrj-65577	116	39	mean	mean	NOUN
esrj-65577	116	40	and	and	CCONJ
esrj-65577	116	41	variance	variance	NOUN
esrj-65577	116	42	terms	term	NOUN
esrj-65577	116	43	.	.	PUNCT
esrj-65577	117	1	table	table	NOUN
esrj-65577	117	2	1	1	NUM
esrj-65577	117	3	.	.	X
esrj-65577	117	4	normal	normal	ADJ
esrj-65577	117	5	model	model	NOUN
esrj-65577	117	6	:	:	PUNCT
esrj-65577	117	7	bayesian	bayesian	NOUN
esrj-65577	117	8	estimates	estimate	NOUN
esrj-65577	117	9	for	for	ADP
esrj-65577	117	10	the	the	DET
esrj-65577	117	11	mean	mean	ADJ
esrj-65577	117	12	parameters	parameter	NOUN
esrj-65577	117	13	.	.	PUNCT
esrj-65577	118	1	table	table	NOUN
esrj-65577	118	2	2	2	NUM
esrj-65577	118	3	.	.	PUNCT
esrj-65577	118	4	bayesian	bayesian	NOUN
esrj-65577	118	5	estimates	estimate	NOUN
esrj-65577	118	6	of	of	ADP
esrj-65577	118	7	the	the	DET
esrj-65577	118	8	variance	variance	NOUN
esrj-65577	118	9	parameters	parameter	NOUN
esrj-65577	118	10	.	.	PUNCT
esrj-65577	119	1	87seasonal	87seasonal	ADJ
esrj-65577	119	2	hydrological	hydrological	ADJ
esrj-65577	119	3	and	and	CCONJ
esrj-65577	119	4	meteorological	meteorological	ADJ
esrj-65577	119	5	time	time	NOUN
esrj-65577	119	6	series	series	PROPN
esrj-65577	119	7	figure	figure	NOUN
esrj-65577	119	8	5	5	NUM
esrj-65577	119	9	.	.	X
esrj-65577	119	10	normal	normal	ADJ
esrj-65577	119	11	fitted	fit	VERB
esrj-65577	119	12	squared	square	VERB
esrj-65577	119	13	root	root	NOUN
esrj-65577	119	14	of	of	ADP
esrj-65577	119	15	the	the	DET
esrj-65577	119	16	expected	expect	VERB
esrj-65577	119	17	volatility	volatility	NOUN
esrj-65577	119	18	.	.	PUNCT
esrj-65577	120	1	figure	figure	VERB
esrj-65577	120	2	6	6	NUM
esrj-65577	120	3	.	.	PUNCT
esrj-65577	120	4	monthly	monthly	ADJ
esrj-65577	120	5	averages	average	NOUN
esrj-65577	120	6	of	of	ADP
esrj-65577	120	7	natural	natural	ADJ
esrj-65577	120	8	streamflow	streamflow	NOUN
esrj-65577	120	9	.	.	PUNCT
esrj-65577	121	1	figure	figure	NOUN
esrj-65577	121	2	4	4	NUM
esrj-65577	121	3	.	.	PUNCT
esrj-65577	121	4	monthly	monthly	ADJ
esrj-65577	121	5	averages	average	NOUN
esrj-65577	121	6	of	of	ADP
esrj-65577	121	7	natural	natural	ADJ
esrj-65577	121	8	streamflow	streamflow	NOUN
esrj-65577	121	9	and	and	CCONJ
esrj-65577	121	10	normal	normal	ADJ
esrj-65577	121	11	fitted	fit	VERB
esrj-65577	121	12	mean	mean	NOUN
esrj-65577	121	13	estimates	estimate	NOUN
esrj-65577	121	14	.	.	PUNCT
esrj-65577	122	1	as	as	ADP
esrj-65577	122	2	an	an	DET
esrj-65577	122	3	illustration	illustration	NOUN
esrj-65577	122	4	of	of	ADP
esrj-65577	122	5	the	the	DET
esrj-65577	122	6	performance	performance	NOUN
esrj-65577	122	7	of	of	ADP
esrj-65577	122	8	the	the	DET
esrj-65577	122	9	proposed	propose	VERB
esrj-65577	122	10	model	model	NOUN
esrj-65577	122	11	,	,	PUNCT
esrj-65577	122	12	figure	figure	VERB
esrj-65577	122	13	4	4	NUM
esrj-65577	122	14	shows	show	VERB
esrj-65577	122	15	the	the	DET
esrj-65577	122	16	agreement	agreement	NOUN
esrj-65577	122	17	between	between	ADP
esrj-65577	122	18	monthly	monthly	ADJ
esrj-65577	122	19	averages	average	NOUN
esrj-65577	122	20	of	of	ADP
esrj-65577	122	21	natural	natural	ADJ
esrj-65577	122	22	streamflows	streamflow	NOUN
esrj-65577	122	23	and	and	CCONJ
esrj-65577	122	24	the	the	DET
esrj-65577	122	25	fitted	fit	VERB
esrj-65577	122	26	mean	mean	ADJ
esrj-65577	122	27	estimate	estimate	NOUN
esrj-65577	122	28	.	.	PUNCT
esrj-65577	123	1	at	at	ADP
esrj-65577	123	2	the	the	DET
esrj-65577	123	3	same	same	ADJ
esrj-65577	123	4	time	time	NOUN
esrj-65577	123	5	,	,	PUNCT
esrj-65577	123	6	figure	figure	NOUN
esrj-65577	123	7	5	5	NUM
esrj-65577	123	8	,	,	PUNCT
esrj-65577	123	9	depicting	depict	VERB
esrj-65577	123	10	of	of	ADP
esrj-65577	123	11	the	the	DET
esrj-65577	123	12	fitted	fit	VERB
esrj-65577	123	13	squared	square	VERB
esrj-65577	123	14	root	root	NOUN
esrj-65577	123	15	of	of	ADP
esrj-65577	123	16	the	the	DET
esrj-65577	123	17	expected	expect	VERB
esrj-65577	123	18	volatility	volatility	NOUN
esrj-65577	123	19	shows	show	VERB
esrj-65577	123	20	periods	period	NOUN
esrj-65577	123	21	of	of	ADP
esrj-65577	123	22	high	high	ADJ
esrj-65577	123	23	volatility	volatility	NOUN
esrj-65577	123	24	around	around	ADP
esrj-65577	123	25	of	of	ADP
esrj-65577	123	26	the	the	DET
esrj-65577	123	27	months	month	NOUN
esrj-65577	123	28	200	200	NUM
esrj-65577	123	29	,	,	PUNCT
esrj-65577	123	30	400	400	NUM
esrj-65577	123	31	,	,	PUNCT
esrj-65577	123	32	600	600	NUM
esrj-65577	123	33	and	and	CCONJ
esrj-65577	123	34	800	800	NUM
esrj-65577	123	35	,	,	PUNCT
esrj-65577	123	36	as	as	SCONJ
esrj-65577	123	37	observed	observe	VERB
esrj-65577	123	38	in	in	ADP
esrj-65577	123	39	the	the	DET
esrj-65577	123	40	data	data	NOUN
esrj-65577	123	41	behavior	behavior	NOUN
esrj-65577	123	42	.	.	PUNCT
esrj-65577	124	1	4.2	4.2	NUM
esrj-65577	124	2	gamma	gamma	PROPN
esrj-65577	124	3	seasonal	seasonal	ADJ
esrj-65577	124	4	time	time	NOUN
esrj-65577	124	5	series	series	NOUN
esrj-65577	124	6	in	in	ADP
esrj-65577	124	7	this	this	DET
esrj-65577	124	8	section	section	NOUN
esrj-65577	124	9	we	we	PRON
esrj-65577	124	10	present	present	VERB
esrj-65577	124	11	the	the	DET
esrj-65577	124	12	results	result	NOUN
esrj-65577	124	13	of	of	ADP
esrj-65577	124	14	the	the	DET
esrj-65577	124	15	bayesian	bayesian	NOUN
esrj-65577	124	16	analysis	analysis	NOUN
esrj-65577	124	17	for	for	ADP
esrj-65577	124	18	the	the	DET
esrj-65577	124	19	time	time	NOUN
esrj-65577	124	20	series	series	NOUN
esrj-65577	124	21	for	for	ADP
esrj-65577	124	22	monthly	monthly	ADJ
esrj-65577	124	23	averages	average	NOUN
esrj-65577	124	24	of	of	ADP
esrj-65577	124	25	natural	natural	ADJ
esrj-65577	124	26	streamflows	streamflow	NOUN
esrj-65577	124	27	,	,	PUNCT
esrj-65577	124	28	measured	measure	VERB
esrj-65577	124	29	in	in	ADP
esrj-65577	124	30	the	the	DET
esrj-65577	124	31	period	period	NOUN
esrj-65577	124	32	1931	1931	NUM
esrj-65577	124	33	to	to	ADP
esrj-65577	124	34	2010	2010	NUM
esrj-65577	124	35	,	,	PUNCT
esrj-65577	124	36	in	in	ADP
esrj-65577	124	37	furnas	furnas	PROPN
esrj-65577	124	38	hydroelectric	hydroelectric	PROPN
esrj-65577	124	39	dam	dam	PROPN
esrj-65577	124	40	,	,	PUNCT
esrj-65577	124	41	assuming	assume	VERB
esrj-65577	124	42	joint	joint	ADJ
esrj-65577	124	43	modeling	modeling	NOUN
esrj-65577	124	44	for	for	ADP
esrj-65577	124	45	the	the	DET
esrj-65577	124	46	mean	mean	NOUN
esrj-65577	124	47	and	and	CCONJ
esrj-65577	124	48	variance	variance	NOUN
esrj-65577	124	49	autoregressive	autoregressive	ADJ
esrj-65577	124	50	gamma	gamma	NOUN
esrj-65577	124	51	models	model	NOUN
esrj-65577	124	52	,	,	PUNCT
esrj-65577	124	53	that	that	ADV
esrj-65577	124	54	is	is	ADV
esrj-65577	124	55	,	,	PUNCT
esrj-65577	124	56	we	we	PRON
esrj-65577	124	57	assume	assume	VERB
esrj-65577	124	58	that	that	SCONJ
esrj-65577	124	59	the	the	DET
esrj-65577	124	60	observations	observation	NOUN
esrj-65577	124	61	of	of	ADP
esrj-65577	124	62	the	the	DET
esrj-65577	124	63	interest	interest	NOUN
esrj-65577	124	64	are	be	AUX
esrj-65577	124	65	generated	generate	VERB
esrj-65577	124	66	from	from	ADP
esrj-65577	124	67	a	a	DET
esrj-65577	124	68	conditional	conditional	ADJ
esrj-65577	124	69	gamma	gamma	NOUN
esrj-65577	124	70	density	density	NOUN
esrj-65577	124	71	function	function	NOUN
esrj-65577	124	72	given	give	VERB
esrj-65577	124	73	by	by	ADP
esrj-65577	124	74	f	f	PROPN
esrj-65577	124	75	(	(	PUNCT
esrj-65577	124	76	yt	yt	PROPN
esrj-65577	124	77	|ht-1	|ht-1	PROPN
esrj-65577	124	78	)	)	PUNCT
esrj-65577	124	79	,	,	PUNCT
esrj-65577	124	80	where	where	SCONJ
esrj-65577	124	81	ht-1	ht-1	VERB
esrj-65577	124	82	)	)	PUNCT
esrj-65577	124	83	is	be	AUX
esrj-65577	124	84	the	the	DET
esrj-65577	124	85	information	information	NOUN
esrj-65577	124	86	up	up	ADP
esrj-65577	124	87	to	to	ADP
esrj-65577	124	88	time	time	NOUN
esrj-65577	124	89	t	t	PROPN
esrj-65577	124	90	−	−	PROPN
esrj-65577	124	91	1	1	NUM
esrj-65577	124	92	and	and	CCONJ
esrj-65577	124	93	yt	yt	PROPN
esrj-65577	124	94	has	have	VERB
esrj-65577	124	95	conditional	conditional	ADJ
esrj-65577	124	96	mean	mean	NOUN
esrj-65577	124	97	and	and	CCONJ
esrj-65577	124	98	conditional	conditional	ADJ
esrj-65577	124	99	variance	variance	NOUN
esrj-65577	124	100	given	give	VERB
esrj-65577	124	101	respectively	respectively	ADV
esrj-65577	124	102	by	by	ADP
esrj-65577	124	103	µt	µt	PROPN
esrj-65577	124	104	=	=	PROPN
esrj-65577	124	105	e(yt	e(yt	PROPN
esrj-65577	124	106	|	|	ADV
esrj-65577	124	107	ht-1	ht-1	X
esrj-65577	124	108	)	)	PUNCT
esrj-65577	124	109	and	and	CCONJ
esrj-65577	124	110	σt	σt	ADP
esrj-65577	124	111	2	2	NUM
esrj-65577	124	112	=	=	NOUN
esrj-65577	124	113	var(yt	var(yt	NOUN
esrj-65577	124	114	|	|	ADV
esrj-65577	124	115	ht-1	ht-1	NOUN
esrj-65577	124	116	)	)	PUNCT
esrj-65577	124	117	,	,	PUNCT
esrj-65577	124	118	and	and	CCONJ
esrj-65577	124	119	defined	define	VERB
esrj-65577	124	120	by	by	ADP
esrj-65577	124	121	(	(	PUNCT
esrj-65577	124	122	10	10	NUM
esrj-65577	124	123	)	)	PUNCT
esrj-65577	124	124	and	and	CCONJ
esrj-65577	124	125	(	(	PUNCT
esrj-65577	124	126	11	11	NUM
esrj-65577	124	127	)	)	PUNCT
esrj-65577	124	128	.	.	PUNCT
esrj-65577	125	1	for	for	ADP
esrj-65577	125	2	this	this	DET
esrj-65577	125	3	model	model	NOUN
esrj-65577	125	4	,	,	PUNCT
esrj-65577	125	5	the	the	DET
esrj-65577	125	6	logarithm	logarithm	NOUN
esrj-65577	125	7	of	of	ADP
esrj-65577	125	8	the	the	DET
esrj-65577	125	9	likelihood	likelihood	NOUN
esrj-65577	125	10	function	function	NOUN
esrj-65577	125	11	evaluated	evaluate	VERB
esrj-65577	125	12	at	at	ADP
esrj-65577	125	13	the	the	DET
esrj-65577	125	14	estimates	estimate	NOUN
esrj-65577	125	15	for	for	ADP
esrj-65577	125	16	the	the	DET
esrj-65577	125	17	parameters	parameter	NOUN
esrj-65577	125	18	of	of	ADP
esrj-65577	125	19	interest	interest	NOUN
esrj-65577	125	20	is	be	AUX
esrj-65577	125	21	given	give	VERB
esrj-65577	125	22	by	by	ADP
esrj-65577	125	23	−2logl=10649	−2logl=10649	NOUN
esrj-65577	125	24	and	and	CCONJ
esrj-65577	125	25	the	the	DET
esrj-65577	125	26	dic	dic	ADJ
esrj-65577	125	27	value	value	NOUN
esrj-65577	125	28	is	be	AUX
esrj-65577	125	29	given	give	VERB
esrj-65577	125	30	by	by	ADP
esrj-65577	125	31	10862.300	10862.300	NUM
esrj-65577	125	32	.	.	PUNCT
esrj-65577	125	33	using	use	VERB
esrj-65577	125	34	the	the	DET
esrj-65577	125	35	dic	dic	ADJ
esrj-65577	125	36	criterion	criterion	NOUN
esrj-65577	125	37	to	to	PART
esrj-65577	125	38	discriminate	discriminate	VERB
esrj-65577	125	39	the	the	DET
esrj-65577	125	40	two	two	NUM
esrj-65577	125	41	models	model	NOUN
esrj-65577	125	42	(	(	PUNCT
esrj-65577	125	43	normal	normal	ADJ
esrj-65577	125	44	seasonal	seasonal	ADJ
esrj-65577	125	45	time	time	NOUN
esrj-65577	125	46	series	series	NOUN
esrj-65577	125	47	and	and	CCONJ
esrj-65577	125	48	gamma	gamma	PROPN
esrj-65577	125	49	seasonal	seasonal	ADJ
esrj-65577	125	50	time	time	NOUN
esrj-65577	125	51	series	series	PROPN
esrj-65577	125	52	)	)	PUNCT
esrj-65577	125	53	,	,	PUNCT
esrj-65577	125	54	we	we	PRON
esrj-65577	125	55	observe	observe	VERB
esrj-65577	125	56	better	well	ADJ
esrj-65577	125	57	fit	fit	NOUN
esrj-65577	125	58	of	of	ADP
esrj-65577	125	59	the	the	DET
esrj-65577	125	60	data	datum	NOUN
esrj-65577	125	61	for	for	ADP
esrj-65577	125	62	the	the	DET
esrj-65577	125	63	gamma	gamma	PROPN
esrj-65577	125	64	seasonal	seasonal	ADJ
esrj-65577	125	65	time	time	PROPN
esrj-65577	125	66	series	series	PROPN
esrj-65577	125	67	model	model	PROPN
esrj-65577	125	68	,	,	PUNCT
esrj-65577	125	69	since	since	SCONJ
esrj-65577	125	70	we	we	PRON
esrj-65577	125	71	have	have	VERB
esrj-65577	125	72	smaller	small	ADJ
esrj-65577	125	73	dic	dic	ADJ
esrj-65577	125	74	value	value	NOUN
esrj-65577	125	75	for	for	ADP
esrj-65577	125	76	this	this	DET
esrj-65577	125	77	model	model	NOUN
esrj-65577	125	78	.	.	PUNCT
esrj-65577	126	1	the	the	DET
esrj-65577	126	2	bayesian	bayesian	NOUN
esrj-65577	126	3	estimates	estimate	NOUN
esrj-65577	126	4	of	of	ADP
esrj-65577	126	5	the	the	DET
esrj-65577	126	6	posterior	posterior	ADJ
esrj-65577	126	7	means	mean	NOUN
esrj-65577	126	8	for	for	ADP
esrj-65577	126	9	the	the	DET
esrj-65577	126	10	parameters	parameter	NOUN
esrj-65577	126	11	together	together	ADV
esrj-65577	126	12	with	with	ADP
esrj-65577	126	13	the	the	DET
esrj-65577	126	14	corresponding	corresponding	ADJ
esrj-65577	126	15	standard	standard	ADJ
esrj-65577	126	16	deviations	deviation	NOUN
esrj-65577	126	17	are	be	AUX
esrj-65577	126	18	given	give	VERB
esrj-65577	126	19	in	in	ADP
esrj-65577	126	20	tables	table	NOUN
esrj-65577	126	21	3	3	NUM
esrj-65577	126	22	and	and	CCONJ
esrj-65577	126	23	4	4	NUM
esrj-65577	126	24	.	.	NOUN
esrj-65577	126	25	table	table	NOUN
esrj-65577	126	26	3	3	NUM
esrj-65577	126	27	.	.	PUNCT
esrj-65577	126	28	gamma	gamma	PROPN
esrj-65577	126	29	model	model	PROPN
esrj-65577	126	30	:	:	PUNCT
esrj-65577	126	31	bayesian	bayesian	NOUN
esrj-65577	126	32	estimates	estimate	NOUN
esrj-65577	126	33	for	for	ADP
esrj-65577	126	34	the	the	DET
esrj-65577	126	35	mean	mean	ADJ
esrj-65577	126	36	parameters	parameter	NOUN
esrj-65577	126	37	.	.	PUNCT
esrj-65577	127	1	table	table	NOUN
esrj-65577	127	2	4	4	NUM
esrj-65577	127	3	.	.	PUNCT
esrj-65577	127	4	gamma	gamma	PROPN
esrj-65577	127	5	model	model	PROPN
esrj-65577	127	6	:	:	PUNCT
esrj-65577	127	7	bayesian	bayesian	NOUN
esrj-65577	127	8	estimates	estimate	NOUN
esrj-65577	127	9	for	for	ADP
esrj-65577	127	10	the	the	DET
esrj-65577	127	11	variance	variance	NOUN
esrj-65577	127	12	parameters	parameter	NOUN
esrj-65577	127	13	.	.	PUNCT
esrj-65577	128	1	although	although	SCONJ
esrj-65577	128	2	the	the	DET
esrj-65577	128	3	mean	mean	ADJ
esrj-65577	128	4	parameter	parameter	NOUN
esrj-65577	128	5	estimates	estimate	NOUN
esrj-65577	128	6	given	give	VERB
esrj-65577	128	7	in	in	ADP
esrj-65577	128	8	tables	table	NOUN
esrj-65577	128	9	1	1	NUM
esrj-65577	128	10	and	and	CCONJ
esrj-65577	128	11	3	3	NUM
esrj-65577	128	12	,	,	PUNCT
esrj-65577	128	13	and	and	CCONJ
esrj-65577	128	14	variance	variance	NOUN
esrj-65577	128	15	parameter	parameter	NOUN
esrj-65577	128	16	estimates	estimate	NOUN
esrj-65577	128	17	given	give	VERB
esrj-65577	128	18	in	in	ADP
esrj-65577	128	19	tables	table	NOUN
esrj-65577	128	20	2	2	NUM
esrj-65577	128	21	and	and	CCONJ
esrj-65577	128	22	4	4	NUM
esrj-65577	128	23	,	,	PUNCT
esrj-65577	128	24	show	show	VERB
esrj-65577	128	25	some	some	DET
esrj-65577	128	26	agreement	agreement	NOUN
esrj-65577	128	27	between	between	ADP
esrj-65577	128	28	conditional	conditional	ADJ
esrj-65577	128	29	normal	normal	ADJ
esrj-65577	128	30	and	and	CCONJ
esrj-65577	128	31	conditional	conditional	ADJ
esrj-65577	128	32	gamma	gamma	NOUN
esrj-65577	128	33	regression	regression	PROPN
esrj-65577	128	34	parameter	parameter	NOUN
esrj-65577	128	35	estimates	estimate	NOUN
esrj-65577	128	36	,	,	PUNCT
esrj-65577	128	37	the	the	DET
esrj-65577	128	38	dic	dic	ADJ
esrj-65577	128	39	value	value	NOUN
esrj-65577	128	40	of	of	ADP
esrj-65577	128	41	the	the	DET
esrj-65577	128	42	conditional	conditional	ADJ
esrj-65577	128	43	gamma	gamma	NOUN
esrj-65577	128	44	model	model	NOUN
esrj-65577	128	45	is	be	AUX
esrj-65577	128	46	smaller	small	ADJ
esrj-65577	128	47	than	than	ADP
esrj-65577	128	48	that	that	PRON
esrj-65577	128	49	of	of	ADP
esrj-65577	128	50	the	the	DET
esrj-65577	128	51	conditional	conditional	ADJ
esrj-65577	128	52	normal	normal	ADJ
esrj-65577	128	53	heteroscedastic	heteroscedastic	ADJ
esrj-65577	128	54	models	model	NOUN
esrj-65577	128	55	,	,	PUNCT
esrj-65577	128	56	showing	show	VERB
esrj-65577	128	57	that	that	SCONJ
esrj-65577	128	58	the	the	DET
esrj-65577	128	59	class	class	NOUN
esrj-65577	128	60	of	of	ADP
esrj-65577	128	61	gamma	gamma	NOUN
esrj-65577	128	62	models	model	NOUN
esrj-65577	128	63	is	be	AUX
esrj-65577	128	64	better	well	ADJ
esrj-65577	128	65	to	to	PART
esrj-65577	128	66	fit	fit	VERB
esrj-65577	128	67	the	the	DET
esrj-65577	128	68	monthly	monthly	ADJ
esrj-65577	128	69	averages	average	NOUN
esrj-65577	128	70	of	of	ADP
esrj-65577	128	71	natural	natural	ADJ
esrj-65577	128	72	streamflow	streamflow	NOUN
esrj-65577	128	73	data	datum	NOUN
esrj-65577	128	74	.	.	PUNCT
esrj-65577	129	1	in	in	ADP
esrj-65577	129	2	order	order	NOUN
esrj-65577	129	3	to	to	PART
esrj-65577	129	4	determine	determine	VERB
esrj-65577	129	5	the	the	DET
esrj-65577	129	6	forecasting	forecasting	NOUN
esrj-65577	129	7	performance	performance	NOUN
esrj-65577	129	8	of	of	ADP
esrj-65577	129	9	the	the	DET
esrj-65577	129	10	proposed	propose	VERB
esrj-65577	129	11	gamma	gamma	PROPN
esrj-65577	129	12	seasonal	seasonal	PROPN
esrj-65577	129	13	model	model	NOUN
esrj-65577	129	14	,	,	PUNCT
esrj-65577	129	15	we	we	PRON
esrj-65577	129	16	fit	fit	VERB
esrj-65577	129	17	this	this	DET
esrj-65577	129	18	model	model	NOUN
esrj-65577	129	19	to	to	ADP
esrj-65577	129	20	the	the	DET
esrj-65577	129	21	first	first	ADJ
esrj-65577	129	22	910	910	NUM
esrj-65577	129	23	observed	observed	ADJ
esrj-65577	129	24	values	value	NOUN
esrj-65577	129	25	of	of	ADP
esrj-65577	129	26	the	the	DET
esrj-65577	129	27	furnas	furnas	PROPN
esrj-65577	129	28	dam	dam	PROPN
esrj-65577	129	29	hydrological	hydrological	ADJ
esrj-65577	129	30	time	time	NOUN
esrj-65577	129	31	series	series	PROPN
esrj-65577	129	32	,	,	PUNCT
esrj-65577	129	33	in	in	ADP
esrj-65577	129	34	order	order	NOUN
esrj-65577	129	35	to	to	PART
esrj-65577	129	36	predict	predict	VERB
esrj-65577	129	37	the	the	DET
esrj-65577	129	38	temporal	temporal	ADJ
esrj-65577	129	39	behavior	behavior	NOUN
esrj-65577	129	40	over	over	ADP
esrj-65577	129	41	the	the	DET
esrj-65577	129	42	50	50	NUM
esrj-65577	129	43	last	last	ADJ
esrj-65577	129	44	months	month	NOUN
esrj-65577	129	45	.	.	PUNCT
esrj-65577	130	1	the	the	DET
esrj-65577	130	2	parameter	parameter	NOUN
esrj-65577	130	3	estimates	estimate	NOUN
esrj-65577	130	4	agree	agree	VERB
esrj-65577	130	5	with	with	ADP
esrj-65577	130	6	those	those	PRON
esrj-65577	130	7	reported	report	VERB
esrj-65577	130	8	in	in	ADP
esrj-65577	130	9	tables	table	NOUN
esrj-65577	130	10	3	3	NUM
esrj-65577	130	11	and	and	CCONJ
esrj-65577	130	12	4	4	NUM
esrj-65577	130	13	.	.	X
esrj-65577	130	14	figure	figure	VERB
esrj-65577	130	15	6	6	NUM
esrj-65577	130	16	shows	show	VERB
esrj-65577	130	17	that	that	SCONJ
esrj-65577	130	18	this	this	DET
esrj-65577	130	19	model	model	NOUN
esrj-65577	130	20	has	have	VERB
esrj-65577	130	21	good	good	ADJ
esrj-65577	130	22	performance	performance	NOUN
esrj-65577	130	23	in	in	ADP
esrj-65577	130	24	predicting	predict	VERB
esrj-65577	130	25	monthly	monthly	ADJ
esrj-65577	130	26	averages	average	NOUN
esrj-65577	130	27	of	of	ADP
esrj-65577	130	28	natural	natural	ADJ
esrj-65577	130	29	streamflows	streamflow	NOUN
esrj-65577	130	30	.	.	PUNCT
esrj-65577	131	1	this	this	DET
esrj-65577	131	2	figure	figure	NOUN
esrj-65577	131	3	shows	show	VERB
esrj-65577	131	4	the	the	DET
esrj-65577	131	5	90	90	NUM
esrj-65577	131	6	%	%	NOUN
esrj-65577	131	7	prediction	prediction	NOUN
esrj-65577	131	8	interval	interval	NOUN
esrj-65577	131	9	for	for	ADP
esrj-65577	131	10	the	the	DET
esrj-65577	131	11	variable	variable	NOUN
esrj-65577	131	12	of	of	ADP
esrj-65577	131	13	interest	interest	NOUN
esrj-65577	131	14	in	in	ADP
esrj-65577	131	15	these	these	DET
esrj-65577	131	16	last	last	ADJ
esrj-65577	131	17	weeks	week	NOUN
esrj-65577	131	18	in	in	ADP
esrj-65577	131	19	dashed	dash	VERB
esrj-65577	131	20	lines	line	NOUN
esrj-65577	131	21	,	,	PUNCT
esrj-65577	131	22	and	and	CCONJ
esrj-65577	131	23	the	the	DET
esrj-65577	131	24	observed	observed	ADJ
esrj-65577	131	25	values	value	NOUN
esrj-65577	131	26	of	of	ADP
esrj-65577	131	27	natural	natural	ADJ
esrj-65577	131	28	streamflows	streamflow	NOUN
esrj-65577	131	29	in	in	ADP
esrj-65577	131	30	black	black	ADJ
esrj-65577	131	31	points	point	NOUN
esrj-65577	131	32	.	.	PUNCT
esrj-65577	132	1	5	5	X
esrj-65577	132	2	.	.	X
esrj-65577	132	3	beta	beta	ADJ
esrj-65577	132	4	mean	mean	NOUN
esrj-65577	132	5	and	and	CCONJ
esrj-65577	132	6	variance	variance	NOUN
esrj-65577	132	7	seasonal	seasonal	ADJ
esrj-65577	132	8	models	model	NOUN
esrj-65577	132	9	applied	apply	VERB
esrj-65577	132	10	to	to	ADP
esrj-65577	132	11	air	air	NOUN
esrj-65577	132	12	humidity	humidity	PROPN
esrj-65577	132	13	time	time	NOUN
esrj-65577	132	14	series	series	NOUN
esrj-65577	132	15	in	in	ADP
esrj-65577	132	16	this	this	DET
esrj-65577	132	17	section	section	NOUN
esrj-65577	132	18	it	it	PRON
esrj-65577	132	19	is	be	AUX
esrj-65577	132	20	assumed	assume	VERB
esrj-65577	132	21	that	that	SCONJ
esrj-65577	132	22	the	the	DET
esrj-65577	132	23	time	time	NOUN
esrj-65577	132	24	series	series	PROPN
esrj-65577	132	25	data	datum	NOUN
esrj-65577	132	26	are	be	AUX
esrj-65577	132	27	generated	generate	VERB
esrj-65577	132	28	from	from	ADP
esrj-65577	132	29	a	a	DET
esrj-65577	132	30	beta	beta	ADJ
esrj-65577	132	31	distribution	distribution	NOUN
esrj-65577	132	32	,	,	PUNCT
esrj-65577	132	33	b(pi	b(pi	X
esrj-65577	132	34	,	,	PUNCT
esrj-65577	132	35	qi	qi	PROPN
esrj-65577	132	36	)	)	PUNCT
esrj-65577	132	37	,	,	PUNCT
esrj-65577	132	38	with	with	ADP
esrj-65577	132	39	conditional	conditional	ADJ
esrj-65577	132	40	mean	mean	NOUN
esrj-65577	132	41	and	and	CCONJ
esrj-65577	132	42	variance	variance	NOUN
esrj-65577	132	43	given	give	VERB
esrj-65577	132	44	,	,	PUNCT
esrj-65577	132	45	respectively	respectively	ADV
esrj-65577	132	46	,	,	PUNCT
esrj-65577	132	47	by	by	ADP
esrj-65577	132	48	(	(	PUNCT
esrj-65577	132	49	6	6	NUM
esrj-65577	132	50	)	)	PUNCT
esrj-65577	132	51	and	and	CCONJ
esrj-65577	132	52	(	(	PUNCT
esrj-65577	132	53	7	7	NUM
esrj-65577	132	54	)	)	PUNCT
esrj-65577	132	55	.	.	PUNCT
esrj-65577	133	1	to	to	PART
esrj-65577	133	2	illustrate	illustrate	VERB
esrj-65577	133	3	the	the	DET
esrj-65577	133	4	application	application	NOUN
esrj-65577	133	5	of	of	ADP
esrj-65577	133	6	the	the	DET
esrj-65577	133	7	proposed	propose	VERB
esrj-65577	133	8	model	model	NOUN
esrj-65577	133	9	to	to	PART
esrj-65577	133	10	be	be	AUX
esrj-65577	133	11	fitted	fit	VERB
esrj-65577	133	12	by	by	ADP
esrj-65577	133	13	the	the	DET
esrj-65577	133	14	data	datum	NOUN
esrj-65577	133	15	set	set	NOUN
esrj-65577	133	16	,	,	PUNCT
esrj-65577	133	17	we	we	PRON
esrj-65577	133	18	consider	consider	VERB
esrj-65577	133	19	the	the	DET
esrj-65577	133	20	time	time	NOUN
esrj-65577	133	21	series	series	NOUN
esrj-65577	133	22	of	of	ADP
esrj-65577	133	23	weekly	weekly	ADJ
esrj-65577	133	24	averages	average	NOUN
esrj-65577	133	25	air	air	NOUN
esrj-65577	133	26	humidity	humidity	NOUN
esrj-65577	133	27	,	,	PUNCT
esrj-65577	133	28	measured	measure	VERB
esrj-65577	133	29	in	in	ADP
esrj-65577	133	30	rio	rio	PROPN
esrj-65577	133	31	claro	claro	PROPN
esrj-65577	133	32	city	city	PROPN
esrj-65577	133	33	,	,	PUNCT
esrj-65577	133	34	located	locate	VERB
esrj-65577	133	35	in	in	ADP
esrj-65577	133	36	southeastern	southeastern	NOUN
esrj-65577	133	37	of	of	ADP
esrj-65577	133	38	brazil	brazil	PROPN
esrj-65577	133	39	,	,	PUNCT
esrj-65577	133	40	from	from	ADP
esrj-65577	133	41	18/10/2002	18/10/2002	NUM
esrj-65577	133	42	to	to	ADP
esrj-65577	133	43	08/10/2008	08/10/2008	PROPN
esrj-65577	133	44	.	.	PUNCT
esrj-65577	134	1	this	this	DET
esrj-65577	134	2	time	time	NOUN
esrj-65577	134	3	series	series	NOUN
esrj-65577	134	4	,	,	PUNCT
esrj-65577	134	5	introduced	introduce	VERB
esrj-65577	134	6	in	in	ADP
esrj-65577	134	7	section	section	NOUN
esrj-65577	134	8	1	1	NUM
esrj-65577	134	9	,	,	PUNCT
esrj-65577	134	10	is	be	AUX
esrj-65577	134	11	shown	show	VERB
esrj-65577	134	12	in	in	ADP
esrj-65577	134	13	figure	figure	NOUN
esrj-65577	134	14	2	2	NUM
esrj-65577	134	15	.	.	PUNCT
esrj-65577	135	1	as	as	ADP
esrj-65577	135	2	in	in	ADP
esrj-65577	135	3	section	section	NOUN
esrj-65577	135	4	4	4	NUM
esrj-65577	135	5	,	,	PUNCT
esrj-65577	135	6	the	the	DET
esrj-65577	135	7	first	first	ADJ
esrj-65577	135	8	step	step	NOUN
esrj-65577	135	9	in	in	ADP
esrj-65577	135	10	the	the	DET
esrj-65577	135	11	proposed	propose	VERB
esrj-65577	135	12	analysis	analysis	NOUN
esrj-65577	135	13	is	be	AUX
esrj-65577	135	14	to	to	PART
esrj-65577	135	15	determine	determine	VERB
esrj-65577	135	16	the	the	DET
esrj-65577	135	17	period	period	NOUN
esrj-65577	135	18	of	of	ADP
esrj-65577	135	19	harmonics	harmonic	NOUN
esrj-65577	135	20	of	of	ADP
esrj-65577	135	21	higher	high	ADJ
esrj-65577	135	22	intensity	intensity	NOUN
esrj-65577	135	23	in	in	ADP
esrj-65577	135	24	the	the	DET
esrj-65577	135	25	spectral	spectral	ADJ
esrj-65577	135	26	analysis	analysis	NOUN
esrj-65577	135	27	of	of	ADP
esrj-65577	135	28	the	the	DET
esrj-65577	135	29	humidity	humidity	NOUN
esrj-65577	135	30	data	datum	NOUN
esrj-65577	135	31	.	.	PUNCT
esrj-65577	136	1	from	from	ADP
esrj-65577	136	2	the	the	DET
esrj-65577	136	3	corresponding	corresponding	ADJ
esrj-65577	136	4	periodogram	periodogram	NOUN
esrj-65577	136	5	,	,	PUNCT
esrj-65577	136	6	figure	figure	NOUN
esrj-65577	136	7	7	7	NUM
esrj-65577	136	8	,	,	PUNCT
esrj-65577	136	9	we	we	PRON
esrj-65577	136	10	note	note	VERB
esrj-65577	136	11	that	that	SCONJ
esrj-65577	136	12	the	the	DET
esrj-65577	136	13	88	88	NUM
esrj-65577	136	14	edilberto	edilberto	VERB
esrj-65577	136	15	cepeda	cepeda	PROPN
esrj-65577	136	16	cuervo	cuervo	PROPN
esrj-65577	136	17	,	,	PUNCT
esrj-65577	136	18	jorge	jorge	PROPN
esrj-65577	136	19	alberto	alberto	PROPN
esrj-65577	136	20	achcar	achcar	PROPN
esrj-65577	136	21	,	,	PUNCT
esrj-65577	136	22	marinho	marinho	PROPN
esrj-65577	136	23	g.	g.	PROPN
esrj-65577	136	24	andrade	andrade	PROPN
esrj-65577	136	25	harmonics	harmonic	NOUN
esrj-65577	136	26	of	of	ADP
esrj-65577	136	27	higher	high	ADJ
esrj-65577	136	28	intensity	intensity	NOUN
esrj-65577	136	29	corresponds	correspond	VERB
esrj-65577	136	30	to	to	ADP
esrj-65577	136	31	the	the	DET
esrj-65577	136	32	cycle	cycle	NOUN
esrj-65577	136	33	(	(	PUNCT
esrj-65577	136	34	1	1	NUM
esrj-65577	136	35	/	/	SYM
esrj-65577	136	36	fi	fi	NOUN
esrj-65577	136	37	)	)	PUNCT
esrj-65577	136	38	of	of	ADP
esrj-65577	136	39	26	26	NUM
esrj-65577	136	40	and	and	CCONJ
esrj-65577	136	41	52	52	NUM
esrj-65577	136	42	days	day	NOUN
esrj-65577	136	43	.	.	PUNCT
esrj-65577	137	1	as	as	ADP
esrj-65577	137	2	in	in	ADP
esrj-65577	137	3	the	the	DET
esrj-65577	137	4	analysis	analysis	NOUN
esrj-65577	137	5	of	of	ADP
esrj-65577	137	6	streamflow	streamflow	PROPN
esrj-65577	137	7	data	datum	NOUN
esrj-65577	137	8	,	,	PUNCT
esrj-65577	137	9	the	the	DET
esrj-65577	137	10	periodogram	periodogram	NOUN
esrj-65577	137	11	shows	show	VERB
esrj-65577	137	12	that	that	SCONJ
esrj-65577	137	13	this	this	DET
esrj-65577	137	14	time	time	NOUN
esrj-65577	137	15	series	series	PROPN
esrj-65577	137	16	contains	contain	VERB
esrj-65577	137	17	two	two	NUM
esrj-65577	137	18	cosine	cosine	ADJ
esrj-65577	137	19	-	-	PUNCT
esrj-65577	137	20	sine	sine	ADJ
esrj-65577	137	21	peaks	peak	NOUN
esrj-65577	137	22	at	at	ADP
esrj-65577	137	23	these	these	DET
esrj-65577	137	24	frequencies	frequency	NOUN
esrj-65577	137	25	,	,	PUNCT
esrj-65577	137	26	two	two	NUM
esrj-65577	137	27	larger	large	ADJ
esrj-65577	137	28	peaks	peak	NOUN
esrj-65577	137	29	,	,	PUNCT
esrj-65577	137	30	and	and	CCONJ
esrj-65577	137	31	other	other	ADJ
esrj-65577	137	32	very	very	ADV
esrj-65577	137	33	small	small	ADJ
esrj-65577	137	34	peaks	peak	NOUN
esrj-65577	137	35	,	,	PUNCT
esrj-65577	137	36	possibly	possibly	ADV
esrj-65577	137	37	caused	cause	VERB
esrj-65577	137	38	by	by	ADP
esrj-65577	137	39	noise	noise	NOUN
esrj-65577	137	40	components	component	NOUN
esrj-65577	137	41	.	.	PUNCT
esrj-65577	138	1	thus	thus	ADV
esrj-65577	138	2	,	,	PUNCT
esrj-65577	138	3	the	the	DET
esrj-65577	138	4	seasonal	seasonal	ADJ
esrj-65577	138	5	term	term	NOUN
esrj-65577	138	6	to	to	PART
esrj-65577	138	7	be	be	AUX
esrj-65577	138	8	included	include	VERB
esrj-65577	138	9	in	in	ADP
esrj-65577	138	10	the	the	DET
esrj-65577	138	11	mean	mean	ADJ
esrj-65577	138	12	equation	equation	NOUN
esrj-65577	138	13	model	model	NOUN
esrj-65577	138	14	of	of	ADP
esrj-65577	138	15	the	the	DET
esrj-65577	138	16	streamflow	streamflow	PROPN
esrj-65577	138	17	series	series	NOUN
esrj-65577	138	18	are	be	AUX
esrj-65577	138	19	given	give	VERB
esrj-65577	138	20	by	by	ADP
esrj-65577	138	21	:	:	PUNCT
esrj-65577	138	22	cos(2πt/26	cos(2πt/26	NOUN
esrj-65577	138	23	)	)	PUNCT
esrj-65577	138	24	,	,	PUNCT
esrj-65577	138	25	sin(2πt/26	sin(2πt/26	PROPN
esrj-65577	138	26	)	)	PUNCT
esrj-65577	138	27	,	,	PUNCT
esrj-65577	138	28	cos(2πt/52	cos(2πt/52	PROPN
esrj-65577	138	29	)	)	PUNCT
esrj-65577	138	30	and	and	CCONJ
esrj-65577	138	31	sin(2πt/52	sin(2πt/52	NOUN
esrj-65577	138	32	)	)	PUNCT
esrj-65577	138	33	.	.	PUNCT
esrj-65577	139	1	figure	figure	VERB
esrj-65577	139	2	8	8	NUM
esrj-65577	139	3	.	.	PUNCT
esrj-65577	139	4	air	air	PROPN
esrj-65577	139	5	humidity	humidity	PROPN
esrj-65577	139	6	time	time	PROPN
esrj-65577	139	7	series	series	PROPN
esrj-65577	139	8	data	data	PROPN
esrj-65577	139	9	(	(	PUNCT
esrj-65577	139	10	continuous	continuous	ADJ
esrj-65577	139	11	line	line	NOUN
esrj-65577	139	12	)	)	PUNCT
esrj-65577	139	13	and	and	CCONJ
esrj-65577	139	14	fitted	fit	VERB
esrj-65577	139	15	mean	mean	NOUN
esrj-65577	139	16	(	(	PUNCT
esrj-65577	139	17	diseased	diseased	ADJ
esrj-65577	139	18	line	line	NOUN
esrj-65577	139	19	)	)	PUNCT
esrj-65577	139	20	for	for	ADP
esrj-65577	139	21	double	double	ADJ
esrj-65577	139	22	seasonal	seasonal	ADJ
esrj-65577	139	23	model	model	NOUN
esrj-65577	139	24	.	.	PUNCT
esrj-65577	140	1	figure	figure	NOUN
esrj-65577	140	2	9	9	NUM
esrj-65577	140	3	.	.	PUNCT
esrj-65577	140	4	fitted	fit	VERB
esrj-65577	140	5	conditional	conditional	ADJ
esrj-65577	140	6	variance	variance	NOUN
esrj-65577	140	7	time	time	NOUN
esrj-65577	140	8	series	series	PROPN
esrj-65577	140	9	.	.	PUNCT
esrj-65577	141	1	5.1	5.1	NUM
esrj-65577	141	2	.	.	PUNCT
esrj-65577	142	1	seasonal	seasonal	ADJ
esrj-65577	142	2	mean	mean	NOUN
esrj-65577	142	3	and	and	CCONJ
esrj-65577	142	4	conditional	conditional	ADJ
esrj-65577	142	5	variance	variance	NOUN
esrj-65577	142	6	models	model	NOUN
esrj-65577	142	7	in	in	ADP
esrj-65577	142	8	this	this	DET
esrj-65577	142	9	section	section	NOUN
esrj-65577	142	10	,	,	PUNCT
esrj-65577	142	11	double	double	ADJ
esrj-65577	142	12	seasonal	seasonal	ADJ
esrj-65577	142	13	beta	beta	NOUN
esrj-65577	142	14	repression	repression	NOUN
esrj-65577	142	15	models	model	NOUN
esrj-65577	142	16	are	be	AUX
esrj-65577	142	17	proposed	propose	VERB
esrj-65577	142	18	to	to	PART
esrj-65577	142	19	analyze	analyze	VERB
esrj-65577	142	20	the	the	DET
esrj-65577	142	21	air	air	NOUN
esrj-65577	142	22	humidity	humidity	PROPN
esrj-65577	142	23	time	time	NOUN
esrj-65577	142	24	series	series	PROPN
esrj-65577	142	25	data	datum	NOUN
esrj-65577	142	26	introduced	introduce	VERB
esrj-65577	142	27	in	in	ADP
esrj-65577	142	28	section	section	NOUN
esrj-65577	142	29	1	1	NUM
esrj-65577	142	30	.	.	PUNCT
esrj-65577	143	1	in	in	ADP
esrj-65577	143	2	this	this	DET
esrj-65577	143	3	way	way	NOUN
esrj-65577	143	4	,	,	PUNCT
esrj-65577	143	5	we	we	PRON
esrj-65577	143	6	conclude	conclude	VERB
esrj-65577	143	7	that	that	SCONJ
esrj-65577	143	8	the	the	DET
esrj-65577	143	9	best	good	ADJ
esrj-65577	143	10	beta	beta	ADJ
esrj-65577	143	11	seasonal	seasonal	ADJ
esrj-65577	143	12	mean	mean	NOUN
esrj-65577	143	13	and	and	CCONJ
esrj-65577	143	14	variance	variance	NOUN
esrj-65577	143	15	model	model	NOUN
esrj-65577	143	16	is	be	AUX
esrj-65577	143	17	the	the	DET
esrj-65577	143	18	one	one	NUM
esrj-65577	143	19	where	where	SCONJ
esrj-65577	143	20	the	the	DET
esrj-65577	143	21	mean	mean	NOUN
esrj-65577	143	22	and	and	CCONJ
esrj-65577	143	23	dispersion	dispersion	NOUN
esrj-65577	143	24	regression	regression	NOUN
esrj-65577	143	25	structures	structure	NOUN
esrj-65577	143	26	are	be	AUX
esrj-65577	143	27	given	give	VERB
esrj-65577	143	28	by	by	ADP
esrj-65577	143	29	:	:	PUNCT
esrj-65577	143	30	(	(	PUNCT
esrj-65577	143	31	12	12	NUM
esrj-65577	143	32	)	)	PUNCT
esrj-65577	143	33	(	(	PUNCT
esrj-65577	143	34	13	13	NUM
esrj-65577	143	35	)	)	PUNCT
esrj-65577	143	36	assuming	assume	VERB
esrj-65577	143	37	independent	independent	ADJ
esrj-65577	143	38	normal	normal	ADJ
esrj-65577	143	39	prior	prior	ADJ
esrj-65577	143	40	distributions	distribution	NOUN
esrj-65577	143	41	n(0,100	n(0,100	PROPN
esrj-65577	143	42	)	)	PUNCT
esrj-65577	143	43	for	for	ADP
esrj-65577	143	44	the	the	DET
esrj-65577	143	45	regression	regression	NOUN
esrj-65577	143	46	parameters	parameter	NOUN
esrj-65577	143	47	α0	α0	ADJ
esrj-65577	143	48	and	and	CCONJ
esrj-65577	143	49	α1,i	α1,i	PROPN
esrj-65577	143	50	,	,	PUNCT
esrj-65577	143	51	for	for	ADP
esrj-65577	143	52	i	i	PROPN
esrj-65577	143	53	=	=	SYM
esrj-65577	143	54	1,2	1,2	NUM
esrj-65577	143	55	and	and	CCONJ
esrj-65577	143	56	for	for	ADP
esrj-65577	143	57	λ0	λ0	NOUN
esrj-65577	143	58	and	and	CCONJ
esrj-65577	143	59	λ2,i	λ2,i	ADV
esrj-65577	143	60	,	,	PUNCT
esrj-65577	143	61	for	for	ADP
esrj-65577	143	62	i	i	PROPN
esrj-65577	143	63	=	=	SYM
esrj-65577	143	64	1,2	1,2	NUM
esrj-65577	143	65	.	.	PUNCT
esrj-65577	143	66	to	to	PART
esrj-65577	143	67	fit	fit	VERB
esrj-65577	143	68	the	the	DET
esrj-65577	143	69	model	model	NOUN
esrj-65577	143	70	20,000	20,000	NUM
esrj-65577	143	71	samples	sample	NOUN
esrj-65577	143	72	of	of	ADP
esrj-65577	143	73	the	the	DET
esrj-65577	143	74	joint	joint	ADJ
esrj-65577	143	75	posterior	posterior	ADJ
esrj-65577	143	76	distribution	distribution	NOUN
esrj-65577	143	77	for	for	ADP
esrj-65577	143	78	the	the	DET
esrj-65577	143	79	parameters	parameter	NOUN
esrj-65577	143	80	of	of	ADP
esrj-65577	143	81	the	the	DET
esrj-65577	143	82	model	model	NOUN
esrj-65577	143	83	were	be	AUX
esrj-65577	143	84	also	also	ADV
esrj-65577	143	85	generated	generate	VERB
esrj-65577	143	86	using	use	VERB
esrj-65577	143	87	the	the	DET
esrj-65577	143	88	mcmc	mcmc	PROPN
esrj-65577	143	89	methods	method	NOUN
esrj-65577	143	90	and	and	CCONJ
esrj-65577	143	91	the	the	DET
esrj-65577	143	92	winbugs	winbug	NOUN
esrj-65577	143	93	software	software	NOUN
esrj-65577	143	94	(	(	PUNCT
esrj-65577	143	95	spiegelhalter	spiegelhalter	VERB
esrj-65577	143	96	et	et	PROPN
esrj-65577	143	97	al	al	PROPN
esrj-65577	143	98	,	,	PUNCT
esrj-65577	143	99	2003	2003	NUM
esrj-65577	143	100	)	)	PUNCT
esrj-65577	143	101	.	.	PUNCT
esrj-65577	144	1	monte	monte	PROPN
esrj-65577	144	2	carlo	carlo	PROPN
esrj-65577	144	3	estimates	estimate	NOUN
esrj-65577	144	4	for	for	ADP
esrj-65577	144	5	the	the	DET
esrj-65577	144	6	posterior	posterior	ADJ
esrj-65577	144	7	means	mean	NOUN
esrj-65577	144	8	of	of	ADP
esrj-65577	144	9	each	each	DET
esrj-65577	144	10	parameter	parameter	NOUN
esrj-65577	144	11	were	be	AUX
esrj-65577	144	12	obtained	obtain	VERB
esrj-65577	144	13	from	from	ADP
esrj-65577	144	14	the	the	DET
esrj-65577	144	15	final	final	ADJ
esrj-65577	144	16	simulated	simulate	VERB
esrj-65577	144	17	gibbs	gibbs	PROPN
esrj-65577	144	18	sample	sample	NOUN
esrj-65577	144	19	,	,	PUNCT
esrj-65577	144	20	after	after	ADP
esrj-65577	144	21	an	an	DET
esrj-65577	144	22	initial	initial	ADJ
esrj-65577	144	23	burn	burn	NOUN
esrj-65577	144	24	-	-	PUNCT
esrj-65577	144	25	in	in	ADP
esrj-65577	144	26	sample	sample	NOUN
esrj-65577	144	27	period	period	NOUN
esrj-65577	144	28	of	of	ADP
esrj-65577	144	29	2000	2000	NUM
esrj-65577	144	30	samples	sample	NOUN
esrj-65577	144	31	.	.	PUNCT
esrj-65577	145	1	this	this	DET
esrj-65577	145	2	“	"	PUNCT
esrj-65577	145	3	burn	burn	VERB
esrj-65577	145	4	-	-	PUNCT
esrj-65577	145	5	in	in	ADP
esrj-65577	145	6	sample	sample	NOUN
esrj-65577	145	7	”	"	PUNCT
esrj-65577	145	8	was	be	AUX
esrj-65577	145	9	discarded	discard	VERB
esrj-65577	145	10	to	to	PART
esrj-65577	145	11	eliminate	eliminate	VERB
esrj-65577	145	12	the	the	DET
esrj-65577	145	13	effect	effect	NOUN
esrj-65577	145	14	of	of	ADP
esrj-65577	145	15	the	the	DET
esrj-65577	145	16	initial	initial	ADJ
esrj-65577	145	17	values	value	NOUN
esrj-65577	145	18	in	in	ADP
esrj-65577	145	19	the	the	DET
esrj-65577	145	20	iterative	iterative	NOUN
esrj-65577	145	21	procedure	procedure	NOUN
esrj-65577	145	22	.	.	PUNCT
esrj-65577	146	1	after	after	ADP
esrj-65577	146	2	this	this	DET
esrj-65577	146	3	“	"	PUNCT
esrj-65577	146	4	burn	burn	VERB
esrj-65577	146	5	-	-	PUNCT
esrj-65577	146	6	in	in	ADP
esrj-65577	146	7	sample	sample	NOUN
esrj-65577	146	8	”	"	PUNCT
esrj-65577	146	9	period	period	NOUN
esrj-65577	146	10	we	we	PRON
esrj-65577	146	11	simulated	simulate	VERB
esrj-65577	146	12	another	another	DET
esrj-65577	146	13	20,000	20,000	NUM
esrj-65577	146	14	gibbs	gibbs	PROPN
esrj-65577	146	15	samples	sample	NOUN
esrj-65577	146	16	choosing	choose	VERB
esrj-65577	146	17	every	every	DET
esrj-65577	146	18	20	20	NUM
esrj-65577	146	19	iteration	iteration	NOUN
esrj-65577	146	20	to	to	PART
esrj-65577	146	21	get	get	VERB
esrj-65577	146	22	approximately	approximately	ADV
esrj-65577	146	23	non	non	ADJ
esrj-65577	146	24	-	-	ADJ
esrj-65577	146	25	correlated	correlate	VERB
esrj-65577	146	26	samples	sample	NOUN
esrj-65577	146	27	,	,	PUNCT
esrj-65577	146	28	which	which	PRON
esrj-65577	146	29	gives	give	VERB
esrj-65577	146	30	a	a	DET
esrj-65577	146	31	final	final	ADJ
esrj-65577	146	32	sample	sample	NOUN
esrj-65577	146	33	of	of	ADP
esrj-65577	146	34	size	size	NOUN
esrj-65577	146	35	1,000	1,000	NUM
esrj-65577	146	36	used	use	VERB
esrj-65577	146	37	to	to	PART
esrj-65577	146	38	get	get	VERB
esrj-65577	146	39	the	the	DET
esrj-65577	146	40	posterior	posterior	ADJ
esrj-65577	146	41	summaries	summary	NOUN
esrj-65577	146	42	of	of	ADP
esrj-65577	146	43	interest	interest	NOUN
esrj-65577	146	44	.	.	PUNCT
esrj-65577	147	1	the	the	DET
esrj-65577	147	2	posterior	posterior	ADJ
esrj-65577	147	3	summaries	summary	NOUN
esrj-65577	147	4	of	of	ADP
esrj-65577	147	5	interest	interest	NOUN
esrj-65577	147	6	are	be	AUX
esrj-65577	147	7	given	give	VERB
esrj-65577	147	8	in	in	ADP
esrj-65577	147	9	table	table	NOUN
esrj-65577	147	10	5	5	NUM
esrj-65577	147	11	,	,	PUNCT
esrj-65577	147	12	for	for	ADP
esrj-65577	147	13	the	the	DET
esrj-65577	147	14	mean	mean	ADJ
esrj-65577	147	15	regression	regression	NOUN
esrj-65577	147	16	parameters	parameter	NOUN
esrj-65577	147	17	,	,	PUNCT
esrj-65577	147	18	and	and	CCONJ
esrj-65577	147	19	in	in	ADP
esrj-65577	147	20	table	table	NOUN
esrj-65577	147	21	6	6	NUM
esrj-65577	147	22	,	,	PUNCT
esrj-65577	147	23	for	for	ADP
esrj-65577	147	24	the	the	DET
esrj-65577	147	25	variance	variance	NOUN
esrj-65577	147	26	regression	regression	NOUN
esrj-65577	147	27	parameters	parameter	NOUN
esrj-65577	147	28	.	.	PUNCT
esrj-65577	148	1	table	table	NOUN
esrj-65577	148	2	5	5	NUM
esrj-65577	148	3	.	.	PUNCT
esrj-65577	149	1	beta	beta	ADJ
esrj-65577	149	2	model	model	NOUN
esrj-65577	149	3	:	:	PUNCT
esrj-65577	149	4	bayesian	bayesian	NOUN
esrj-65577	149	5	estimates	estimate	NOUN
esrj-65577	149	6	for	for	ADP
esrj-65577	149	7	mean	mean	ADJ
esrj-65577	149	8	parameters	parameter	NOUN
esrj-65577	149	9	.	.	PUNCT
esrj-65577	150	1	table	table	NOUN
esrj-65577	150	2	6	6	NUM
esrj-65577	150	3	.	.	PUNCT
esrj-65577	151	1	beta	beta	ADJ
esrj-65577	151	2	model	model	NOUN
esrj-65577	151	3	:	:	PUNCT
esrj-65577	151	4	bayesian	bayesian	NOUN
esrj-65577	151	5	estimates	estimate	NOUN
esrj-65577	151	6	for	for	ADP
esrj-65577	151	7	the	the	DET
esrj-65577	151	8	variance	variance	NOUN
esrj-65577	151	9	parameter	parameter	NOUN
esrj-65577	151	10	.	.	PUNCT
esrj-65577	152	1	the	the	DET
esrj-65577	152	2	logarithm	logarithm	NOUN
esrj-65577	152	3	of	of	ADP
esrj-65577	152	4	the	the	DET
esrj-65577	152	5	likelihood	likelihood	NOUN
esrj-65577	152	6	function	function	NOUN
esrj-65577	152	7	evaluated	evaluate	VERB
esrj-65577	152	8	at	at	ADP
esrj-65577	152	9	the	the	DET
esrj-65577	152	10	obtained	obtain	VERB
esrj-65577	152	11	estimates	estimate	NOUN
esrj-65577	152	12	for	for	ADP
esrj-65577	152	13	the	the	DET
esrj-65577	152	14	parameters	parameter	NOUN
esrj-65577	152	15	of	of	ADP
esrj-65577	152	16	the	the	DET
esrj-65577	152	17	model	model	NOUN
esrj-65577	152	18	is	be	AUX
esrj-65577	152	19	given	give	VERB
esrj-65577	152	20	by	by	ADP
esrj-65577	152	21	log	log	NOUN
esrj-65577	152	22	l	l	NOUN
esrj-65577	152	23	=	=	PUNCT
esrj-65577	152	24	−853.082	−853.082	PROPN
esrj-65577	152	25	and	and	CCONJ
esrj-65577	152	26	the	the	DET
esrj-65577	152	27	dic	dic	ADJ
esrj-65577	152	28	criterion	criterion	NOUN
esrj-65577	152	29	has	have	VERB
esrj-65577	152	30	a	a	DET
esrj-65577	152	31	value	value	NOUN
esrj-65577	152	32	equals	equal	VERB
esrj-65577	152	33	to	to	ADP
esrj-65577	152	34	−825.525	−825.525	PROPN
esrj-65577	152	35	.	.	PUNCT
esrj-65577	153	1	in	in	ADP
esrj-65577	153	2	figure	figure	NOUN
esrj-65577	153	3	8	8	NUM
esrj-65577	153	4	,	,	PUNCT
esrj-65577	153	5	we	we	PRON
esrj-65577	153	6	observe	observe	VERB
esrj-65577	153	7	a	a	DET
esrj-65577	153	8	good	good	ADJ
esrj-65577	153	9	agreement	agreement	NOUN
esrj-65577	153	10	between	between	ADP
esrj-65577	153	11	data	datum	NOUN
esrj-65577	153	12	and	and	CCONJ
esrj-65577	153	13	the	the	DET
esrj-65577	153	14	fitted	fit	VERB
esrj-65577	153	15	mean	mean	NOUN
esrj-65577	153	16	,	,	PUNCT
esrj-65577	153	17	showing	show	VERB
esrj-65577	153	18	the	the	DET
esrj-65577	153	19	good	good	ADJ
esrj-65577	153	20	performance	performance	NOUN
esrj-65577	153	21	of	of	ADP
esrj-65577	153	22	the	the	DET
esrj-65577	153	23	proposed	propose	VERB
esrj-65577	153	24	model	model	NOUN
esrj-65577	153	25	to	to	PART
esrj-65577	153	26	analyze	analyze	VERB
esrj-65577	153	27	this	this	DET
esrj-65577	153	28	data	datum	NOUN
esrj-65577	153	29	set	set	VERB
esrj-65577	153	30	.	.	PUNCT
esrj-65577	154	1	figure	figure	NOUN
esrj-65577	154	2	9	9	NUM
esrj-65577	154	3	,	,	PUNCT
esrj-65577	154	4	revels	revel	VERB
esrj-65577	154	5	a	a	DET
esrj-65577	154	6	good	good	ADJ
esrj-65577	154	7	agreement	agreement	NOUN
esrj-65577	154	8	for	for	ADP
esrj-65577	154	9	the	the	DET
esrj-65577	154	10	variances	variance	NOUN
esrj-65577	154	11	,	,	PUNCT
esrj-65577	154	12	where	where	SCONJ
esrj-65577	154	13	smaller	small	ADJ
esrj-65577	154	14	means	mean	NOUN
esrj-65577	154	15	are	be	AUX
esrj-65577	154	16	accompanied	accompany	VERB
esrj-65577	154	17	by	by	ADP
esrj-65577	154	18	smaller	small	ADJ
esrj-65577	154	19	variance	variance	NOUN
esrj-65577	154	20	.	.	PUNCT
esrj-65577	155	1	this	this	DET
esrj-65577	155	2	behavior	behavior	NOUN
esrj-65577	155	3	also	also	ADV
esrj-65577	155	4	was	be	AUX
esrj-65577	155	5	observed	observe	VERB
esrj-65577	155	6	in	in	ADP
esrj-65577	155	7	the	the	DET
esrj-65577	155	8	original	original	ADJ
esrj-65577	155	9	time	time	NOUN
esrj-65577	155	10	series	series	NOUN
esrj-65577	155	11	.	.	PUNCT
esrj-65577	156	1	that	that	PRON
esrj-65577	156	2	is	is	ADV
esrj-65577	156	3	,	,	PUNCT
esrj-65577	156	4	we	we	PRON
esrj-65577	156	5	conclude	conclude	VERB
esrj-65577	156	6	that	that	SCONJ
esrj-65577	156	7	this	this	DET
esrj-65577	156	8	model	model	NOUN
esrj-65577	156	9	fits	fit	VERB
esrj-65577	156	10	by	by	ADP
esrj-65577	156	11	the	the	DET
esrj-65577	156	12	time	time	NOUN
esrj-65577	156	13	series	series	PROPN
esrj-65577	156	14	data	datum	NOUN
esrj-65577	156	15	very	very	ADV
esrj-65577	156	16	well	well	ADV
esrj-65577	156	17	.	.	PUNCT
esrj-65577	157	1	to	to	PART
esrj-65577	157	2	determine	determine	VERB
esrj-65577	157	3	the	the	DET
esrj-65577	157	4	forecasting	forecasting	NOUN
esrj-65577	157	5	performance	performance	NOUN
esrj-65577	157	6	of	of	ADP
esrj-65577	157	7	the	the	DET
esrj-65577	157	8	proposed	propose	VERB
esrj-65577	157	9	models	model	NOUN
esrj-65577	157	10	,	,	PUNCT
esrj-65577	157	11	we	we	PRON
esrj-65577	157	12	fit	fit	VERB
esrj-65577	157	13	the	the	DET
esrj-65577	157	14	seasonal	seasonal	ADJ
esrj-65577	157	15	beta	beta	ADJ
esrj-65577	157	16	autoregressive	autoregressive	ADJ
esrj-65577	157	17	model	model	NOUN
esrj-65577	157	18	to	to	ADP
esrj-65577	157	19	the	the	DET
esrj-65577	157	20	first	first	ADJ
esrj-65577	157	21	282	282	NUM
esrj-65577	157	22	observed	observed	ADJ
esrj-65577	157	23	values	value	NOUN
esrj-65577	157	24	of	of	ADP
esrj-65577	157	25	the	the	DET
esrj-65577	157	26	air	air	NOUN
esrj-65577	157	27	humidity	humidity	PROPN
esrj-65577	157	28	time	time	PROPN
esrj-65577	157	29	series	series	PROPN
esrj-65577	157	30	data	data	PROPN
esrj-65577	157	31	,	,	PUNCT
esrj-65577	157	32	in	in	ADP
esrj-65577	157	33	order	order	NOUN
esrj-65577	157	34	to	to	PART
esrj-65577	157	35	predict	predict	VERB
esrj-65577	157	36	the	the	DET
esrj-65577	157	37	time	time	NOUN
esrj-65577	157	38	behavior	behavior	NOUN
esrj-65577	157	39	in	in	ADP
esrj-65577	157	40	the	the	DET
esrj-65577	157	41	30	30	NUM
esrj-65577	157	42	last	last	ADJ
esrj-65577	157	43	weeks	week	NOUN
esrj-65577	157	44	.	.	PUNCT
esrj-65577	158	1	figure	figure	NOUN
esrj-65577	158	2	10	10	NUM
esrj-65577	158	3	shows	show	VERB
esrj-65577	158	4	the	the	DET
esrj-65577	158	5	90	90	NUM
esrj-65577	158	6	%	%	NOUN
esrj-65577	158	7	prediction	prediction	NOUN
esrj-65577	158	8	interval	interval	NOUN
esrj-65577	158	9	for	for	ADP
esrj-65577	158	10	these	these	DET
esrj-65577	158	11	last	last	ADJ
esrj-65577	158	12	weeks	week	NOUN
esrj-65577	158	13	,	,	PUNCT
esrj-65577	158	14	in	in	ADP
esrj-65577	158	15	dotted	dotted	ADJ
esrj-65577	158	16	lines	line	NOUN
esrj-65577	158	17	and	and	CCONJ
esrj-65577	158	18	the	the	DET
esrj-65577	158	19	observed	observed	ADJ
esrj-65577	158	20	values	value	NOUN
esrj-65577	158	21	of	of	ADP
esrj-65577	158	22	natural	natural	ADJ
esrj-65577	158	23	streamflows	streamflow	NOUN
esrj-65577	158	24	in	in	ADP
esrj-65577	158	25	black	black	ADJ
esrj-65577	158	26	points	point	NOUN
esrj-65577	158	27	.	.	PUNCT
esrj-65577	159	1	figure	figure	VERB
esrj-65577	159	2	7	7	NUM
esrj-65577	159	3	.	.	PUNCT
esrj-65577	159	4	periodogram	periodogram	PROPN
esrj-65577	159	5	of	of	ADP
esrj-65577	159	6	humidity	humidity	NOUN
esrj-65577	159	7	times	times	PROPN
esrj-65577	159	8	series	series	NOUN
esrj-65577	159	9	.	.	PUNCT
esrj-65577	160	1	89seasonal	89seasonal	NUM
esrj-65577	160	2	hydrological	hydrological	ADJ
esrj-65577	160	3	and	and	CCONJ
esrj-65577	160	4	meteorological	meteorological	ADJ
esrj-65577	160	5	time	time	NOUN
esrj-65577	160	6	series	series	PROPN
esrj-65577	160	7	figure	figure	NOUN
esrj-65577	160	8	10	10	NUM
esrj-65577	160	9	.	.	PUNCT
esrj-65577	161	1	forecasting	forecast	VERB
esrj-65577	161	2	humidity	humidity	NOUN
esrj-65577	161	3	time	time	NOUN
esrj-65577	161	4	series	series	PROPN
esrj-65577	161	5	.	.	PUNCT
esrj-65577	162	1	6	6	X
esrj-65577	162	2	.	.	X
esrj-65577	162	3	concluding	conclude	VERB
esrj-65577	162	4	remarks	remark	NOUN
esrj-65577	162	5	in	in	ADP
esrj-65577	162	6	this	this	DET
esrj-65577	162	7	paper	paper	NOUN
esrj-65577	162	8	,	,	PUNCT
esrj-65577	162	9	we	we	PRON
esrj-65577	162	10	introduce	introduce	VERB
esrj-65577	162	11	a	a	DET
esrj-65577	162	12	new	new	ADJ
esrj-65577	162	13	class	class	NOUN
esrj-65577	162	14	of	of	ADP
esrj-65577	162	15	time	time	NOUN
esrj-65577	162	16	series	series	NOUN
esrj-65577	162	17	models	model	NOUN
esrj-65577	162	18	assuming	assume	VERB
esrj-65577	162	19	continuous	continuous	ADJ
esrj-65577	162	20	random	random	ADJ
esrj-65577	162	21	variables	variable	NOUN
esrj-65577	162	22	within	within	ADP
esrj-65577	162	23	the	the	DET
esrj-65577	162	24	exponential	exponential	ADJ
esrj-65577	162	25	family	family	NOUN
esrj-65577	162	26	applied	apply	VERB
esrj-65577	162	27	to	to	ADP
esrj-65577	162	28	hydrological	hydrological	ADJ
esrj-65577	162	29	and	and	CCONJ
esrj-65577	162	30	meteorological	meteorological	ADJ
esrj-65577	162	31	data	datum	NOUN
esrj-65577	162	32	.	.	PUNCT
esrj-65577	163	1	special	special	ADJ
esrj-65577	163	2	cases	case	NOUN
esrj-65577	163	3	of	of	ADP
esrj-65577	163	4	this	this	DET
esrj-65577	163	5	proposed	propose	VERB
esrj-65577	163	6	methodology	methodology	NOUN
esrj-65577	163	7	were	be	AUX
esrj-65577	163	8	considered	consider	VERB
esrj-65577	163	9	assuming	assume	VERB
esrj-65577	163	10	,	,	PUNCT
esrj-65577	163	11	normal	normal	ADJ
esrj-65577	163	12	,	,	PUNCT
esrj-65577	163	13	gamma	gamma	NOUN
esrj-65577	163	14	and	and	CCONJ
esrj-65577	163	15	beta	beta	NOUN
esrj-65577	163	16	distributions	distribution	NOUN
esrj-65577	163	17	.	.	PUNCT
esrj-65577	164	1	these	these	DET
esrj-65577	164	2	new	new	ADJ
esrj-65577	164	3	models	model	NOUN
esrj-65577	164	4	could	could	AUX
esrj-65577	164	5	be	be	AUX
esrj-65577	164	6	of	of	ADP
esrj-65577	164	7	great	great	ADJ
esrj-65577	164	8	interest	interest	NOUN
esrj-65577	164	9	to	to	PART
esrj-65577	164	10	analyze	analyze	VERB
esrj-65577	164	11	hydrological	hydrological	ADJ
esrj-65577	164	12	and	and	CCONJ
esrj-65577	164	13	meteorological	meteorological	ADJ
esrj-65577	164	14	data	datum	NOUN
esrj-65577	164	15	,	,	PUNCT
esrj-65577	164	16	since	since	SCONJ
esrj-65577	164	17	the	the	DET
esrj-65577	164	18	original	original	ADJ
esrj-65577	164	19	data	datum	NOUN
esrj-65577	164	20	usually	usually	ADV
esrj-65577	164	21	could	could	AUX
esrj-65577	164	22	not	not	PART
esrj-65577	164	23	be	be	AUX
esrj-65577	164	24	fitted	fit	VERB
esrj-65577	164	25	assuming	assume	VERB
esrj-65577	164	26	the	the	DET
esrj-65577	164	27	standard	standard	ADJ
esrj-65577	164	28	modeling	modeling	NOUN
esrj-65577	164	29	approach	approach	NOUN
esrj-65577	164	30	for	for	ADP
esrj-65577	164	31	the	the	DET
esrj-65577	164	32	means	mean	NOUN
esrj-65577	164	33	of	of	ADP
esrj-65577	164	34	the	the	DET
esrj-65577	164	35	data	datum	NOUN
esrj-65577	164	36	or	or	CCONJ
esrj-65577	164	37	assuming	assume	VERB
esrj-65577	164	38	standard	standard	ADJ
esrj-65577	164	39	distribution	distribution	NOUN
esrj-65577	164	40	assumptions	assumption	NOUN
esrj-65577	164	41	for	for	ADP
esrj-65577	164	42	time	time	NOUN
esrj-65577	164	43	series	series	PROPN
esrj-65577	164	44	data	data	PROPN
esrj-65577	164	45	.	.	PUNCT
esrj-65577	165	1	other	other	ADJ
esrj-65577	165	2	important	important	ADJ
esrj-65577	165	3	practical	practical	ADJ
esrj-65577	165	4	point	point	NOUN
esrj-65577	165	5	:	:	PUNCT
esrj-65577	165	6	in	in	ADP
esrj-65577	165	7	practical	practical	ADJ
esrj-65577	165	8	work	work	NOUN
esrj-65577	165	9	,	,	PUNCT
esrj-65577	165	10	usually	usually	ADV
esrj-65577	165	11	it	it	PRON
esrj-65577	165	12	is	be	AUX
esrj-65577	165	13	required	require	VERB
esrj-65577	165	14	to	to	PART
esrj-65577	165	15	model	model	VERB
esrj-65577	165	16	simultaneously	simultaneously	ADV
esrj-65577	165	17	the	the	DET
esrj-65577	165	18	mean	mean	NOUN
esrj-65577	165	19	and	and	CCONJ
esrj-65577	165	20	the	the	DET
esrj-65577	165	21	variance	variance	NOUN
esrj-65577	165	22	depending	depend	VERB
esrj-65577	165	23	on	on	ADP
esrj-65577	165	24	a	a	DET
esrj-65577	165	25	vector	vector	NOUN
esrj-65577	165	26	of	of	ADP
esrj-65577	165	27	parameters	parameter	NOUN
esrj-65577	165	28	to	to	PART
esrj-65577	165	29	get	get	VERB
esrj-65577	165	30	better	well	ADJ
esrj-65577	165	31	predictions	prediction	NOUN
esrj-65577	165	32	and	and	CCONJ
esrj-65577	165	33	to	to	PART
esrj-65577	165	34	discover	discover	VERB
esrj-65577	165	35	the	the	DET
esrj-65577	165	36	real	real	ADJ
esrj-65577	165	37	behavior	behavior	NOUN
esrj-65577	165	38	of	of	ADP
esrj-65577	165	39	a	a	DET
esrj-65577	165	40	hydrological	hydrological	NOUN
esrj-65577	165	41	or	or	CCONJ
esrj-65577	165	42	a	a	DET
esrj-65577	165	43	meteorological	meteorological	ADJ
esrj-65577	165	44	time	time	NOUN
esrj-65577	165	45	series	series	NOUN
esrj-65577	165	46	.	.	PUNCT
esrj-65577	166	1	with	with	ADP
esrj-65577	166	2	this	this	DET
esrj-65577	166	3	modeling	modeling	NOUN
esrj-65577	166	4	approach	approach	NOUN
esrj-65577	166	5	,	,	PUNCT
esrj-65577	166	6	we	we	PRON
esrj-65577	166	7	could	could	AUX
esrj-65577	166	8	get	get	VERB
esrj-65577	166	9	better	well	ADJ
esrj-65577	166	10	inferences	inference	NOUN
esrj-65577	166	11	as	as	SCONJ
esrj-65577	166	12	it	it	PRON
esrj-65577	166	13	was	be	AUX
esrj-65577	166	14	observed	observe	VERB
esrj-65577	166	15	in	in	ADP
esrj-65577	166	16	the	the	DET
esrj-65577	166	17	illustrations	illustration	NOUN
esrj-65577	166	18	introduced	introduce	VERB
esrj-65577	166	19	in	in	ADP
esrj-65577	166	20	this	this	DET
esrj-65577	166	21	paper	paper	NOUN
esrj-65577	166	22	.	.	PUNCT
esrj-65577	167	1	this	this	DET
esrj-65577	167	2	approach	approach	NOUN
esrj-65577	167	3	usually	usually	ADV
esrj-65577	167	4	is	be	AUX
esrj-65577	167	5	not	not	PART
esrj-65577	167	6	considered	consider	VERB
esrj-65577	167	7	by	by	ADP
esrj-65577	167	8	hydrological	hydrological	ADJ
esrj-65577	167	9	or	or	CCONJ
esrj-65577	167	10	meteorological	meteorological	ADJ
esrj-65577	167	11	researchers	researcher	NOUN
esrj-65577	167	12	using	use	VERB
esrj-65577	167	13	standard	standard	ADJ
esrj-65577	167	14	available	available	ADJ
esrj-65577	167	15	software	software	NOUN
esrj-65577	167	16	for	for	ADP
esrj-65577	167	17	hydrology	hydrology	NOUN
esrj-65577	167	18	or	or	CCONJ
esrj-65577	167	19	meteorology	meteorology	NOUN
esrj-65577	167	20	time	time	NOUN
esrj-65577	167	21	series	series	NOUN
esrj-65577	167	22	.	.	PUNCT
esrj-65577	168	1	in	in	ADP
esrj-65577	168	2	this	this	DET
esrj-65577	168	3	way	way	NOUN
esrj-65577	168	4	,	,	PUNCT
esrj-65577	168	5	the	the	DET
esrj-65577	168	6	use	use	NOUN
esrj-65577	168	7	of	of	ADP
esrj-65577	168	8	bayesian	bayesian	NOUN
esrj-65577	168	9	methods	method	NOUN
esrj-65577	168	10	is	be	AUX
esrj-65577	168	11	a	a	DET
esrj-65577	168	12	good	good	ADJ
esrj-65577	168	13	alternative	alternative	NOUN
esrj-65577	168	14	to	to	PART
esrj-65577	168	15	get	get	VERB
esrj-65577	168	16	accurate	accurate	ADJ
esrj-65577	168	17	inferences	inference	NOUN
esrj-65577	168	18	and	and	CCONJ
esrj-65577	168	19	predictions	prediction	NOUN
esrj-65577	168	20	,	,	PUNCT
esrj-65577	168	21	especially	especially	ADV
esrj-65577	168	22	using	use	VERB
esrj-65577	168	23	mcmc	mcmc	PROPN
esrj-65577	168	24	methods	method	NOUN
esrj-65577	168	25	,	,	PUNCT
esrj-65577	168	26	since	since	SCONJ
esrj-65577	168	27	these	these	DET
esrj-65577	168	28	inference	inference	NOUN
esrj-65577	168	29	methods	method	NOUN
esrj-65577	168	30	are	be	AUX
esrj-65577	168	31	not	not	PART
esrj-65577	168	32	based	base	VERB
esrj-65577	168	33	on	on	ADP
esrj-65577	168	34	asymptotical	asymptotical	ADJ
esrj-65577	168	35	results	result	NOUN
esrj-65577	168	36	as	as	ADP
esrj-65577	168	37	its	its	PRON
esrj-65577	168	38	common	common	ADJ
esrj-65577	168	39	with	with	ADP
esrj-65577	168	40	standard	standard	ADJ
esrj-65577	168	41	existing	exist	VERB
esrj-65577	168	42	classical	classical	ADJ
esrj-65577	168	43	approaches	approach	NOUN
esrj-65577	168	44	based	base	VERB
esrj-65577	168	45	on	on	ADP
esrj-65577	168	46	maximum	maximum	ADJ
esrj-65577	168	47	likelihood	likelihood	NOUN
esrj-65577	168	48	estimation	estimation	NOUN
esrj-65577	168	49	procedures	procedure	NOUN
esrj-65577	168	50	.	.	PUNCT
esrj-65577	169	1	other	other	ADJ
esrj-65577	169	2	important	important	ADJ
esrj-65577	169	3	point	point	NOUN
esrj-65577	169	4	:	:	PUNCT
esrj-65577	169	5	under	under	ADP
esrj-65577	169	6	the	the	DET
esrj-65577	169	7	use	use	NOUN
esrj-65577	169	8	of	of	ADP
esrj-65577	169	9	a	a	DET
esrj-65577	169	10	bayesian	bayesian	NOUN
esrj-65577	169	11	approach	approach	NOUN
esrj-65577	169	12	,	,	PUNCT
esrj-65577	169	13	we	we	PRON
esrj-65577	169	14	could	could	AUX
esrj-65577	169	15	consider	consider	VERB
esrj-65577	169	16	informative	informative	ADJ
esrj-65577	169	17	prior	prior	ADJ
esrj-65577	169	18	distributions	distribution	NOUN
esrj-65577	169	19	when	when	SCONJ
esrj-65577	169	20	is	be	AUX
esrj-65577	169	21	available	available	ADJ
esrj-65577	169	22	prior	prior	ADJ
esrj-65577	169	23	opinion	opinion	NOUN
esrj-65577	169	24	of	of	ADP
esrj-65577	169	25	experts	expert	NOUN
esrj-65577	169	26	in	in	ADP
esrj-65577	169	27	hydrology	hydrology	NOUN
esrj-65577	169	28	and	and	CCONJ
esrj-65577	169	29	meteorology	meteorology	NOUN
esrj-65577	169	30	.	.	PUNCT
esrj-65577	170	1	this	this	PRON
esrj-65577	170	2	means	mean	VERB
esrj-65577	170	3	,	,	PUNCT
esrj-65577	170	4	better	well	ADJ
esrj-65577	170	5	predictions	prediction	NOUN
esrj-65577	170	6	.	.	PUNCT
esrj-65577	171	1	it	it	PRON
esrj-65577	171	2	is	be	AUX
esrj-65577	171	3	also	also	ADV
esrj-65577	171	4	important	important	ADJ
esrj-65577	171	5	,	,	PUNCT
esrj-65577	171	6	to	to	PART
esrj-65577	171	7	point	point	VERB
esrj-65577	171	8	out	out	ADP
esrj-65577	171	9	that	that	SCONJ
esrj-65577	171	10	the	the	DET
esrj-65577	171	11	computational	computational	ADJ
esrj-65577	171	12	work	work	NOUN
esrj-65577	171	13	needed	need	VERB
esrj-65577	171	14	in	in	ADP
esrj-65577	171	15	the	the	DET
esrj-65577	171	16	simulation	simulation	NOUN
esrj-65577	171	17	of	of	ADP
esrj-65577	171	18	samples	sample	NOUN
esrj-65577	171	19	of	of	ADP
esrj-65577	171	20	the	the	DET
esrj-65577	171	21	joint	joint	ADJ
esrj-65577	171	22	posterior	posterior	ADJ
esrj-65577	171	23	distribution	distribution	NOUN
esrj-65577	171	24	to	to	PART
esrj-65577	171	25	get	get	VERB
esrj-65577	171	26	the	the	DET
esrj-65577	171	27	posterior	posterior	ADJ
esrj-65577	171	28	summaries	summary	NOUN
esrj-65577	171	29	of	of	ADP
esrj-65577	171	30	interest	interest	NOUN
esrj-65577	171	31	is	be	AUX
esrj-65577	171	32	greatly	greatly	ADV
esrj-65577	171	33	simplified	simplified	ADJ
esrj-65577	171	34	using	use	VERB
esrj-65577	171	35	standard	standard	ADJ
esrj-65577	171	36	existing	exist	VERB
esrj-65577	171	37	softwares	software	NOUN
esrj-65577	171	38	like	like	ADP
esrj-65577	171	39	the	the	DET
esrj-65577	171	40	winbugs	winbug	NOUN
esrj-65577	171	41	software.the	software.the	PROPN
esrj-65577	171	42	proposed	propose	VERB
esrj-65577	171	43	methodology	methodology	NOUN
esrj-65577	171	44	was	be	AUX
esrj-65577	171	45	illustrated	illustrate	VERB
esrj-65577	171	46	considering	consider	VERB
esrj-65577	171	47	two	two	NUM
esrj-65577	171	48	brazilian	brazilian	ADJ
esrj-65577	171	49	data	datum	NOUN
esrj-65577	171	50	sets	set	NOUN
esrj-65577	171	51	:	:	PUNCT
esrj-65577	171	52	a	a	DET
esrj-65577	171	53	hydrological	hydrological	ADJ
esrj-65577	171	54	time	time	NOUN
esrj-65577	171	55	series	series	NOUN
esrj-65577	171	56	and	and	CCONJ
esrj-65577	171	57	a	a	DET
esrj-65577	171	58	meteorological	meteorological	ADJ
esrj-65577	171	59	time	time	NOUN
esrj-65577	171	60	series	series	NOUN
esrj-65577	171	61	.	.	PUNCT
esrj-65577	172	1	a	a	DET
esrj-65577	172	2	final	final	ADJ
esrj-65577	172	3	point	point	NOUN
esrj-65577	172	4	of	of	ADP
esrj-65577	172	5	relevance	relevance	NOUN
esrj-65577	172	6	for	for	ADP
esrj-65577	172	7	the	the	DET
esrj-65577	172	8	results	result	NOUN
esrj-65577	172	9	of	of	ADP
esrj-65577	172	10	this	this	DET
esrj-65577	172	11	paper	paper	NOUN
esrj-65577	172	12	:	:	PUNCT
esrj-65577	172	13	new	new	ADJ
esrj-65577	172	14	statistical	statistical	ADJ
esrj-65577	172	15	models	model	NOUN
esrj-65577	172	16	for	for	ADP
esrj-65577	172	17	time	time	NOUN
esrj-65577	172	18	series	series	PROPN
esrj-65577	172	19	to	to	PART
esrj-65577	172	20	model	model	VERB
esrj-65577	172	21	climatic	climatic	ADJ
esrj-65577	172	22	variables	variable	NOUN
esrj-65577	172	23	leading	lead	VERB
esrj-65577	172	24	to	to	ADP
esrj-65577	172	25	better	well	ADJ
esrj-65577	172	26	inferences	inference	NOUN
esrj-65577	172	27	and	and	CCONJ
esrj-65577	172	28	predictions	prediction	NOUN
esrj-65577	172	29	based	base	VERB
esrj-65577	172	30	on	on	ADP
esrj-65577	172	31	data	datum	NOUN
esrj-65577	172	32	from	from	ADP
esrj-65577	172	33	hydrology	hydrology	NOUN
esrj-65577	172	34	and	and	CCONJ
esrj-65577	172	35	meteorology	meteorology	NOUN
esrj-65577	172	36	can	can	AUX
esrj-65577	172	37	be	be	AUX
esrj-65577	172	38	of	of	ADP
esrj-65577	172	39	great	great	ADJ
esrj-65577	172	40	practical	practical	ADJ
esrj-65577	172	41	interest	interest	NOUN
esrj-65577	172	42	,	,	PUNCT
esrj-65577	172	43	especially	especially	ADV
esrj-65577	172	44	with	with	ADP
esrj-65577	172	45	the	the	DET
esrj-65577	172	46	large	large	ADJ
esrj-65577	172	47	climate	climate	NOUN
esrj-65577	172	48	changes	change	NOUN
esrj-65577	172	49	that	that	PRON
esrj-65577	172	50	have	have	AUX
esrj-65577	172	51	been	be	AUX
esrj-65577	172	52	observed	observe	VERB
esrj-65577	172	53	in	in	ADP
esrj-65577	172	54	the	the	DET
esrj-65577	172	55	world	world	NOUN
esrj-65577	172	56	in	in	ADP
esrj-65577	172	57	recent	recent	ADJ
esrj-65577	172	58	decades	decade	NOUN
esrj-65577	172	59	.	.	PUNCT
esrj-65577	173	1	to	to	PART
esrj-65577	173	2	determine	determine	VERB
esrj-65577	173	3	the	the	DET
esrj-65577	173	4	performance	performance	NOUN
esrj-65577	173	5	of	of	ADP
esrj-65577	173	6	the	the	DET
esrj-65577	173	7	proposed	propose	VERB
esrj-65577	173	8	models	model	NOUN
esrj-65577	173	9	,	,	PUNCT
esrj-65577	173	10	an	an	DET
esrj-65577	173	11	extensive	extensive	ADJ
esrj-65577	173	12	comparison	comparison	NOUN
esrj-65577	173	13	with	with	ADP
esrj-65577	173	14	other	other	ADJ
esrj-65577	173	15	models	model	NOUN
esrj-65577	173	16	proposed	propose	VERB
esrj-65577	173	17	in	in	ADP
esrj-65577	173	18	the	the	DET
esrj-65577	173	19	literature	literature	NOUN
esrj-65577	173	20	should	should	AUX
esrj-65577	173	21	be	be	AUX
esrj-65577	173	22	developed	develop	VERB
esrj-65577	173	23	.	.	PUNCT
esrj-65577	174	1	however	however	ADV
esrj-65577	174	2	,	,	PUNCT
esrj-65577	174	3	in	in	ADP
esrj-65577	174	4	order	order	NOUN
esrj-65577	174	5	to	to	PART
esrj-65577	174	6	compare	compare	VERB
esrj-65577	174	7	the	the	DET
esrj-65577	174	8	performance	performance	NOUN
esrj-65577	174	9	of	of	ADP
esrj-65577	174	10	the	the	DET
esrj-65577	174	11	gamma	gamma	NOUN
esrj-65577	174	12	seasonal	seasonal	ADJ
esrj-65577	174	13	models	model	NOUN
esrj-65577	174	14	with	with	ADP
esrj-65577	174	15	in	in	ADP
esrj-65577	174	16	a	a	DET
esrj-65577	174	17	model	model	NOUN
esrj-65577	174	18	without	without	ADP
esrj-65577	174	19	a	a	DET
esrj-65577	174	20	seasonal	seasonal	ADJ
esrj-65577	174	21	component	component	NOUN
esrj-65577	174	22	,	,	PUNCT
esrj-65577	174	23	we	we	PRON
esrj-65577	174	24	fit	fit	VERB
esrj-65577	174	25	the	the	DET
esrj-65577	174	26	autoregressive	autoregressive	ADJ
esrj-65577	174	27	model	model	NOUN
esrj-65577	174	28	ar(3	ar(3	NOUN
esrj-65577	174	29	)	)	PUNCT
esrj-65577	174	30	,	,	PUNCT
esrj-65577	174	31	for	for	ADP
esrj-65577	174	32	which	which	PRON
esrj-65577	174	33	the	the	DET
esrj-65577	174	34	dic	dic	ADJ
esrj-65577	174	35	value	value	NOUN
esrj-65577	174	36	was	be	AUX
esrj-65577	174	37	11990	11990	NUM
esrj-65577	174	38	,	,	PUNCT
esrj-65577	174	39	bigger	big	ADJ
esrj-65577	174	40	than	than	ADP
esrj-65577	174	41	the	the	DET
esrj-65577	174	42	dic	dic	ADJ
esrj-65577	174	43	value	value	NOUN
esrj-65577	174	44	of	of	ADP
esrj-65577	174	45	the	the	DET
esrj-65577	174	46	fitted	fit	VERB
esrj-65577	174	47	gamma	gamma	NOUN
esrj-65577	174	48	seasonal	seasonal	ADJ
esrj-65577	174	49	model	model	NOUN
esrj-65577	174	50	.	.	PUNCT
esrj-65577	175	1	the	the	DET
esrj-65577	175	2	sum	sum	NOUN
esrj-65577	175	3	of	of	ADP
esrj-65577	175	4	square	square	ADJ
esrj-65577	175	5	residuals	residual	NOUN
esrj-65577	175	6	obtained	obtain	VERB
esrj-65577	175	7	from	from	ADP
esrj-65577	175	8	applying	apply	VERB
esrj-65577	175	9	the	the	DET
esrj-65577	175	10	ar(3	ar(3	NOUN
esrj-65577	175	11	)	)	PUNCT
esrj-65577	175	12	model	model	NOUN
esrj-65577	175	13	is	be	AUX
esrj-65577	175	14	also	also	ADV
esrj-65577	175	15	bigger	big	ADJ
esrj-65577	175	16	than	than	ADP
esrj-65577	175	17	that	that	PRON
esrj-65577	175	18	for	for	ADP
esrj-65577	175	19	the	the	DET
esrj-65577	175	20	proposed	propose	VERB
esrj-65577	175	21	models	model	NOUN
esrj-65577	175	22	.	.	PUNCT
esrj-65577	176	1	for	for	ADP
esrj-65577	176	2	the	the	DET
esrj-65577	176	3	ar(3	ar(3	NOUN
esrj-65577	176	4	)	)	PUNCT
esrj-65577	176	5	model	model	NOUN
esrj-65577	176	6	,	,	PUNCT
esrj-65577	176	7	the	the	DET
esrj-65577	176	8	sum	sum	NOUN
esrj-65577	176	9	of	of	ADP
esrj-65577	176	10	square	square	ADJ
esrj-65577	176	11	residuals	residual	NOUN
esrj-65577	176	12	is	be	AUX
esrj-65577	176	13	65679347	65679347	NUM
esrj-65577	176	14	and	and	CCONJ
esrj-65577	176	15	for	for	ADP
esrj-65577	176	16	the	the	DET
esrj-65577	176	17	proposed	propose	VERB
esrj-65577	176	18	model	model	NOUN
esrj-65577	176	19	it	it	PRON
esrj-65577	176	20	is	be	AUX
esrj-65577	176	21	52976950	52976950	NUM
esrj-65577	176	22	.	.	PUNCT
esrj-65577	177	1	finally	finally	ADV
esrj-65577	177	2	,	,	PUNCT
esrj-65577	177	3	we	we	PRON
esrj-65577	177	4	fit	fit	VERB
esrj-65577	177	5	the	the	DET
esrj-65577	177	6	ar(3	ar(3	NOUN
esrj-65577	177	7	)	)	PUNCT
esrj-65577	177	8	model	model	NOUN
esrj-65577	177	9	to	to	ADP
esrj-65577	177	10	the	the	DET
esrj-65577	177	11	humidity	humidity	NOUN
esrj-65577	177	12	data	datum	NOUN
esrj-65577	177	13	,	,	PUNCT
esrj-65577	177	14	for	for	ADP
esrj-65577	177	15	which	which	PRON
esrj-65577	177	16	the	the	DET
esrj-65577	177	17	dic	dic	ADJ
esrj-65577	177	18	value	value	NOUN
esrj-65577	177	19	was	be	AUX
esrj-65577	177	20	-774.550	-774.550	NOUN
esrj-65577	177	21	,	,	PUNCT
esrj-65577	177	22	bigger	big	ADJ
esrj-65577	177	23	than	than	ADP
esrj-65577	177	24	−825.525	−825.525	NOUN
esrj-65577	177	25	,	,	PUNCT
esrj-65577	177	26	the	the	DET
esrj-65577	177	27	bic	bic	PROPN
esrj-65577	177	28	value	value	NOUN
esrj-65577	177	29	of	of	ADP
esrj-65577	177	30	the	the	DET
esrj-65577	177	31	fitted	fit	VERB
esrj-65577	177	32	beta	beta	ADJ
esrj-65577	177	33	seasonal	seasonal	ADJ
esrj-65577	177	34	model	model	NOUN
esrj-65577	177	35	.	.	PUNCT
esrj-65577	178	1	the	the	DET
esrj-65577	178	2	sum	sum	NOUN
esrj-65577	178	3	of	of	ADP
esrj-65577	178	4	square	square	ADJ
esrj-65577	178	5	residuals	residual	NOUN
esrj-65577	178	6	obtained	obtain	VERB
esrj-65577	178	7	from	from	ADP
esrj-65577	178	8	applying	apply	VERB
esrj-65577	178	9	the	the	DET
esrj-65577	178	10	ar(3	ar(3	NOUN
esrj-65577	178	11	)	)	PUNCT
esrj-65577	178	12	model	model	NOUN
esrj-65577	178	13	to	to	ADP
esrj-65577	178	14	the	the	DET
esrj-65577	178	15	humidity	humidity	NOUN
esrj-65577	178	16	data	datum	NOUN
esrj-65577	178	17	is	be	AUX
esrj-65577	178	18	17.1565	17.1565	NUM
esrj-65577	178	19	,	,	PUNCT
esrj-65577	178	20	larger	large	ADJ
esrj-65577	178	21	than	than	ADP
esrj-65577	178	22	the	the	DET
esrj-65577	178	23	dic	dic	ADJ
esrj-65577	178	24	value	value	NOUN
esrj-65577	178	25	(	(	PUNCT
esrj-65577	178	26	1.3786	1.3786	NUM
esrj-65577	178	27	)	)	PUNCT
esrj-65577	178	28	of	of	ADP
esrj-65577	178	29	the	the	DET
esrj-65577	178	30	proposed	propose	VERB
esrj-65577	178	31	models	model	NOUN
esrj-65577	178	32	.	.	PUNCT
esrj-65577	179	1	references	reference	NOUN
esrj-65577	179	2	ahdesmaki	ahdesmaki	PROPN
esrj-65577	179	3	m	m	PROPN
esrj-65577	179	4	,	,	PUNCT
esrj-65577	179	5	fokianos	fokianos	PROPN
esrj-65577	179	6	k	k	PROPN
esrj-65577	179	7	,	,	PUNCT
esrj-65577	179	8	strimmer	strimmer	PROPN
esrj-65577	179	9	k	k	PROPN
esrj-65577	179	10	(	(	PUNCT
esrj-65577	179	11	2012	2012	NUM
esrj-65577	179	12	)	)	PUNCT
esrj-65577	179	13	package	package	NOUN
esrj-65577	179	14	‘	'	PUNCT
esrj-65577	179	15	genecycle	genecycle	NOUN
esrj-65577	179	16	’	'	PUNCT
esrj-65577	179	17	.	.	PUNCT
esrj-65577	180	1	r	r	X
esrj-65577	180	2	-	-	PUNCT
esrj-65577	180	3	project	project	NOUN
esrj-65577	180	4	website	website	NOUN
esrj-65577	180	5	.	.	PUNCT
esrj-65577	181	1	url	url	PROPN
esrj-65577	181	2	:	:	PUNCT
esrj-65577	181	3	http://cran.r-project.org/web/packages/	http://cran.r-project.org/web/packages/	PROPN
esrj-65577	181	4	genecycle	genecycle	PROPN
esrj-65577	181	5	/	/	SYM
esrj-65577	181	6	genecycle.pdf	genecycle.pdf	NOUN
esrj-65577	181	7	.	.	PUNCT
esrj-65577	182	1	accessed	access	VERB
esrj-65577	182	2	2017	2017	NUM
esrj-65577	182	3	dec	dec	PROPN
esrj-65577	182	4	5	5	NUM
esrj-65577	182	5	.	.	PUNCT
esrj-65577	183	1	cepeda	cepeda	PROPN
esrj-65577	183	2	-	-	PUNCT
esrj-65577	183	3	cuervo	cuervo	PROPN
esrj-65577	183	4	,	,	PUNCT
esrj-65577	183	5	e.	e.	PROPN
esrj-65577	183	6	(	(	PUNCT
esrj-65577	183	7	2001	2001	NUM
esrj-65577	183	8	)	)	PUNCT
esrj-65577	183	9	.	.	PUNCT
esrj-65577	184	1	variability	variability	NOUN
esrj-65577	184	2	modeling	modeling	NOUN
esrj-65577	184	3	in	in	ADP
esrj-65577	184	4	generalized	generalized	ADJ
esrj-65577	184	5	linear	linear	NOUN
esrj-65577	184	6	models	model	NOUN
esrj-65577	184	7	,	,	PUNCT
esrj-65577	184	8	unpublished	unpublished	ADJ
esrj-65577	184	9	ph.d	ph.d	PROPN
esrj-65577	184	10	.	.	PUNCT
esrj-65577	185	1	thesis	thesis	NOUN
esrj-65577	185	2	.	.	PUNCT
esrj-65577	186	1	mathematics	mathematics	PROPN
esrj-65577	186	2	institute	institute	PROPN
esrj-65577	186	3	,	,	PUNCT
esrj-65577	186	4	universidade	universidade	PROPN
esrj-65577	186	5	federal	federal	PROPN
esrj-65577	186	6	do	do	PROPN
esrj-65577	186	7	rio	rio	PROPN
esrj-65577	186	8	de	de	PROPN
esrj-65577	186	9	janeiro	janeiro	PROPN
esrj-65577	186	10	.	.	PUNCT
esrj-65577	187	1	http://www.docentes.unal	http://www.docentes.unal	ADJ
esrj-65577	187	2	.	.	PUNCT
esrj-65577	188	1	edu.co/ecepedac/docs/modelagemda	edu.co/ecepedac/docs/modelagemda	PROPN
esrj-65577	188	2	variabilidade	variabilidade	VERB
esrj-65577	188	3	.	.	PUNCT
esrj-65577	189	1	pdf	pdf	PROPN
esrj-65577	189	2	cepeda	cepeda	PROPN
esrj-65577	189	3	-	-	PUNCT
esrj-65577	189	4	cuervo	cuervo	PROPN
esrj-65577	189	5	,	,	PUNCT
esrj-65577	189	6	e.	e.	PROPN
esrj-65577	189	7	,	,	PUNCT
esrj-65577	189	8	andrade	andrade	PROPN
esrj-65577	189	9	,	,	PUNCT
esrj-65577	189	10	m.	m.	NOUN
esrj-65577	189	11	g.	g.	PROPN
esrj-65577	189	12	,	,	PUNCT
esrj-65577	189	13	&	&	CCONJ
esrj-65577	189	14	achcar	achcar	PROPN
esrj-65577	189	15	,	,	PUNCT
esrj-65577	189	16	j.	j.	PROPN
esrj-65577	189	17	a.	a.	PROPN
esrj-65577	189	18	(	(	PUNCT
esrj-65577	189	19	2012	2012	NUM
esrj-65577	189	20	)	)	PUNCT
esrj-65577	189	21	.	.	PUNCT
esrj-65577	190	1	a	a	DET
esrj-65577	190	2	seasonal	seasonal	ADJ
esrj-65577	190	3	and	and	CCONJ
esrj-65577	190	4	heteroscedastic	heteroscedastic	ADJ
esrj-65577	190	5	gamma	gamma	NOUN
esrj-65577	190	6	model	model	NOUN
esrj-65577	190	7	for	for	ADP
esrj-65577	190	8	hydrological	hydrological	ADJ
esrj-65577	190	9	time	time	NOUN
esrj-65577	190	10	series	series	PROPN
esrj-65577	190	11	:	:	PUNCT
esrj-65577	190	12	a	a	DET
esrj-65577	190	13	bayesian	bayesian	NOUN
esrj-65577	190	14	approach	approach	NOUN
esrj-65577	190	15	.	.	PUNCT
esrj-65577	191	1	in	in	ADP
esrj-65577	191	2	:	:	PUNCT
esrj-65577	191	3	aip	aip	PROPN
esrj-65577	191	4	conference	conference	NOUN
esrj-65577	191	5	proceedings	proceeding	NOUN
esrj-65577	191	6	,	,	PUNCT
esrj-65577	191	7	vol	vol	NOUN
esrj-65577	191	8	.	.	NOUN
esrj-65577	191	9	1490	1490	NUM
esrj-65577	191	10	,	,	PUNCT
esrj-65577	191	11	p.	p.	NOUN
esrj-65577	191	12	97	97	NUM
esrj-65577	191	13	.	.	PUNCT
esrj-65577	192	1	cepeda	cepeda	PROPN
esrj-65577	192	2	c.	c.	PROPN
esrj-65577	192	3	e.	e.	PROPN
esrj-65577	192	4	&	&	CCONJ
esrj-65577	192	5	gamerman	gamerman	PROPN
esrj-65577	192	6	d.	d.	PROPN
esrj-65577	192	7	(	(	PUNCT
esrj-65577	192	8	2005	2005	NUM
esrj-65577	192	9	)	)	PUNCT
esrj-65577	192	10	.	.	PUNCT
esrj-65577	193	1	bayesian	bayesian	NOUN
esrj-65577	193	2	methodology	methodology	NOUN
esrj-65577	193	3	for	for	ADP
esrj-65577	193	4	modeling	model	VERB
esrj-65577	193	5	parameters	parameter	NOUN
esrj-65577	193	6	in	in	ADP
esrj-65577	193	7	the	the	DET
esrj-65577	193	8	two	two	NUM
esrj-65577	193	9	parameter	parameter	NOUN
esrj-65577	193	10	exponential	exponential	ADJ
esrj-65577	193	11	family	family	NOUN
esrj-65577	193	12	.	.	PUNCT
esrj-65577	194	1	estadística	estadística	PROPN
esrj-65577	194	2	,	,	PUNCT
esrj-65577	194	3	57	57	NUM
esrj-65577	194	4	,	,	PUNCT
esrj-65577	194	5	93	93	NUM
esrj-65577	194	6	-	-	SYM
esrj-65577	194	7	105	105	NUM
esrj-65577	194	8	.	.	PUNCT
esrj-65577	195	1	chiang	chiang	PROPN
esrj-65577	195	2	,	,	PUNCT
esrj-65577	195	3	s.	s.	PROPN
esrj-65577	195	4	m.	m.	PROPN
esrj-65577	195	5	,	,	PUNCT
esrj-65577	195	6	tsay	tsay	PROPN
esrj-65577	195	7	,	,	PUNCT
esrj-65577	195	8	t.	t.	PROPN
esrj-65577	195	9	k.	k.	PROPN
esrj-65577	195	10	&	&	CCONJ
esrj-65577	195	11	nix	nix	PROPN
esrj-65577	195	12	,	,	PUNCT
esrj-65577	195	13	s.	s.	PROPN
esrj-65577	195	14	j.	j.	PROPN
esrj-65577	195	15	(	(	PUNCT
esrj-65577	195	16	2002a	2002a	NUM
esrj-65577	195	17	)	)	PUNCT
esrj-65577	195	18	.	.	PUNCT
esrj-65577	196	1	hydrologic	hydrologic	ADJ
esrj-65577	196	2	regionalization	regionalization	NOUN
esrj-65577	196	3	of	of	ADP
esrj-65577	196	4	watersheds	watershed	NOUN
esrj-65577	196	5	.	.	PUNCT
esrj-65577	197	1	i	i	PRON
esrj-65577	197	2	:	:	PUNCT
esrj-65577	197	3	methodology	methodology	NOUN
esrj-65577	197	4	development	development	NOUN
esrj-65577	197	5	.	.	PUNCT
esrj-65577	198	1	journal	journal	PROPN
esrj-65577	198	2	of	of	ADP
esrj-65577	198	3	water	water	NOUN
esrj-65577	198	4	resources	resource	NOUN
esrj-65577	198	5	planning	planning	NOUN
esrj-65577	198	6	and	and	CCONJ
esrj-65577	198	7	management	management	NOUN
esrj-65577	198	8	,	,	PUNCT
esrj-65577	198	9	128(1	128(1	NUM
esrj-65577	198	10	)	)	PUNCT
esrj-65577	198	11	,	,	PUNCT
esrj-65577	198	12	3	3	NUM
esrj-65577	198	13	-	-	SYM
esrj-65577	198	14	11	11	NUM
esrj-65577	198	15	.	.	PUNCT
esrj-65577	199	1	chiang	chiang	PROPN
esrj-65577	199	2	,	,	PUNCT
esrj-65577	199	3	s.	s.	PROPN
esrj-65577	199	4	m.	m.	PROPN
esrj-65577	199	5	,	,	PUNCT
esrj-65577	199	6	tsay	tsay	PROPN
esrj-65577	199	7	,	,	PUNCT
esrj-65577	199	8	t.	t.	PROPN
esrj-65577	199	9	k.	k.	PROPN
esrj-65577	199	10	&	&	CCONJ
esrj-65577	199	11	nix	nix	PROPN
esrj-65577	199	12	,	,	PUNCT
esrj-65577	199	13	s.	s.	PROPN
esrj-65577	199	14	j.	j.	PROPN
esrj-65577	199	15	(	(	PUNCT
esrj-65577	199	16	2002b	2002b	NUM
esrj-65577	199	17	)	)	PUNCT
esrj-65577	199	18	.	.	PUNCT
esrj-65577	200	1	hydrologic	hydrologic	ADJ
esrj-65577	200	2	regionalization	regionalization	NOUN
esrj-65577	200	3	of	of	ADP
esrj-65577	200	4	watersheds	watershed	NOUN
esrj-65577	200	5	.	.	PUNCT
esrj-65577	201	1	ii	ii	NOUN
esrj-65577	201	2	:	:	PUNCT
esrj-65577	202	1	applications	application	NOUN
esrj-65577	202	2	.	.	PUNCT
esrj-65577	203	1	journal	journal	NOUN
esrj-65577	203	2	of	of	ADP
esrj-65577	203	3	water	water	NOUN
esrj-65577	203	4	resources	resource	NOUN
esrj-65577	203	5	planning	planning	NOUN
esrj-65577	203	6	and	and	CCONJ
esrj-65577	203	7	management	management	NOUN
esrj-65577	203	8	,	,	PUNCT
esrj-65577	203	9	128(1	128(1	NUM
esrj-65577	203	10	)	)	PUNCT
esrj-65577	203	11	,	,	PUNCT
esrj-65577	203	12	1220	1220	NUM
esrj-65577	203	13	.	.	PUNCT
esrj-65577	204	1	ferrari	ferrari	PROPN
esrj-65577	204	2	,	,	PUNCT
esrj-65577	204	3	s.	s.	PROPN
esrj-65577	204	4	,	,	PUNCT
esrj-65577	204	5	&	&	CCONJ
esrj-65577	204	6	cribari	cribari	PROPN
esrj-65577	204	7	-	-	PUNCT
esrj-65577	204	8	neto	neto	NOUN
esrj-65577	204	9	,	,	PUNCT
esrj-65577	204	10	f.	f.	PROPN
esrj-65577	204	11	(	(	PUNCT
esrj-65577	204	12	2004	2004	NUM
esrj-65577	204	13	)	)	PUNCT
esrj-65577	204	14	.	.	PUNCT
esrj-65577	205	1	beta	beta	ADJ
esrj-65577	205	2	regression	regression	NOUN
esrj-65577	205	3	for	for	ADP
esrj-65577	205	4	modeling	modeling	NOUN
esrj-65577	205	5	rates	rate	NOUN
esrj-65577	205	6	and	and	CCONJ
esrj-65577	205	7	proportions	proportion	NOUN
esrj-65577	205	8	.	.	PUNCT
esrj-65577	206	1	journal	journal	PROPN
esrj-65577	206	2	of	of	ADP
esrj-65577	206	3	applied	applied	ADJ
esrj-65577	206	4	statistics	statistic	NOUN
esrj-65577	206	5	,	,	PUNCT
esrj-65577	206	6	31	31	NUM
esrj-65577	206	7	,	,	PUNCT
esrj-65577	206	8	799	799	NUM
esrj-65577	206	9	-	-	SYM
esrj-65577	206	10	815	815	NUM
esrj-65577	206	11	.	.	PUNCT
esrj-65577	207	1	fleming	fleming	PROPN
esrj-65577	207	2	,	,	PUNCT
esrj-65577	207	3	s.	s.	PROPN
esrj-65577	207	4	w.	w.	PROPN
esrj-65577	207	5	,	,	PUNCT
esrj-65577	207	6	marsh	marsh	PROPN
esrj-65577	207	7	lavenue	lavenue	PROPN
esrj-65577	207	8	,	,	PUNCT
esrj-65577	207	9	a.	a.	PROPN
esrj-65577	207	10	,	,	PUNCT
esrj-65577	207	11	aly	aly	PROPN
esrj-65577	207	12	,	,	PUNCT
esrj-65577	207	13	a.	a.	PROPN
esrj-65577	207	14	h.	h.	PROPN
esrj-65577	207	15	,	,	PUNCT
esrj-65577	207	16	&	&	CCONJ
esrj-65577	207	17	adams	adams	PROPN
esrj-65577	207	18	,	,	PUNCT
esrj-65577	207	19	a.	a.	NOUN
esrj-65577	207	20	(	(	PUNCT
esrj-65577	207	21	2002	2002	NUM
esrj-65577	207	22	)	)	PUNCT
esrj-65577	207	23	.	.	PUNCT
esrj-65577	208	1	practical	practical	ADJ
esrj-65577	208	2	applications	application	NOUN
esrj-65577	208	3	of	of	ADP
esrj-65577	208	4	spectral	spectral	ADJ
esrj-65577	208	5	analysis	analysis	NOUN
esrj-65577	208	6	to	to	ADP
esrj-65577	208	7	hydrologic	hydrologic	ADJ
esrj-65577	208	8	time	time	NOUN
esrj-65577	208	9	series	series	PROPN
esrj-65577	208	10	.	.	PUNCT
esrj-65577	209	1	hydrological	hydrological	ADJ
esrj-65577	209	2	processes	process	NOUN
esrj-65577	209	3	,	,	PUNCT
esrj-65577	209	4	16(2	16(2	NUM
esrj-65577	209	5	)	)	PUNCT
esrj-65577	209	6	,	,	PUNCT
esrj-65577	209	7	565	565	NUM
esrj-65577	209	8	-	-	SYM
esrj-65577	209	9	574	574	NUM
esrj-65577	209	10	.	.	PUNCT
esrj-65577	210	1	guimaraes	guimaraes	PROPN
esrj-65577	210	2	,	,	PUNCT
esrj-65577	210	3	r.	r.	PROPN
esrj-65577	210	4	&	&	CCONJ
esrj-65577	210	5	santos	santos	PROPN
esrj-65577	210	6	,	,	PUNCT
esrj-65577	210	7	e.	e.	PROPN
esrj-65577	210	8	g.	g.	PROPN
esrj-65577	210	9	(	(	PUNCT
esrj-65577	210	10	2011	2011	NUM
esrj-65577	210	11	)	)	PUNCT
esrj-65577	210	12	.	.	PUNCT
esrj-65577	211	1	principles	principle	NOUN
esrj-65577	211	2	of	of	ADP
esrj-65577	211	3	stochastic	stochastic	ADJ
esrj-65577	211	4	generation	generation	NOUN
esrj-65577	211	5	of	of	ADP
esrj-65577	211	6	hydrologic	hydrologic	ADJ
esrj-65577	211	7	time	time	NOUN
esrj-65577	211	8	series	series	NOUN
esrj-65577	211	9	for	for	ADP
esrj-65577	211	10	reservoir	reservoir	NOUN
esrj-65577	211	11	planning	planning	NOUN
esrj-65577	211	12	and	and	CCONJ
esrj-65577	211	13	design	design	NOUN
esrj-65577	211	14	:	:	PUNCT
esrj-65577	211	15	a	a	DET
esrj-65577	211	16	case	case	NOUN
esrj-65577	211	17	study	study	NOUN
esrj-65577	211	18	.	.	PUNCT
esrj-65577	212	1	journal	journal	NOUN
esrj-65577	212	2	of	of	ADP
esrj-65577	212	3	hydrologic	hydrologic	ADJ
esrj-65577	212	4	engineering	engineering	NOUN
esrj-65577	212	5	.	.	PUNCT
esrj-65577	213	1	in	in	ADP
esrj-65577	213	2	press	press	NOUN
esrj-65577	213	3	.	.	PUNCT
esrj-65577	214	1	hasebe	hasebe	PROPN
esrj-65577	214	2	,	,	PUNCT
esrj-65577	214	3	m.	m.	NOUN
esrj-65577	214	4	,	,	PUNCT
esrj-65577	214	5	dandou	dandou	NOUN
esrj-65577	214	6	,	,	PUNCT
esrj-65577	214	7	t.	t.	PROPN
esrj-65577	214	8	,	,	PUNCT
esrj-65577	214	9	kumekawa	kumekawa	PROPN
esrj-65577	214	10	,	,	PUNCT
esrj-65577	214	11	t.	t.	PROPN
esrj-65577	214	12	&	&	CCONJ
esrj-65577	214	13	neijou	neijou	PROPN
esrj-65577	214	14	,	,	PUNCT
esrj-65577	214	15	s.	s.	PROPN
esrj-65577	214	16	(	(	PUNCT
esrj-65577	214	17	2000	2000	NUM
esrj-65577	214	18	)	)	PUNCT
esrj-65577	214	19	.	.	PUNCT
esrj-65577	215	1	time	time	NOUN
esrj-65577	215	2	series	series	PROPN
esrj-65577	215	3	analysis	analysis	NOUN
esrj-65577	215	4	of	of	ADP
esrj-65577	215	5	monthly	monthly	ADJ
esrj-65577	215	6	rainfall	rainfall	NOUN
esrj-65577	215	7	,	,	PUNCT
esrj-65577	215	8	mean	mean	VERB
esrj-65577	215	9	air	air	NOUN
esrj-65577	215	10	temperature	temperature	NOUN
esrj-65577	215	11	and	and	CCONJ
esrj-65577	215	12	carbon	carbon	NOUN
esrj-65577	215	13	dioxide	dioxide	NOUN
esrj-65577	215	14	.	.	PUNCT
esrj-65577	216	1	in	in	ADP
esrj-65577	216	2	:	:	PUNCT
esrj-65577	216	3	w.	w.	PROPN
esrj-65577	216	4	z.	z.	PROPN
esrj-65577	216	5	y.	y.	PROPN
esrj-65577	216	6	&	&	CCONJ
esrj-65577	216	7	s.	s.	PROPN
esrj-65577	216	8	x.	x.	PROPN
esrj-65577	216	9	hu	hu	PROPN
esrj-65577	216	10	(	(	PUNCT
esrj-65577	216	11	eds	eds	PROPN
esrj-65577	216	12	.	.	PUNCT
esrj-65577	216	13	)	)	PUNCT
esrj-65577	216	14	proceedings	proceeding	NOUN
esrj-65577	216	15	of	of	ADP
esrj-65577	216	16	the	the	DET
esrj-65577	216	17	eighth	eighth	ADJ
esrj-65577	216	18	international	international	ADJ
esrj-65577	216	19	symposium	symposium	NOUN
esrj-65577	216	20	on	on	ADP
esrj-65577	216	21	stochastic	stochastic	ADJ
esrj-65577	216	22	hydraulics	hydraulic	NOUN
esrj-65577	216	23	,	,	PUNCT
esrj-65577	216	24	533	533	NUM
esrj-65577	216	25	-	-	SYM
esrj-65577	216	26	537	537	NUM
esrj-65577	216	27	.	.	PUNCT
esrj-65577	217	1	beijing	beijing	PROPN
esrj-65577	217	2	,	,	PUNCT
esrj-65577	217	3	china	china	PROPN
esrj-65577	217	4	.	.	PUNCT
esrj-65577	218	1	hipel	hipel	PROPN
esrj-65577	218	2	,	,	PUNCT
esrj-65577	218	3	k.	k.	PROPN
esrj-65577	218	4	w.	w.	PROPN
esrj-65577	218	5	&	&	CCONJ
esrj-65577	218	6	mcleod	mcleod	PROPN
esrj-65577	218	7	,	,	PUNCT
esrj-65577	218	8	a.	a.	PROPN
esrj-65577	218	9	e.	e.	PROPN
esrj-65577	218	10	(	(	PUNCT
esrj-65577	218	11	1994	1994	NUM
esrj-65577	218	12	)	)	PUNCT
esrj-65577	218	13	.	.	PUNCT
esrj-65577	219	1	time	time	NOUN
esrj-65577	219	2	series	series	PROPN
esrj-65577	219	3	modeling	modeling	NOUN
esrj-65577	219	4	of	of	ADP
esrj-65577	219	5	water	water	NOUN
esrj-65577	219	6	resources	resource	NOUN
esrj-65577	219	7	and	and	CCONJ
esrj-65577	219	8	environmental	environmental	ADJ
esrj-65577	219	9	systems	system	NOUN
esrj-65577	219	10	.	.	PUNCT
esrj-65577	220	1	elsevier	elsevier	PROPN
esrj-65577	220	2	,	,	PUNCT
esrj-65577	220	3	amsterdam	amsterdam	PROPN
esrj-65577	220	4	,	,	PUNCT
esrj-65577	220	5	the	the	DET
esrj-65577	220	6	netherlands	netherlands	PROPN
esrj-65577	220	7	.	.	PUNCT
esrj-65577	221	1	hosking	hosking	PROPN
esrj-65577	221	2	,	,	PUNCT
esrj-65577	221	3	j.	j.	PROPN
esrj-65577	221	4	r.	r.	PROPN
esrj-65577	221	5	m.	m.	PROPN
esrj-65577	221	6	(	(	PUNCT
esrj-65577	221	7	1984	1984	NUM
esrj-65577	221	8	)	)	PUNCT
esrj-65577	221	9	.	.	PUNCT
esrj-65577	222	1	modeling	model	VERB
esrj-65577	222	2	persistence	persistence	NOUN
esrj-65577	222	3	in	in	ADP
esrj-65577	222	4	hydrological	hydrological	ADJ
esrj-65577	222	5	time	time	NOUN
esrj-65577	222	6	series	series	PROPN
esrj-65577	222	7	using	use	VERB
esrj-65577	222	8	fractional	fractional	ADJ
esrj-65577	222	9	differencing	differencing	NOUN
esrj-65577	222	10	.	.	PUNCT
esrj-65577	223	1	water	water	NOUN
esrj-65577	223	2	resources	resource	NOUN
esrj-65577	223	3	research	research	NOUN
esrj-65577	223	4	,	,	PUNCT
esrj-65577	223	5	20(12	20(12	NUM
esrj-65577	223	6	)	)	PUNCT
esrj-65577	223	7	,	,	PUNCT
esrj-65577	223	8	1898	1898	NUM
esrj-65577	223	9	-	-	SYM
esrj-65577	223	10	1908	1908	NUM
esrj-65577	223	11	.	.	PUNCT
esrj-65577	224	1	lee	lee	PROPN
esrj-65577	224	2	,	,	PUNCT
esrj-65577	224	3	j.	j.	PROPN
esrj-65577	224	4	y.	y.	PROPN
esrj-65577	224	5	&	&	CCONJ
esrj-65577	224	6	lee	lee	PROPN
esrj-65577	224	7	,	,	PUNCT
esrj-65577	224	8	k.	k.	PROPN
esrj-65577	224	9	k.	k.	PROPN
esrj-65577	224	10	(	(	PUNCT
esrj-65577	224	11	2000	2000	NUM
esrj-65577	224	12	)	)	PUNCT
esrj-65577	224	13	.	.	PUNCT
esrj-65577	225	1	use	use	NOUN
esrj-65577	225	2	of	of	ADP
esrj-65577	225	3	hydrologic	hydrologic	ADJ
esrj-65577	225	4	time	time	NOUN
esrj-65577	225	5	series	series	PROPN
esrj-65577	225	6	data	data	PROPN
esrj-65577	225	7	for	for	ADP
esrj-65577	225	8	identification	identification	NOUN
esrj-65577	225	9	of	of	ADP
esrj-65577	225	10	recharge	recharge	NOUN
esrj-65577	225	11	mechanism	mechanism	NOUN
esrj-65577	225	12	in	in	ADP
esrj-65577	225	13	a	a	DET
esrj-65577	225	14	fractured	fractured	ADJ
esrj-65577	225	15	bedrock	bedrock	NOUN
esrj-65577	225	16	aquifer	aquifer	NOUN
esrj-65577	225	17	system	system	NOUN
esrj-65577	225	18	.	.	PUNCT
esrj-65577	226	1	journal	journal	NOUN
esrj-65577	226	2	of	of	ADP
esrj-65577	226	3	hydrology	hydrology	NOUN
esrj-65577	226	4	,	,	PUNCT
esrj-65577	226	5	229	229	NUM
esrj-65577	226	6	,	,	PUNCT
esrj-65577	226	7	190	190	NUM
esrj-65577	226	8	-	-	PUNCT
esrj-65577	226	9	201	201	NUM
esrj-65577	226	10	.	.	PUNCT
esrj-65577	227	1	lall	lall	PROPN
esrj-65577	227	2	u	u	PROPN
esrj-65577	227	3	,	,	PUNCT
esrj-65577	227	4	mann	mann	PROPN
esrj-65577	227	5	m.	m.	PROPN
esrj-65577	227	6	1995	1995	NUM
esrj-65577	227	7	.	.	PUNCT
esrj-65577	228	1	the	the	DET
esrj-65577	228	2	great	great	ADJ
esrj-65577	228	3	salt	salt	NOUN
esrj-65577	228	4	lake	lake	NOUN
esrj-65577	228	5	:	:	PUNCT
esrj-65577	228	6	a	a	DET
esrj-65577	228	7	barometer	barometer	NOUN
esrj-65577	228	8	of	of	ADP
esrj-65577	228	9	low	low	ADJ
esrj-65577	228	10	frequency	frequency	ADJ
esrj-65577	228	11	climatic	climatic	ADJ
esrj-65577	228	12	variability	variability	NOUN
esrj-65577	228	13	.	.	PUNCT
esrj-65577	229	1	water	water	NOUN
esrj-65577	229	2	resources	resource	NOUN
esrj-65577	229	3	research	research	NOUN
esrj-65577	229	4	31(10	31(10	NUM
esrj-65577	229	5	)	)	PUNCT
esrj-65577	229	6	,	,	PUNCT
esrj-65577	229	7	2503	2503	NUM
esrj-65577	229	8	–	–	PUNCT
esrj-65577	229	9	2515	2515	NUM
esrj-65577	229	10	.	.	PUNCT
esrj-65577	230	1	marques	marques	PROPN
esrj-65577	230	2	,	,	PUNCT
esrj-65577	230	3	c.	c.	PROPN
esrj-65577	230	4	a.	a.	PROPN
esrj-65577	230	5	f.	f.	PROPN
esrj-65577	230	6	,	,	PUNCT
esrj-65577	230	7	ferreira	ferreira	PROPN
esrj-65577	230	8	,	,	PUNCT
esrj-65577	230	9	j.	j.	PROPN
esrj-65577	230	10	a.	a.	PROPN
esrj-65577	230	11	,	,	PUNCT
esrj-65577	230	12	rocha	rocha	PROPN
esrj-65577	230	13	,	,	PUNCT
esrj-65577	230	14	a.	a.	PROPN
esrj-65577	230	15	,	,	PUNCT
esrj-65577	230	16	castanheira	castanheira	PROPN
esrj-65577	230	17	,	,	PUNCT
esrj-65577	230	18	j.	j.	PROPN
esrj-65577	230	19	m.	m.	PROPN
esrj-65577	230	20	,	,	PUNCT
esrj-65577	230	21	melogoncalves	melogoncalve	NOUN
esrj-65577	230	22	,	,	PUNCT
esrj-65577	230	23	p.	p.	PROPN
esrj-65577	230	24	,	,	PUNCT
esrj-65577	230	25	vaz	vaz	PROPN
esrj-65577	230	26	,	,	PUNCT
esrj-65577	230	27	n.	n.	PROPN
esrj-65577	230	28	&	&	CCONJ
esrj-65577	230	29	dias	dias	PROPN
esrj-65577	230	30	,	,	PUNCT
esrj-65577	230	31	j.	j.	PROPN
esrj-65577	230	32	m.	m.	PROPN
esrj-65577	230	33	(	(	PUNCT
esrj-65577	230	34	2006	2006	NUM
esrj-65577	230	35	)	)	PUNCT
esrj-65577	230	36	.	.	PUNCT
esrj-65577	231	1	singular	singular	PROPN
esrj-65577	231	2	spectrum	spectrum	VERB
esrj-65577	231	3	analysis	analysis	NOUN
esrj-65577	231	4	and	and	CCONJ
esrj-65577	231	5	forecasting	forecasting	NOUN
esrj-65577	231	6	of	of	ADP
esrj-65577	231	7	hydrological	hydrological	ADJ
esrj-65577	231	8	time	time	NOUN
esrj-65577	231	9	series	series	PROPN
esrj-65577	231	10	.	.	PUNCT
esrj-65577	232	1	physics	physics	NOUN
esrj-65577	232	2	and	and	CCONJ
esrj-65577	232	3	chemistry	chemistry	NOUN
esrj-65577	232	4	of	of	ADP
esrj-65577	232	5	the	the	DET
esrj-65577	232	6	earth	earth	NOUN
esrj-65577	232	7	,	,	PUNCT
esrj-65577	232	8	parts	part	VERB
esrj-65577	232	9	a	a	PRON
esrj-65577	232	10	/	/	SYM
esrj-65577	232	11	b	b	NOUN
esrj-65577	232	12	/	/	SYM
esrj-65577	232	13	c	c	NOUN
esrj-65577	232	14	,	,	PUNCT
esrj-65577	232	15	31(18	31(18	NUM
esrj-65577	232	16	)	)	PUNCT
esrj-65577	232	17	,	,	PUNCT
esrj-65577	232	18	1172	1172	NUM
esrj-65577	232	19	-	-	SYM
esrj-65577	232	20	1179	1179	NUM
esrj-65577	232	21	.	.	PUNCT
esrj-65577	233	1	modal	modal	NOUN
esrj-65577	233	2	,	,	PUNCT
esrj-65577	233	3	m.	m.	NOUN
esrj-65577	233	4	s.	s.	PROPN
esrj-65577	233	5	,	,	PUNCT
esrj-65577	233	6	&	&	CCONJ
esrj-65577	233	7	wasimi	wasimi	PROPN
esrj-65577	233	8	,	,	PUNCT
esrj-65577	233	9	s.	s.	PROPN
esrj-65577	233	10	a.	a.	PROPN
esrj-65577	233	11	(	(	PUNCT
esrj-65577	233	12	2006	2006	NUM
esrj-65577	233	13	)	)	PUNCT
esrj-65577	233	14	.	.	PUNCT
esrj-65577	234	1	generating	generate	VERB
esrj-65577	234	2	and	and	CCONJ
esrj-65577	234	3	forecasting	forecast	VERB
esrj-65577	234	4	monthly	monthly	ADJ
esrj-65577	234	5	flows	flow	NOUN
esrj-65577	234	6	of	of	ADP
esrj-65577	234	7	the	the	DET
esrj-65577	234	8	ganges	ganges	PROPN
esrj-65577	234	9	river	river	NOUN
esrj-65577	234	10	with	with	ADP
esrj-65577	234	11	par	par	PROPN
esrj-65577	234	12	model	model	NOUN
esrj-65577	234	13	.	.	PUNCT
esrj-65577	235	1	journal	journal	PROPN
esrj-65577	235	2	of	of	ADP
esrj-65577	235	3	hydrology	hydrology	NOUN
esrj-65577	235	4	,	,	PUNCT
esrj-65577	235	5	323(1	323(1	NUM
esrj-65577	235	6	-	-	SYM
esrj-65577	235	7	4	4	NUM
esrj-65577	235	8	)	)	PUNCT
esrj-65577	235	9	,	,	PUNCT
esrj-65577	235	10	41	41	NUM
esrj-65577	235	11	-	-	SYM
esrj-65577	235	12	66	66	NUM
esrj-65577	235	13	.	.	PUNCT
esrj-65577	236	1	montanari	montanari	PROPN
esrj-65577	236	2	,	,	PUNCT
esrj-65577	236	3	a.	a.	NOUN
esrj-65577	236	4	,	,	PUNCT
esrj-65577	236	5	rosso	rosso	PROPN
esrj-65577	236	6	,	,	PUNCT
esrj-65577	236	7	r.	r.	PROPN
esrj-65577	236	8	&	&	CCONJ
esrj-65577	236	9	taqqu	taqqu	PROPN
esrj-65577	236	10	,	,	PUNCT
esrj-65577	236	11	m.	m.	NOUN
esrj-65577	236	12	s.	s.	PROPN
esrj-65577	236	13	(	(	PUNCT
esrj-65577	236	14	1997	1997	NUM
esrj-65577	236	15	)	)	PUNCT
esrj-65577	236	16	.	.	PUNCT
esrj-65577	237	1	fractionally	fractionally	ADV
esrj-65577	237	2	differenced	difference	VERB
esrj-65577	237	3	arima	arima	NOUN
esrj-65577	237	4	models	model	NOUN
esrj-65577	237	5	applied	apply	VERB
esrj-65577	237	6	to	to	ADP
esrj-65577	237	7	hydrologic	hydrologic	ADJ
esrj-65577	237	8	time	time	NOUN
esrj-65577	237	9	series	series	NOUN
esrj-65577	237	10	:	:	PUNCT
esrj-65577	237	11	identification	identification	NOUN
esrj-65577	237	12	,	,	PUNCT
esrj-65577	237	13	estimation	estimation	NOUN
esrj-65577	237	14	and	and	CCONJ
esrj-65577	237	15	simulation	simulation	NOUN
esrj-65577	237	16	.	.	PUNCT
esrj-65577	238	1	water	water	NOUN
esrj-65577	238	2	resources	resource	NOUN
esrj-65577	238	3	research	research	NOUN
esrj-65577	238	4	,	,	PUNCT
esrj-65577	238	5	33(1	33(1	NUM
esrj-65577	238	6	-	-	PUNCT
esrj-65577	238	7	4	4	NUM
esrj-65577	238	8	)	)	PUNCT
esrj-65577	238	9	,	,	PUNCT
esrj-65577	238	10	1035	1035	NUM
esrj-65577	238	11	-	-	SYM
esrj-65577	238	12	1044	1044	NUM
esrj-65577	238	13	.	.	PUNCT
esrj-65577	239	1	robin	robin	PROPN
esrj-65577	239	2	mjl	mjl	PROPN
esrj-65577	239	3	,	,	PUNCT
esrj-65577	239	4	gutjahr	gutjahr	PROPN
esrj-65577	239	5	al	al	PROPN
esrj-65577	239	6	,	,	PUNCT
esrj-65577	239	7	sudicky	sudicky	NOUN
esrj-65577	239	8	ea	ea	PROPN
esrj-65577	239	9	,	,	PUNCT
esrj-65577	239	10	wilson	wilson	PROPN
esrj-65577	239	11	jl	jl	PROPN
esrj-65577	239	12	.	.	PROPN
esrj-65577	239	13	1993	1993	NUM
esrj-65577	239	14	.	.	PUNCT
esrj-65577	240	1	crosscorrelated	crosscorrelate	VERB
esrj-65577	240	2	random	random	ADJ
esrj-65577	240	3	field	field	NOUN
esrj-65577	240	4	generation	generation	NOUN
esrj-65577	240	5	with	with	ADP
esrj-65577	240	6	the	the	DET
esrj-65577	240	7	direct	direct	ADJ
esrj-65577	240	8	fourier	fourier	NOUN
esrj-65577	240	9	transform	transform	NOUN
esrj-65577	240	10	method	method	NOUN
esrj-65577	240	11	.	.	PUNCT
esrj-65577	241	1	water	water	NOUN
esrj-65577	241	2	resources	resource	NOUN
esrj-65577	241	3	research	research	VERB
esrj-65577	241	4	29(7	29(7	NUM
esrj-65577	241	5	):	):	PUNCT
esrj-65577	241	6	2385–2397	2385–2397	NUM
esrj-65577	241	7	.	.	PUNCT
esrj-65577	242	1	salas	sala	NOUN
esrj-65577	242	2	,	,	PUNCT
esrj-65577	242	3	j.	j.	PROPN
esrj-65577	242	4	d.	d.	PROPN
esrj-65577	242	5	,	,	PUNCT
esrj-65577	242	6	delleur	delleur	PROPN
esrj-65577	242	7	,	,	PUNCT
esrj-65577	242	8	j.	j.	PROPN
esrj-65577	242	9	w.	w.	PROPN
esrj-65577	242	10	,	,	PUNCT
esrj-65577	242	11	yevjervich	yevjervich	PROPN
esrj-65577	242	12	,	,	PUNCT
esrj-65577	242	13	v.	v.	PROPN
esrj-65577	242	14	&	&	CCONJ
esrj-65577	242	15	lane	lane	PROPN
esrj-65577	242	16	,	,	PUNCT
esrj-65577	242	17	w.	w.	PROPN
esrj-65577	242	18	l.	l.	PROPN
esrj-65577	242	19	(	(	PUNCT
esrj-65577	242	20	1980	1980	NUM
esrj-65577	242	21	)	)	PUNCT
esrj-65577	242	22	.	.	PUNCT
esrj-65577	242	23	applied	apply	VERB
esrj-65577	242	24	90	90	NUM
esrj-65577	242	25	edilberto	edilberto	VERB
esrj-65577	242	26	cepeda	cepeda	PROPN
esrj-65577	242	27	cuervo	cuervo	PROPN
esrj-65577	242	28	,	,	PUNCT
esrj-65577	242	29	jorge	jorge	PROPN
esrj-65577	242	30	alberto	alberto	PROPN
esrj-65577	242	31	achcar	achcar	PROPN
esrj-65577	242	32	,	,	PUNCT
esrj-65577	242	33	marinho	marinho	PROPN
esrj-65577	242	34	g.	g.	PROPN
esrj-65577	242	35	andrade	andrade	PROPN
esrj-65577	242	36	modeling	modeling	PROPN
esrj-65577	242	37	of	of	ADP
esrj-65577	242	38	hydrologic	hydrologic	ADJ
esrj-65577	242	39	time	time	NOUN
esrj-65577	242	40	series	series	NOUN
esrj-65577	242	41	.	.	PUNCT
esrj-65577	243	1	water	water	NOUN
esrj-65577	243	2	resources	resource	NOUN
esrj-65577	243	3	publications	publication	NOUN
esrj-65577	243	4	,	,	PUNCT
esrj-65577	243	5	littlton	littlton	PROPN
esrj-65577	243	6	,	,	PUNCT
esrj-65577	243	7	usa	usa	PROPN
esrj-65577	243	8	.	.	PROPN
esrj-65577	243	9	salas	salas	PROPN
esrj-65577	243	10	,	,	PUNCT
esrj-65577	243	11	j.	j.	PROPN
esrj-65577	243	12	d.	d.	PROPN
esrj-65577	243	13	,	,	PUNCT
esrj-65577	243	14	boes	boes	PROPN
esrj-65577	243	15	,	,	PUNCT
esrj-65577	243	16	d.	d.	PROPN
esrj-65577	243	17	c.	c.	PROPN
esrj-65577	243	18	&	&	CCONJ
esrj-65577	243	19	smith	smith	PROPN
esrj-65577	243	20	,	,	PUNCT
esrj-65577	243	21	r.	r.	PROPN
esrj-65577	243	22	a.	a.	PROPN
esrj-65577	243	23	(	(	PUNCT
esrj-65577	243	24	1982	1982	NUM
esrj-65577	243	25	)	)	PUNCT
esrj-65577	243	26	.	.	PUNCT
esrj-65577	244	1	estimation	estimation	NOUN
esrj-65577	244	2	of	of	ADP
esrj-65577	244	3	arma	arma	PROPN
esrj-65577	244	4	models	model	NOUN
esrj-65577	244	5	with	with	ADP
esrj-65577	244	6	seasonal	seasonal	ADJ
esrj-65577	244	7	parameters	parameter	NOUN
esrj-65577	244	8	.	.	PUNCT
esrj-65577	245	1	water	water	NOUN
esrj-65577	245	2	resources	resource	NOUN
esrj-65577	245	3	research	research	NOUN
esrj-65577	245	4	,	,	PUNCT
esrj-65577	245	5	18(4	18(4	NUM
esrj-65577	245	6	)	)	PUNCT
esrj-65577	245	7	,	,	PUNCT
esrj-65577	245	8	1006	1006	NUM
esrj-65577	245	9	-	-	SYM
esrj-65577	245	10	1010	1010	NUM
esrj-65577	245	11	.	.	PUNCT
esrj-65577	246	1	spiegelhalter	spiegelhalter	PROPN
esrj-65577	246	2	,	,	PUNCT
esrj-65577	246	3	d.	d.	PROPN
esrj-65577	246	4	j.	j.	PROPN
esrj-65577	246	5	,	,	PUNCT
esrj-65577	246	6	best	good	ADJ
esrj-65577	246	7	,	,	PUNCT
esrj-65577	246	8	n.	n.	PROPN
esrj-65577	246	9	g.	g.	PROPN
esrj-65577	246	10	,	,	PUNCT
esrj-65577	246	11	carlin	carlin	PROPN
esrj-65577	246	12	,	,	PUNCT
esrj-65577	246	13	b.	b.	PROPN
esrj-65577	246	14	p.	p.	PROPN
esrj-65577	246	15	&	&	CCONJ
esrj-65577	246	16	van	van	PROPN
esrj-65577	246	17	der	der	PROPN
esrj-65577	246	18	linde	linde	PROPN
esrj-65577	246	19	,	,	PUNCT
esrj-65577	246	20	a.	a.	NOUN
esrj-65577	246	21	(	(	PUNCT
esrj-65577	246	22	2002	2002	NUM
esrj-65577	246	23	)	)	PUNCT
esrj-65577	246	24	.	.	PUNCT
esrj-65577	247	1	bayesian	bayesian	NOUN
esrj-65577	247	2	measures	measure	NOUN
esrj-65577	247	3	of	of	ADP
esrj-65577	247	4	model	model	NOUN
esrj-65577	247	5	complexity	complexity	NOUN
esrj-65577	247	6	and	and	CCONJ
esrj-65577	247	7	fit	fit	ADJ
esrj-65577	247	8	.	.	PUNCT
esrj-65577	248	1	journal	journal	PROPN
esrj-65577	248	2	of	of	ADP
esrj-65577	248	3	the	the	DET
esrj-65577	248	4	royal	royal	ADJ
esrj-65577	248	5	statistical	statistical	ADJ
esrj-65577	248	6	society	society	NOUN
esrj-65577	248	7	:	:	PUNCT
esrj-65577	248	8	series	series	PROPN
esrj-65577	248	9	b	b	PROPN
esrj-65577	248	10	,	,	PUNCT
esrj-65577	248	11	64(4	64(4	NUM
esrj-65577	248	12	)	)	PUNCT
esrj-65577	248	13	,	,	PUNCT
esrj-65577	248	14	583	583	NUM
esrj-65577	248	15	-	-	SYM
esrj-65577	248	16	639	639	NUM
esrj-65577	248	17	.	.	PUNCT
esrj-65577	249	1	spiegelhalter	spiegelhalter	PROPN
esrj-65577	249	2	,	,	PUNCT
esrj-65577	249	3	d.	d.	PROPN
esrj-65577	249	4	j.	j.	PROPN
esrj-65577	249	5	,	,	PUNCT
esrj-65577	249	6	thomas	thomas	PROPN
esrj-65577	249	7	,	,	PUNCT
esrj-65577	249	8	a.	a.	NOUN
esrj-65577	249	9	,	,	PUNCT
esrj-65577	249	10	best	good	ADJ
esrj-65577	249	11	n.	n.	PROPN
esrj-65577	249	12	g.	g.	PROPN
esrj-65577	249	13	,	,	PUNCT
esrj-65577	249	14	&	&	CCONJ
esrj-65577	249	15	gilks	gilks	PROPN
esrj-65577	249	16	,	,	PUNCT
esrj-65577	249	17	w.	w.	PROPN
esrj-65577	249	18	r.	r.	PROPN
esrj-65577	249	19	(	(	PUNCT
esrj-65577	249	20	2003	2003	NUM
esrj-65577	249	21	)	)	PUNCT
esrj-65577	249	22	.	.	PUNCT
esrj-65577	250	1	win	win	NOUN
esrj-65577	250	2	-	-	PUNCT
esrj-65577	250	3	bugs	bug	NOUN
esrj-65577	250	4	user	user	NOUN
esrj-65577	250	5	manual	manual	NOUN
esrj-65577	250	6	(	(	PUNCT
esrj-65577	250	7	version	version	NOUN
esrj-65577	250	8	1.4	1.4	NUM
esrj-65577	250	9	)	)	PUNCT
esrj-65577	250	10	.	.	PUNCT
esrj-65577	251	1	mrc	mrc	NOUN
esrj-65577	251	2	biostatistics	biostatistic	NOUN
esrj-65577	251	3	unit	unit	NOUN
esrj-65577	251	4	,	,	PUNCT
esrj-65577	251	5	cambridge	cambridge	PROPN
esrj-65577	251	6	,	,	PUNCT
esrj-65577	251	7	u.k	u.k	PROPN
esrj-65577	251	8	.	.	PROPN
esrj-65577	251	9	tesfaye	tesfaye	PROPN
esrj-65577	251	10	,	,	PUNCT
esrj-65577	251	11	y.	y.	PROPN
esrj-65577	251	12	g.	g.	PROPN
esrj-65577	251	13	,	,	PUNCT
esrj-65577	251	14	meerschaert	meerschaert	NOUN
esrj-65577	251	15	,	,	PUNCT
esrj-65577	251	16	m.	m.	NOUN
esrj-65577	251	17	m.	m.	PROPN
esrj-65577	251	18	&	&	CCONJ
esrj-65577	251	19	anderson	anderson	PROPN
esrj-65577	251	20	,	,	PUNCT
esrj-65577	251	21	p.	p.	PROPN
esrj-65577	251	22	l.	l.	PROPN
esrj-65577	251	23	(	(	PUNCT
esrj-65577	251	24	2006	2006	NUM
esrj-65577	251	25	)	)	PUNCT
esrj-65577	251	26	.	.	PUNCT
esrj-65577	252	1	identification	identification	NOUN
esrj-65577	252	2	of	of	ADP
esrj-65577	252	3	periodic	periodic	ADJ
esrj-65577	252	4	autoregressive	autoregressive	ADJ
esrj-65577	252	5	moving	move	VERB
esrj-65577	252	6	average	average	ADJ
esrj-65577	252	7	models	model	NOUN
esrj-65577	252	8	and	and	CCONJ
esrj-65577	252	9	their	their	PRON
esrj-65577	252	10	application	application	NOUN
esrj-65577	252	11	to	to	ADP
esrj-65577	252	12	the	the	DET
esrj-65577	252	13	modeling	modeling	NOUN
esrj-65577	252	14	of	of	ADP
esrj-65577	252	15	river	river	NOUN
esrj-65577	252	16	flows	flow	NOUN
esrj-65577	252	17	.	.	PUNCT
esrj-65577	253	1	water	water	NOUN
esrj-65577	253	2	resources	resource	NOUN
esrj-65577	253	3	research	research	NOUN
esrj-65577	253	4	,	,	PUNCT
esrj-65577	253	5	42(w01419	42(w01419	NUM
esrj-65577	253	6	)	)	PUNCT
esrj-65577	253	7	,	,	PUNCT
esrj-65577	253	8	1	1	NUM
esrj-65577	253	9	-	-	SYM
esrj-65577	253	10	11	11	NUM
esrj-65577	253	11	.	.	PUNCT
esrj-65577	254	1	wang	wang	PROPN
esrj-65577	254	2	,	,	PUNCT
esrj-65577	254	3	q.	q.	PROPN
esrj-65577	254	4	j.	j.	PROPN
esrj-65577	254	5	,	,	PUNCT
esrj-65577	254	6	robertson	robertson	PROPN
esrj-65577	254	7	,	,	PUNCT
esrj-65577	254	8	d.	d.	PROPN
esrj-65577	254	9	e.	e.	PROPN
esrj-65577	254	10	&	&	CCONJ
esrj-65577	254	11	chiew	chiew	PROPN
esrj-65577	254	12	,	,	PUNCT
esrj-65577	254	13	f.	f.	PROPN
esrj-65577	254	14	h.	h.	PROPN
esrj-65577	254	15	s.	s.	PROPN
esrj-65577	254	16	(	(	PUNCT
esrj-65577	254	17	2009	2009	NUM
esrj-65577	254	18	)	)	PUNCT
esrj-65577	254	19	.	.	PUNCT
esrj-65577	255	1	a	a	DET
esrj-65577	255	2	bayesian	bayesian	NOUN
esrj-65577	255	3	joint	joint	ADJ
esrj-65577	255	4	probability	probability	NOUN
esrj-65577	255	5	modeling	modeling	NOUN
esrj-65577	255	6	approach	approach	NOUN
esrj-65577	255	7	for	for	ADP
esrj-65577	255	8	seasonal	seasonal	ADJ
esrj-65577	255	9	forecasting	forecasting	NOUN
esrj-65577	255	10	of	of	ADP
esrj-65577	255	11	streamflows	streamflow	NOUN
esrj-65577	255	12	at	at	ADP
esrj-65577	255	13	multiple	multiple	ADJ
esrj-65577	255	14	sites	site	NOUN
esrj-65577	255	15	.	.	PUNCT
esrj-65577	256	1	water	water	NOUN
esrj-65577	256	2	resources	resource	NOUN
esrj-65577	256	3	research	research	NOUN
esrj-65577	256	4	,	,	PUNCT
esrj-65577	256	5	45(w05407	45(w05407	PROPN
esrj-65577	256	6	)	)	PUNCT
esrj-65577	256	7	,	,	PUNCT
esrj-65577	256	8	1	1	NUM
esrj-65577	256	9	-	-	SYM
esrj-65577	256	10	18	18	NUM
esrj-65577	256	11	.	.	PUNCT
esrj-65577	257	1	wang	wang	PROPN
esrj-65577	257	2	,	,	PUNCT
esrj-65577	257	3	w.	w.	PROPN
esrj-65577	257	4	c.	c.	PROPN
esrj-65577	257	5	,	,	PUNCT
esrj-65577	257	6	chau	chau	NOUN
esrj-65577	257	7	,	,	PUNCT
esrj-65577	257	8	k.	k.	PROPN
esrj-65577	257	9	w.	w.	PROPN
esrj-65577	257	10	,	,	PUNCT
esrj-65577	257	11	xu	xu	PROPN
esrj-65577	257	12	,	,	PUNCT
esrj-65577	257	13	d.	d.	PROPN
esrj-65577	257	14	m.	m.	PROPN
esrj-65577	257	15	,	,	PUNCT
esrj-65577	257	16	&	&	CCONJ
esrj-65577	257	17	chen	chen	PROPN
esrj-65577	257	18	,	,	PUNCT
esrj-65577	257	19	x.	x.	PROPN
esrj-65577	257	20	y.	y.	PROPN
esrj-65577	257	21	(	(	PUNCT
esrj-65577	257	22	2015	2015	NUM
esrj-65577	257	23	)	)	PUNCT
esrj-65577	257	24	.	.	PUNCT
esrj-65577	258	1	improving	improve	VERB
esrj-65577	258	2	forecasting	forecasting	NOUN
esrj-65577	258	3	accuracy	accuracy	NOUN
esrj-65577	258	4	of	of	ADP
esrj-65577	258	5	annual	annual	ADJ
esrj-65577	258	6	runoff	runoff	NOUN
esrj-65577	258	7	time	time	NOUN
esrj-65577	258	8	series	series	PROPN
esrj-65577	258	9	using	use	VERB
esrj-65577	258	10	arima	arima	PROPN
esrj-65577	258	11	based	base	VERB
esrj-65577	258	12	on	on	ADP
esrj-65577	258	13	eemd	eemd	PROPN
esrj-65577	258	14	decomposition	decomposition	NOUN
esrj-65577	258	15	.	.	PUNCT
esrj-65577	259	1	water	water	NOUN
esrj-65577	259	2	resources	resource	NOUN
esrj-65577	259	3	management	management	NOUN
esrj-65577	259	4	,	,	PUNCT
esrj-65577	259	5	29(8	29(8	NOUN
esrj-65577	259	6	)	)	PUNCT
esrj-65577	259	7	,	,	PUNCT
esrj-65577	259	8	2655	2655	NUM
esrj-65577	259	9	-	-	SYM
esrj-65577	259	10	2675	2675	NUM
esrj-65577	259	11	.	.	PUNCT
esrj-65577	260	1	wu	wu	PROPN
esrj-65577	260	2	,	,	PUNCT
esrj-65577	260	3	z.	z.	PROPN
esrj-65577	260	4	,	,	PUNCT
esrj-65577	260	5	&	&	CCONJ
esrj-65577	260	6	huang	huang	PROPN
esrj-65577	260	7	,	,	PUNCT
esrj-65577	260	8	n.	n.	PROPN
esrj-65577	260	9	e.	e.	PROPN
esrj-65577	260	10	(	(	PUNCT
esrj-65577	260	11	2009	2009	NUM
esrj-65577	260	12	)	)	PUNCT
esrj-65577	260	13	.	.	PUNCT
esrj-65577	261	1	ensemble	ensemble	ADJ
esrj-65577	261	2	empirical	empirical	ADJ
esrj-65577	261	3	mode	mode	NOUN
esrj-65577	261	4	decomposition	decomposition	NOUN
esrj-65577	261	5	:	:	PUNCT
esrj-65577	261	6	a	a	DET
esrj-65577	261	7	noise	noise	NOUN
esrj-65577	261	8	-	-	PUNCT
esrj-65577	261	9	assisted	assist	VERB
esrj-65577	261	10	data	datum	NOUN
esrj-65577	261	11	analysis	analysis	NOUN
esrj-65577	261	12	method	method	NOUN
esrj-65577	261	13	.	.	PUNCT
esrj-65577	262	1	advances	advance	NOUN
esrj-65577	262	2	in	in	ADP
esrj-65577	262	3	adaptive	adaptive	ADJ
esrj-65577	262	4	data	datum	NOUN
esrj-65577	262	5	analysis	analysis	NOUN
esrj-65577	262	6	,	,	PUNCT
esrj-65577	262	7	1(01	1(01	NUM
esrj-65577	262	8	)	)	PUNCT
esrj-65577	262	9	,	,	PUNCT
esrj-65577	262	10	1	1	NUM
esrj-65577	262	11	-	-	SYM
esrj-65577	262	12	41	41	NUM
esrj-65577	262	13	.	.	PUNCT
esrj-65577	263	1	valipour	valipour	ADJ
esrj-65577	263	2	,	,	PUNCT
esrj-65577	263	3	m.	m.	NOUN
esrj-65577	263	4	,	,	PUNCT
esrj-65577	263	5	banihabib	banihabib	NOUN
esrj-65577	263	6	,	,	PUNCT
esrj-65577	263	7	m.	m.	PROPN
esrj-65577	263	8	e.	e.	PROPN
esrj-65577	263	9	,	,	PUNCT
esrj-65577	263	10	&	&	CCONJ
esrj-65577	263	11	behbahani	behbahani	PROPN
esrj-65577	263	12	,	,	PUNCT
esrj-65577	263	13	s.	s.	PROPN
esrj-65577	263	14	m.	m.	PROPN
esrj-65577	263	15	r.	r.	PROPN
esrj-65577	263	16	(	(	PUNCT
esrj-65577	263	17	2013	2013	NUM
esrj-65577	263	18	)	)	PUNCT
esrj-65577	263	19	.	.	PUNCT
esrj-65577	264	1	comparison	comparison	NOUN
esrj-65577	264	2	of	of	ADP
esrj-65577	264	3	the	the	DET
esrj-65577	264	4	arma	arma	PROPN
esrj-65577	264	5	,	,	PUNCT
esrj-65577	264	6	arima	arima	NOUN
esrj-65577	264	7	,	,	PUNCT
esrj-65577	264	8	and	and	CCONJ
esrj-65577	264	9	the	the	DET
esrj-65577	264	10	autoregressive	autoregressive	ADJ
esrj-65577	264	11	artificial	artificial	ADJ
esrj-65577	264	12	neural	neural	ADJ
esrj-65577	264	13	network	network	NOUN
esrj-65577	264	14	models	model	NOUN
esrj-65577	264	15	in	in	ADP
esrj-65577	264	16	forecasting	forecast	VERB
esrj-65577	264	17	the	the	DET
esrj-65577	264	18	monthly	monthly	ADJ
esrj-65577	264	19	inflow	inflow	NOUN
esrj-65577	264	20	of	of	ADP
esrj-65577	264	21	dez	dez	PROPN
esrj-65577	264	22	dam	dam	PROPN
esrj-65577	264	23	reservoir	reservoir	PROPN
esrj-65577	264	24	.	.	PUNCT
esrj-65577	265	1	journal	journal	PROPN
esrj-65577	265	2	of	of	ADP
esrj-65577	265	3	hydrology	hydrology	NOUN
esrj-65577	265	4	,	,	PUNCT
esrj-65577	265	5	476	476	NUM
esrj-65577	265	6	,	,	PUNCT
esrj-65577	265	7	433	433	NUM
esrj-65577	265	8	-	-	SYM
esrj-65577	265	9	441	441	NUM
esrj-65577	265	10	.	.	PUNCT