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003			MX-SnUAN
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007			cr nn 008mamaa
008			150903s2007 xxu| o |||| 0|eng d
020			_a9780387699523 _99780387699523
024	7		_a10.1007/9780387699523 _2doi
035			_avtls000332050
039		9	_a201509030733 _bVLOAD _c201404122016 _dVLOAD _c201404091742 _dVLOAD _y201402041019 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA276-280
100	1		_aDedecker, Jérôme. _eautor _9304652
245	1	0	_aWeak Dependence: With Examples and Applications / _cby Jérôme Dedecker, Paul Doukhan, Gabriel Lang, León R. José Rafael, Sana Louhichi, Clémentine Prieur.
264		1	_aNew York, NY : _bSpringer New York, _c2007.
300			_axiv, 318 páginas _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aLecture Notes in Statistics, _x0930-0325 ; _v190
500			_aSpringer eBooks
505	0		_aWeak dependence -- Models -- Tools for non causal cases -- Tools for causal cases -- Applications of strong laws of large numbers -- Central Limit theorem -- Donsker Principles -- Law of the iterated logarithm (LIL) -- The Empirical process -- Functional estimation -- Spectral estimation -- Econometric applications and resampling.
520			_aThis monograph is aimed at developing Doukhan/Louhichi's (1999) idea to measure asymptotic independence of a random process. The authors propose various examples of models fitting such conditions such as stable Markov chains, dynamical systems or more complicated models, nonlinear, non-Markovian, and heteroskedastic models with infinite memory. Most of the commonly used stationary models fit their conditions. The simplicity of the conditions is also their strength. The main existing tools for an asymptotic theory are developed under weak dependence. They apply the theory to nonparametric statistics, spectral analysis, econometrics, and resampling. The level of generality makes those techniques quite robust with respect to the model. The limit theorems are sometimes sharp and always simple to apply. The theory (with proofs) is developed and the authors propose to fix the notation for future applications. A large number of research papers deals with the present ideas; the authors as well as numerous other investigators participated actively in the development of this theory. Several applications are still needed to develop a method of analysis for (nonlinear) times series and they provide here a strong basis for such studies. Jérôme Dedecker (associate professor Paris 6), Gabriel Lang (professor at Ecole Polytechnique, ENGREF Paris), Sana Louhichi (Paris 11, associate professor at Paris 2), and Clémentine Prieur (associate professor at INSA, Toulouse) are main contributors for the development of weak dependence. José Rafael León (Polar price, correspondent of the Bernoulli society for Latino-America) is professor at University Central of Venezuela and Paul Doukhan is professor at ENSAE (SAMOS-CES Paris 1 and Cergy Pontoise) and associate editor of Stochastic Processes and their Applications. His Mixing: Properties and Examples (Springer, 1994) is a main reference for the concurrent notion of mixing.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aDoukhan, Paul. _eautor _9301071
700	1		_aLang, Gabriel. _eautor _9304653
700	1		_aJosé Rafael, León R. _eautor _9304654
700	1		_aLouhichi, Sana. _eautor _9304655
700	1		_aPrieur, Clémentine. _eautor _9304656
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9780387699516
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-387-69952-3 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c280017 _d280017