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008			150903s2005 xxu| o |||| 0|eng d
020			_a9780387289823 _99780387289823
024	7		_a10.1007/0387289828 _2doi
035			_avtls000330691
039		9	_a201509030724 _bVLOAD _c201404120518 _dVLOAD _c201404090259 _dVLOAD _c201401311348 _dstaff _y201401301152 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA276-280
100	1		_aCappé, Olivier. _eautor _9302274
245	1	0	_aInference in Hidden Markov Models / _cby Olivier Cappé, Eric Moulines, Tobias Rydén.
264		1	_aNew York, NY : _bSpringer New York, _c2005.
300			_axviii, 654 páginas, 78 ilustraciones _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		_aSpringer Series in Statistics, _x0172-7397
500			_aSpringer eBooks
505	0		_aMain Definitions and Notations -- Main Definitions and Notations -- State Inference -- Filtering and Smoothing Recursions -- Advanced Topics in Smoothing -- Applications of Smoothing -- Monte Carlo Methods -- Sequential Monte Carlo Methods -- Advanced Topics in Sequential Monte Carlo -- Analysis of Sequential Monte Carlo Methods -- Parameter Inference -- Maximum Likelihood Inference, Part I: Optimization Through Exact Smoothing -- Maximum Likelihood Inference, Part II: Monte Carlo Optimization -- Statistical Properties of the Maximum Likelihood Estimator -- Fully Bayesian Approaches -- Background and Complements -- Elements of Markov Chain Theory -- An Information-Theoretic Perspective on Order Estimation.
520			_aHidden Markov models have become a widely used class of statistical models with applications in diverse areas such as communications engineering, bioinformatics, finance and many more. This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. Topics range from filtering and smoothing of the hidden Markov chain to parameter estimation, Bayesian methods and estimation of the number of states. In a unified way the book covers both models with finite state spaces, which allow for exact algorithms for filtering, estimation etc. and models with continuous state spaces (also called state-space models) requiring approximate simulation-based algorithms that are also described in detail. Simulation in hidden Markov models is addressed in five different chapters that cover both Markov chain Monte Carlo and sequential Monte Carlo approaches. Many examples illustrate the algorithms and theory. The book also carefully treats Gaussian linear state-space models and their extensions and it contains a chapter on general Markov chain theory and probabilistic aspects of hidden Markov models. This volume will suit anybody with an interest in inference for stochastic processes, and it will be useful for researchers and practitioners in areas such as statistics, signal processing, communications engineering, control theory, econometrics, finance and more. The algorithmic parts of the book do not require an advanced mathematical background, while the more theoretical parts require knowledge of probability theory at the measure-theoretical level. Olivier Cappé is Researcher for the French National Center for Scientific Research (CNRS). He received the Ph.D. degree in 1993 from Ecole Nationale Supérieure des Télécommunications, Paris, France, where he is currently a Research Associate. Most of his current research concerns computational statistics and statistical learning. Eric Moulines is Professor at Ecole Nationale Supérieure des Télécommunications (ENST), Paris, France. He graduated from Ecole Polytechnique, France, in 1984 and received the Ph.D. degree from ENST in 1990. He has authored more than 150 papers in applied probability, mathematical statistics and signal processing. Tobias Rydén is Professor of Mathematical Statistics at Lund University, Sweden, where he also received his Ph.D. in 1993. His publications include papers ranging from statistical theory to algorithmic developments for hidden Markov models.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aMoulines, Eric. _eautor _9302275
700	1		_aRydén, Tobias. _eautor _9302276
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9780387402642
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/0-387-28982-8 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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