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Inference in hidden Markov models

Author: Olivier Cappé; Eric Moulines; Tobias Rydén
Publisher: New York, NY : Springer, 2005.
Series: Springer series in statistics.
Edition/Format:   Print book : EnglishView all editions and formats
Database:WorldCat
Summary:

This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory. The book builds on recent developments, both at the foundational level  Read more...

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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Olivier Cappé; Eric Moulines; Tobias Rydén
ISBN: 0387402640 9780387402642
OCLC Number: 255109662
Description: XVII, 652 S. : graph. Darst.
Contents: Main 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.
Series Title: Springer series in statistics.
Responsibility: Olivier Cappé ; Eric Moulines ; Tobias Rydén.
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From the reviews: "By providing an overall survey of results obtained so far in a very readable manner, and also presenting some new ideas, this well-written book will appeal to academic researchers Read more...

 
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