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Springer Inference in Hidden Markov Models (Springer Series in Statistics)

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Description

Hidden 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. 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. Many examples illustrate the algorithms and theory. The book builds on recent developments, both at the foundational level and the computational level, to present a self-contained view.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
01 December 2010
Listed Since
14 June 2010

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