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 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. This book builds on recent developments to present a self-contained view.
- ISBN13 9780387402642
- Publish Date 26 January 2007 (first published 1 January 2005)
- Publish Status Active
- Publish Country US
- Imprint Springer-Verlag New York Inc.
- Edition 1st ed. 2005. Corr. 2nd printing 2007
- Format Hardcover
- Pages 653
- Language English