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Inference in Hidden Markov Models

Inference in Hidden Markov Models

Eric Moulines / Olivier Cappé / Tobias Ryden

302,88 €
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Editorial:
Springer Nature B.V.
Año de edición:
2007
Materia
Probabilidad y estadística
ISBN:
9780387402642

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Sobre IBD

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.

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  • Inference in Hidden Markov Models
    Eric Moulines / Olivier Cappé / Tobias Ryden
    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...
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