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CRC Press Hidden Markov Models for Time Series Using R, 2nd Ed

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Description

Expand your statistical toolkit with Hidden Markov Models for Time Series: An Introduction Using R, Second Edition. Published by CRC Press as part of the Chapman and Hall/CRC Monographs on Statistics and Applied Probability, this text demonstrates the flexibility of hidden Markov models (HMMs) as general-purpose tools for analyzing time series data. This second edition provides a broad understanding of model formulations and practical uses. Readers will learn to navigate the essential components of HMMs, including estimation, forecasting, decoding, and prediction. The book also covers advanced topics such as model selection and Bayesian inference, ensuring a comprehensive grasp of the subject matter. By utilizing various examples and applications, the authors show how to extend and generalize basic models to fit a wide variety of real-world situations. Whether you are studying biological sciences or applied probability, this resource offers the technical foundation needed to apply HMMs to complex data sets effectively.

Key Features

Comprehensive coverage of HMMs as general-purpose models for diverse time series data applications.

Detailed instruction on essential statistical processes including estimation, forecasting, and decoding.

In-depth exploration of advanced methodologies such as model selection and Bayesian inference.

Practical guidance on extending and generalizing basic models to suit a wide variety of situations.

Educational approach using real-world examples and applications to build a broad understanding.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
12 August 2016
Listed Since
11 February 2016

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