Hidden Markov Models for Time Series

"Hidden Markov Models for Time Series" presents an accessible overview of hidden Markov models for analyzing a wide range of time series data, including discrete-valued, continuous-valued, circular, and multivariate. Demonstrating how to apply methods to real world problems, it features applications [...]
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"Hidden Markov Models for Time Series" presents an accessible overview of hidden Markov models for analyzing a wide range of time series data, including discrete-valued, continuous-valued, circular, and multivariate. Demonstrating how to apply methods to real world problems, it features applications from a variety of fields, such as animal behavior, epidemiology, and finance. It also discusses the implementation of all of the techniques using R, illustrating how R can be used for parameter estimation, model selection, and model checking. With numerous exercises, this is outstanding both as a text for graduate students and as a reference for researchers, practitioners.