Hidden Markov models for time series : an introduction using R

Autor: Zucchini, Walter
Rok: c2009
ISBN: 9781584885733
OKCZID: 110674806

Citace (dle ČSN ISO 690):
ZUCCHINI, Walter. Hidden Markov models for time series: an introduction using R. Boca Raton: CRC Press, c2009. xxii, 275 s. Monographs on statistics and applied probability, 110.

Anotace

Reveals How HMMs Can Be Used as General-Purpose Time Series Models Implements all methods in RHidden Markov Models for Time Series: An Introduction Using R applies hidden Markov models (HMMs) to a wide range of time series types, from continuous-valued, circular, and multivariate series to binary data, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out computations for parameter estimation, model selection and checking, decoding, and forecasting. Illustrates the methodology in actionAfter presenting the simple Poisson HMM, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference. Through examples and applications, the authors describe how to extend and generalize the basic model so it can be applied in a rich variety of situations. They also provide R code for some of the examples, enabling the use of the codes in similar applications. Effectively interpret data using HMMs This book illustrates the wonderful flexibility of HMMs as general-purpose models for time series data. It provides a broad understanding of the models and their uses.

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