Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses.
After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian inference for HMMs. Through examples and applications, the authors describe how to extend and generalize the basic model so that it can be applied in a rich variety of situations.
The book demonstrates how HMMs can be applied to a wide range of types of time series: continuous-valued, circular, multivariate, binary, bounded and unbounded counts, and categorical observations. It also discusses how to employ the freely available computing environment R to carry out the computations.
Medium erhältlich in:
3 MSH Medical School Hamburg,
Hamburg
Serie / Reihe: Monographs on statistics and applied probability 150
Personen: Zucchini, Walter
Zucchini, Walter:
Hidden markov models for time series : an introduction using R / Walter Zucchini; Iain L. MacDonald; Roland Langrock. - Second edition. - Boca Raton ; London ; New York : CRC Press, Taylor & Francis, 2016. - xxviii, 370 Seiten. - (Monographs on statistics and applied probability; 150). - Includes bibliographical references and index
ISBN 978-1-4822-5383-2
Sozialwissenschaftliche Theorien und Methoden - Signatur: MR 2100 Z94-01 (2) - Buch