Hidden Markov Models for Time Series. This item is unavailable.
Language: English
Published by Taylor and Francis Ltd, GB, 2021
Series: Book 66 of 110 - ISSN
- Softcover
- New
Seller: Rarewaves USA, HEBRON, KY, U.S.A.Rarewaves USA
AbeBooks seller since June 10, 2025
Condition: New
US$ 96.48
Item description from seller
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.FeaturesPresents an accessible overview of HMMsExplores a variety of applications in ecology, finance, epidemiology, climatology, and sociologyIncludes numerous theoretical and programming exercisesProvides most of the analysed data sets online New to the second editionA total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state processNew case studies on animal movement, rainfall occurrence and capture-recapture data. …
Seller Inventory # LU-9781032179490
- Title
- Hidden Markov Models for Time Series
- Author
- Iain L. MacDonald, Walter Zucchini, Roland Langrock
- Publisher
- Taylor and Francis Ltd, GB
- Publication year
- 2021
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 103217949X
- ISBN 13
- 9781032179490
- Edition
- 2nd.
- Item weight
- 625 grams
- Dimensions
- 15.6 x 2.31 x 23.4 cm
- Series
- Book 66 of 110: ISSN
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.
Features
- Presents an accessible overview of HMMs
- Explores a variety of applications in ecology, finance, epidemiology, climatology, and sociology
- Includes numerous theoretical and programming exercises
- Provides most of the analysed data sets online
New to the second edition
- A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process
- New case studies on animal movement, rainfall occurrence and capture-recapture data
"Synopsis" may belong to another edition of this title.
About the Author
Walter Zucchini, Iain K. MacDonald, Roland Langrock
"About the title" may belong to another edition of this title.