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Hidden Markov Models for Time Series: An Introduction Using R, Second Edition (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) - Hardcover
Inhaltsangabe
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
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Über die Autorin bzw. den Autor
Walter Zucchini, Iain K. MacDonald, Roland Langrock
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Hidden Markov Models for Time Series: An Introduction Using R, Second Edition (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
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Chapman and Hall/CRC 01/g /12 A, 2016
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Hidden Markov Models for Time Series: An Introduction Using R, Second Edition (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
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Chapman and Hall/CRC 12 A, 2016
ISBN 10: 1482253836
ISBN 13: 9781482253832
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Hidden Markov Models for Time Series
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Gebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Walter Zucchini, Iain K. MacDonald, Roland LangrockHidden 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 ser. Bestandsnummer des Verkäufers 123043554
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Hidden Markov Models for Time Series: An Introduction Using R, Second Edition (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
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Chapman and Hall/CRC 2016-08-12, 2016
ISBN 10: 1482253836
ISBN 13: 9781482253832
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Hidden Markov Models for Time Series
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Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 onlineNew 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 398 pp. Englisch. Bestandsnummer des Verkäufers 9781482253832
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Hidden Markov Models for Time Series: An Introduction Using R, Second Edition
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Hidden Markov Models for Time Series
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Hidden Markov Models for Time Series : An Introduction Using R, Second Edition
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Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 onlineNew 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. Bestandsnummer des Verkäufers 9781482253832
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Hidden Markov Models for Time Series
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Hidden Markov Models for Time Series: An Introduction Using R, Second Edition (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
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