9781482253832-1482253836-Hidden Markov Models for Time Series: An Introduction Using R, Second Edition (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Hidden Markov Models for Time Series: An Introduction Using R, Second Edition (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

ISBN-13: 9781482253832
ISBN-10: 1482253836
Edition: 2
Author: Walter Zucchini, Iain L. MacDonald, Roland Langrock
Publication date: 2016
Publisher: Chapman and Hall/CRC
Format: Hardcover 398 pages
Category: Statistics
FREE shipping on ALL orders

Book details

ISBN-13: 9781482253832
ISBN-10: 1482253836
Edition: 2
Author: Walter Zucchini, Iain L. MacDonald, Roland Langrock
Publication date: 2016
Publisher: Chapman and Hall/CRC
Format: Hardcover 398 pages
Category: Statistics

Summary

Acknowledged authors Walter Zucchini , Iain L. MacDonald , Roland Langrock wrote Hidden Markov Models for Time Series: An Introduction Using R, Second Edition (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) comprising 398 pages back in 2016. Textbook and eTextbook are published under ISBN 1482253836 and 9781482253832. Since then Hidden Markov Models for Time Series: An Introduction Using R, Second Edition (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) textbook was available to sell back to BooksRun online for the top buyback price of $ 46.50 or rent at the marketplace.

Description

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

  1. Presents an accessible overview of HMMs
  2. Explores a variety of applications in ecology, finance, epidemiology, climatology, and sociology
  3. Includes numerous theoretical and programming exercises
  4. Provides most of the analysed data sets online

New to the second edition

  1. A total of five chapters on extensions, including HMMs for longitudinal data, hidden semi-Markov models and models with continuous-valued state process
  2. New case studies on animal movement, rainfall occurrence and capture-recapture data
Rate this book Rate this book

We would LOVE it if you could help us and other readers by reviewing the book