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Use R!

Dynamic Linear Models with R

Authors: Petris, Giovanni, Petrone, Sonia, Campagnoli, Patrizia

  • Contains fully worked-out examples in the freely available statistical software
  • Guides the reader in a friendly way from the basics of the Bayesian approach to its practical application to time series analysis
  • Coverage includes advanced Bayesian computations, Markov chain Monte Carlo methods and particle filters
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eBook $69.99
price for USA
  • ISBN 978-0-387-77238-7
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Softcover $89.99
price for USA
  • ISBN 978-0-387-77237-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms.

The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online.

No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.

Giovanni Petris is Associate Professor at the University of Arkansas. He has published many articles on time series analysis, Bayesian methods, and Monte Carlo techniques, and has served on National Science Foundation review panels. He regularly teaches courses on time series analysis at various universities in the US and in Italy. An active participant on the R mailing lists, he has developed and maintains a couple of contributed packages.

Sonia Petrone is Associate Professor of Statistics at Bocconi University,Milano. She has published research papers in top journals in the areas of Bayesian inference, Bayesian nonparametrics, and latent variables models. She is interested in Bayesian nonparametric methods for dynamic systems and state space models and is an active member of the International Society of Bayesian Analysis.

Patrizia Campagnoli received her PhD in Mathematical Statistics from the University of Pavia in 2002. She was Assistant Professor at the University of Milano-Bicocca and currently works for a financial software company.

Reviews

“This book is a welcome addition to the series Use R! The text is interspersed with snippets of R code to illustrate the techniques and models and provides the basis of an excellent text for private study.” (International Statistical Review, 2010, 78, 1, 134-159)

“Dynamic Linear models With R provides a friendly introduction to the world of dynamic linear models (DLMs)… . This book provides the reader with the minimal tools necessary for Bayesian analysis of time series data using DLMs. …The main contribution…is the DLM package in R which provides functions for dynamic linear model creation as well as filtering, smoothing, and forecasting. Therefore, the book can be utilized as a descriptive manual that provides a hybrid practical-theoretical perspective on the purpose of the functions in this extremely useful R package. …I’d like to thank these authors for a useful applied Bayesian time series handbook suitable to a graduate statistics course and also to thank the editors of the Use R! series for providing a valuable collection of books for a fantastic open-source software.”  (American Statistician, August 2010, Vol. 64, No. 3)


Table of contents (5 chapters)

  • Introduction: basic notions about Bayesian inference

    Petris, Giovanni (et al.)

    Pages 1-29

  • Dynamic linear models

    Petris, Giovanni (et al.)

    Pages 31-84

  • Model specification

    Petris, Giovanni (et al.)

    Pages 85-142

  • Models with unknown parameters

    Petris, Giovanni (et al.)

    Pages 143-206

  • Sequential Monte Carlo methods

    Petris, Giovanni (et al.)

    Pages 207-229

Buy this book

eBook $69.99
price for USA
  • ISBN 978-0-387-77238-7
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Softcover $89.99
price for USA
  • ISBN 978-0-387-77237-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Dynamic Linear Models with R
Authors
Series Title
Use R!
Copyright
2009
Publisher
Springer-Verlag New York
Copyright Holder
Springer-Verlag New York
eBook ISBN
978-0-387-77238-7
DOI
10.1007/b135794
Softcover ISBN
978-0-387-77237-0
Series ISSN
2197-5736
Edition Number
1
Number of Pages
XIII, 252
Topics