Springer Texts in Statistics

Time Series Analysis and Its Applications

With R Examples

Authors: Shumway, Robert H., Stoffer, David S.

  • Student-tested and improved
  • Accessible and complete treatment of modern time series analysis
  • Promotes understanding of theoretical concepts by bringing them into a more practical context
  • Comprehensive appendices covering the necessities of understanding the mathematics of time series analysis
  • Instructors Manual available for adopters
  • New to this edition:
  • Introductions to each chapter replaced with one-page abstracts
  • All graphics and plots redone and made uniform in style
  • Bayesian section completely rewritten, covering linear Gaussian state space models only
  • R code for each example provided directly in the text for ease of data analysis replication
  • Expanded appendices with tutorials containing basic R and R time seriescommands
  • Data sets and additional R scripts available for download on Springer.com
  • Internal online links to every reference (equations, examples, chapters, etc.)
see more benefits

Buy this book

eBook $69.99
price for USA (gross)
  • ISBN 978-3-319-52452-8
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $89.99
price for USA
  • ISBN 978-3-319-52451-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this Textbook

The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty.

The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, ARMAX models, stochastic volatility, wavelets, and Markov chain Monte Carlo integration methods.

This edition includes R code for each numerical example in addition to Appendix R, which provides a reference for the data sets and R scripts used in the text in addition to a tutorial on basic R commands and R time series. An additional file is available on the book’s website for download, making all the data sets and scripts easy to load into R.


About the authors

Robert H. Shumway, PhD, is Professor Emeritus of Statistics at the University of California, Davis. He is a Fellow of the American Statistical Association and a member of the International Statistical Institute. He won the 1986 American Statistical Association Award for Outstanding Statistical Application and the 1992 Communicable Diseases Center Statistics Award; both awards were for joint papers on time series applications. He is also the author of a Prentice-Hall text on applied time series analysis and served as a Departmental Editor for the Journal of Forecasting and Associate Editor for the Journal of the American Statistical Association.

David S. Stoffer, PhD, is Professor of Statistics at the University of Pittsburgh. He is a Fellow of the American Statistical Association and has made seminal contributions to the analysis of categorical time series. David won the 1989 American Statistical Association Award for Outstanding Statistical Application in a joint paper analyzing categorical time series arising in infant sleep-state cycling. He is currently a Departmental Editor of the Journal of Forecasting and an Associate Editor of the Annals of Statistical Mathematics. He has served as Program Director in the Division of Mathematical Sciences at the National Science Foundation and as Associate Editor for the Journal of the American Statistical Association.

Reviews

  
  

Video

Table of contents (7 chapters)

  • Characteristics of Time Series

    Shumway, Robert H. (et al.)

    Pages 1-44

  • Time Series Regression and Exploratory Data Analysis

    Shumway, Robert H. (et al.)

    Pages 45-74

  • ARIMA Models

    Shumway, Robert H. (et al.)

    Pages 75-163

  • Spectral Analysis and Filtering

    Shumway, Robert H. (et al.)

    Pages 165-239

  • Additional Time Domain Topics

    Shumway, Robert H. (et al.)

    Pages 241-287

Buy this book

eBook $69.99
price for USA (gross)
  • ISBN 978-3-319-52452-8
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $89.99
price for USA
  • ISBN 978-3-319-52451-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Time Series Analysis and Its Applications
Book Subtitle
With R Examples
Authors
Series Title
Springer Texts in Statistics
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-52452-8
DOI
10.1007/978-3-319-52452-8
Softcover ISBN
978-3-319-52451-1
Series ISSN
1431-875X
Edition Number
4
Number of Pages
XIII, 562
Number of Illustrations and Tables
78 b/w illustrations, 70 illustrations in colour
Topics