Time Series Analysis

With Applications in R

  • Jonathan D. Cryer
  • Kung-Sik Chan
Part of the Springer Texts in Statistics book series (STS)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Pages 1-10
  3. Pages 11-26
  4. Pages 27-54
  5. Pages 109-147
  6. Pages 149-174
  7. Pages 175-190
  8. Pages 191-226
  9. Pages 227-248
  10. Pages 351-382
  11. Pages 383-422
  12. Back Matter
    Pages 423-491

About this book

Introduction

Time Series Analysis With Applications in R, Second Edition, presents an accessible approach to understanding time series models and their applications. Although the emphasis is on time domain ARIMA models and their analysis, the new edition devotes two chapters to the frequency domain and three to time series regression models, models for heteroscedasticity, and threshold models. All of the ideas and methods are illustrated with both real and simulated data sets.

A unique feature of this edition is its integration with the R computing environment. The tables and graphical displays are accompanied by the R commands used to produce them. An extensive R package, TSA, which contains many new or revised R functions and all of the data used in the book, accompanies the written text. Script files of R commands for each chapter are available for download. There is also an extensive appendix in the book that leads the reader through the use of R commands and the new R package to carry out the analyses.

Jonathan Cryer is Professor Emeritus, University of Iowa, in the Department of Statistics and Actuarial Science. He is a Fellow of the American Statistical Association and received a Collegiate Teaching Award from the University of Iowa College of Liberal Arts and Sciences. He is the author of Statistics for Business: Data Analysis and Modeling, Second Edition, (with Robert B. Miller), the Minitab Handbook, Fifth Edition, (with Barbara Ryan and Brian Joiner), the Electronic Companion to Statistics (with George Cobb), Electronic Companion to Business Statistics (with George Cobb) and numerous research papers.

Kung-Sik Chan is Professor, University of Iowa, in the Department of Statistics and Actuarial Science. He is a Fellow of the American Statistical Association and the Institute of the Mathematical Statistics, and an Elected Member of the International Statistical Institute. He received a Faculty Scholar Award from the University of Iowa in 1996. He is the author of Chaos: A Statistical Perspective (with Howell Tong) and numerous research papers.

Keywords

R package Time series Time series regression correlation financial time series nonlinear time series spectral analysis

Authors and affiliations

  • Jonathan D. Cryer
    • 1
  • Kung-Sik Chan
    • 1
  1. 1.University of IowaIowa CityUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-387-75959-3
  • Copyright Information Springer-Verlag New York 2008
  • Publisher Name Springer, New York, NY
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-0-387-75958-6
  • Online ISBN 978-0-387-75959-3
  • Series Print ISSN 1431-875X
  • About this book