Time Series Analysis and Its Applications

1. Front Matter

   Pages i-xiii

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2. Characteristics of Time Series

   Pages 1-47

3. Time Series Regression and Exploratory Data Analysis

   Pages 48-83

4. ARIMA Models

   Pages 84-173

5. Spectral Analysis and Filtering

   Pages 174-270

6. Additional Time Domain Topics

   Pages 271-323

7. State-Space Models

   Pages 324-411

8. Statistical Methods in the Frequency Domain

   Pages 412-500

9. Back Matter

   Pages 501-576

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The second edition marks a substantial change to the ?rst edition. P- haps the most signi?cant change is the introduction of examples based on the freeware R package. The package, which runs on most operating systems, can be downloaded from The Comprehensive R Archive Network (CRAN) at http://cran. r-project. org/ or any one of its mirrors. Readers who have experience with the S-PLUS R package will have no problem working with R. For novices, R installs some help manuals, and CRAN supplies links to contributed tutorials such as R for Beginners. In our examples, we assume the reader has downloaded and installed R and has downloaded the nec- sary data ?les. The data ?les can be downloaded from the website for the text,http://www. stat. pitt. edu/stoffer/tsa2/ or any one of its mirrors. We will also provide additional code and other information of interest on the text’s website. Most of the material that would be given in an introductory course on time series analysis has associated R code. Although examples are given in R, the material is not R-dependent. In courses we have given using a preliminary version of the new edition of the text, students were allowed to use any package of preference. Although most students used R (or S-PLUS), a number of them completed the course successfully using other programs such R R R as ASTSA, MATLAB ,SAS , and SPSS . Another substantial change from the ?rst edition is that the material has beendividedintosmallerchapters.

• Radiologieinformationssystem
• Resampling
• Time Series Analysis
• Time series
• data analysis
• statistics

From the reviews of the second edition:

"The book gives an introduction to time series analysis. It is designed as a textbook at both the undergraduate and graduate level and as a reference work for practitioners … . This now available second edition of the book differs from the first … by several substantial changes. … the presentation has improved. The consideration of new material makes it more attractive as well. Moreover, the use of the R package … makes the book more interesting … ." (Wolfgang Schmid, Zentrablatt MATH, Vol. 1096 (22), 2006)

"This is the second edition of a text first published in 2000 … . The text is intended as a course text for a time series analysis class at the graduate level. … I believe that every time series teacher and researcher should own this text." (Robert Lund, Journal of the American Statistical Association, Vol. 102 (479), 2007)

"This is the second edition of a text first published in 2000 … . The book is intended as a course text for a graduate-level time series analysis class. It presents a very readable introduction to time series, and uses numerous examples based on nontrivial data to illustrate the methods. … Altogether, the book offers a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Compared to other established texts, it presents a more modern slice of the discipline." (Rainer Schlittgen, Advances in Statistical Analysis, Vol. 92, 2008)

"A textbook aimed at graduate-level students, while … the book could also serve as an undergraduate introductory course in time series analysis. … The clear division between time and frequency domain methods produces a well balanced and comprehensive treatment of modern time series analysis … . The book certainly fulfils its claim to be suitable as a textbook for courses at both the undergraduate and graduate levels, as tutors can pick and choose from an abundanceof material at different levels of complexity." (Pieter Bastiaan Ober, Journal of Applied Statistics, Vol. 35 (2), 2008)

• Department of Statistics, University of California, Davis, Davis, USA

  Robert H. Shumway

• Department of Statistics, University of Pittsburgh, Pittsburgh, USA

  David S. Stoffer

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