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Time series analysis and its applications. With R examples. 2nd ed. (English) Zbl 1096.62088
New York, NY: Springer (ISBN 0-387-29317-5/hbk; 978-1-4419-2125-3/pbk). xiii, 575 p. (2006).
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 dealing with the analysis of time-correlated data. This now available second edition of the book differs from the first edition from 2000, see the review Zbl 0942.62098, by several substantial changes. The most obvious change is the use of the freeware $$R$$ package. The authors nearly always describe how the examples can be treated in $$R$$. The $$R$$ code for the calculation of many time series characteristics is given. However, there are changes in the structure of the book as well. ARIMA processes are now handled in an own chapter and the treatment of GARCH models is expanded. Kernel based estimators and spectral window estimators have been included. The chapter on ARMAX models has been shortened. Several important theoretical results are summarized in an appendix and not, as in the first version, stated at the end of the chapters.
Overall the second edition has around 30 pages more than the first version. This is not very much. Because of the numerous changes in the structure of the book the presentation has improved. The consideration of new material makes it more attractive as well. Moreover, the use of the $$R$$ package permits the analysis of interesting examples and makes the book more interesting as a textbook.

##### MSC:
 62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH) 62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics 62-04 Software, source code, etc. for problems pertaining to statistics 62-02 Research exposition (monographs, survey articles) pertaining to statistics 62-08 Computational methods for problems pertaining to statistics
##### Software:
astsa; CRAN; ggplot2; R; RStudio