02082cam a22002177a 4500020003200000020003500032020002300067020002600090082001600116100002300132245005000155250001200205260003400217300003200251505042600283520101900709650002501728650003401753700002001787856005701807 a0387759581 (acidfree paper) a9780387759586 (acidfree paper) a038775959X (ebook) a9780387759593 (ebook)04a519.55bCRY1 aCryer, Jonathan D.10aTime series analysis : with applications in R a2nd ed. aNew York :bSpringer,cc2008. axiii, 491 p. :bill., map ;0 aIntroduction -- Fundamental concepts -- Trends -- Models for stationary time series -- Models for nonstationary time series -- Model specification -- Parameter estimation -- Model diagnostics -- Forecasting -- Seasonal models -- Time series regression models -- Time series models of heteroscedasticity -- Introduction to spectral analysis -- Estimating the spectrum -- Threshold models -- Appendix: an introduction to R. a
"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 heteroscedasticty, 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." 0aTime-series analysis 0aR (Computer program language)1 aChan, Kung-sik.41uhttp://www.loc.gov/catdir/toc/fy0804/2008923058.html