000			02131cam a22002417a 4500
020			_a0387759581 (acidfree paper)
020			_a9780387759586 (acidfree paper)
020			_a038775959X (ebook)
020			_a9780387759593 (ebook)
082	0	4	_a519.55 _bCRY
100	1		_aCryer, Jonathan D.
245	1	0	_aTime series analysis : with applications in R
250			_a2nd ed.
260			_aNew York : _bSpringer, _cc2008.
300			_axiii, 491 p. : _bill., map ;
505	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.
520			_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."
650		0	_aTime-series analysis
650		0	_aR (Computer program language)
700	1		_aChan, Kung-sik.
856	4	1	_uhttp://www.loc.gov/catdir/toc/fy0804/2008923058.html
942			_cBK
999			_c44475 _d44475