000			03887nam a22004215i 4500
001			978-0-387-75959-3
003			DE-He213
005			20250710084023.0
007			cr nn 008mamaa
008			100301s2008 xxu| s |||| 0|eng d
020			_a9780387759593 _a99780387759593
024	7		_a10.1007/978-0-387-75959-3 _2doi
082	0	4	_a519.5 _223
100	1		_aCryer, Jonathan D. _eauthor.
245	1	0	_aTime Series Analysis _h[recurso electrónico] : _bWith Applications in R / _cby Jonathan D. Cryer, Kung-Sik Chan.
264		1	_aNew York, NY : _bSpringer New York, _c2008.
300			_aXIV, 491p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringer Texts in Statistics, _x1431-875X
505	0		_aFundamental 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 -- To Spectral Analysis -- Estimating The Spectrum -- Threshold Models.
520			_aTime 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.
650		0	_aSTATISTICS.
650		0	_aMATHEMATICAL STATISTICS.
650	1	4	_aSTATISTICS.
650	2	4	_aSTATISTICAL THEORY AND METHODS.
700	1		_aChan, Kung-Sik. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387759586
830		0	_aSpringer Texts in Statistics, _x1431-875X
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-75959-3 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
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