000			03967nam a22003855i 4500
001			279418
003			MX-SnUAN
005			20160429153944.0
007			cr nn 008mamaa
008			150903s2008 xxu| o |||| 0|eng d
020			_a9780387759593 _99780387759593
024	7		_a10.1007/9780387759593 _2doi
035			_avtls000332648
039		9	_a201509030234 _bVLOAD _c201404122218 _dVLOAD _c201404091948 _dVLOAD _y201402041034 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA276-280
100	1		_aCryer, Jonathan D. _eautor _9303726
245	1	0	_aTime Series Analysis : _bWith Applications in R / _cby Jonathan D. Cryer, Kung-Sik Chan.
264		1	_aNew York, NY : _bSpringer New York, _c2008.
300			_axiv, 491 páginas _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aSpringer Texts in Statistics, _x1431-875X
500			_aSpringer eBooks
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.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aChan, Kung-Sik. _eautor _9303727
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9780387759586
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-0-387-75959-3 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942			_c14
999			_c279418 _d279418