Time Series Analysis With Applications in R

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 Statist...

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Bibliographic Details
Main Authors: Cryer, Jonathan D., Chan, Kung-Sik (Author)
Format: eBook
Language:English
Published: New York, NY Springer New York 2008, 2008
Edition:2nd ed. 2008
Series:Springer Texts in Statistics
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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245 0 0 |a Time Series Analysis  |h Elektronische Ressource  |b With Applications in R  |c by Jonathan D. Cryer, Kung-Sik Chan 
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505 0 |a 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 -- To Spectral Analysis -- Estimating The Spectrum -- Threshold Models 
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520 |a 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.  
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 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.  
520 |a 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 isthe author of Chaos: A Statistical Perspective (with Howell Tong) and numerous research papers