Time series analysis : with applications in R
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Bibliographic Information
Time series analysis : with applications in R
（Springer texts in statistics）
Springer, c2008
2nd ed
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Note
Includes bibliographical references (p. 477-486) and index
Description and Table of Contents
Description
This book has been developed for a one-semester course usually attended by students in statistics, economics, business, engineering, and quantitative social sciences. A unique feature of this edition is its integration with the R computing environment. Basic applied statistics is assumed through multiple regression. Calculus is assumed only to the extent of minimizing sums of squares but a calculus-based introduction to statistics is necessary for a thorough understanding of some of the theory. Actual time series data drawn from various disciplines are used throughout the book to illustrate the methodology.
Table of Contents
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.
by "Nielsen BookData"