Time series analysis : with applications in R

Bibliographic Information

Time series analysis : with applications in R

Jonathan D. Cryer, Kung-Sik Chan

(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.

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