Książki

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.

Time Series Analysis: With Applications in R. Script files of R commands for each chapter are available for download

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.