Forecasting is required in many situations.

This edition includes R code for each numerical example in addition to Appendix R, which provides a reference for the data sets and R scripts used in the text in addition to a tutorial on basic R commands and R time series.

This book covers the recent advancements in time series forecasting. The book includes theoretical as well as recent applications of time series analysis.

This is an introduction to time series that emphasizes methods and analysis of data sets.

From the author of the bestselling "Analysis of Time Series," Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods.

Including univariate and multivariate techniques, Applied Time Series Analysis provides data sets and program files that support a broad range of multidisciplinary applications, distinguishing this book from others.

The authors of this book harness the power of intelligent technologies individually and in combination.

Accompanying CD-ROM contains datasets in the floowing formats: ASCII, EXCEL, SAS, JMP, MINITAB, STATA, S-PLUS, EVIEWS.

The book introduces popular forecasting methods and approaches used in a variety of business applications. The book offers clear explanations, practical examples, and end-of-chapter exercises and cases.

Providing a clear explanation of the fundamental theory of time series analysis and forecasting, this book couples theory with applications of two popular statistical packages--SAS and SPSS.