SAS for Forecasting Time Series, Second Edition - Softcover

John C.; Ph.D. Brocklebank; David A. Dickey

Softcover

ISBN 10: 1590471822 ISBN 13: 9781590471821

Publisher: SAS Institute, 2003

Synopsis

In this second edition of the indispensable SAS for Forecasting Time Series, Brocklebank and Dickey show you how SAS performs univariate and multivariate time series analysis. Taking a tutorial approach, the authors focus on the procedures that most effectively bring results: the advanced procedures ARIMA, SPECTRA, STATESPACE, and VARMAX. They demonstrate the interrelationship of SAS/ETS procedures with a discussion of how the choice of a procedure depends on the data to be analyzed and the results desired. With this book, you will learn to model and forecast simple autoregressive (AR) processes using PROC ARIMA, and you will learn how to fit autoregressive and vector ARMA processes using the STATESPACE and VARMAX procedures. Other topics covered include detecting sinusoidal components in time series models, performing bivariate cross-spectral analysis, and comparing these frequency-based results with the time domain transfer function methodology. New and updated examples in the second edition include retail sales with seasonality, ARCH models for stock prices with changing volatility, vector autoregression and cointegration models, intervention analysis for product recall data, expanded discussion of unit root tests and nonstationarity, and expanded discussion of frequency domain analysis and cycles in data.

About this title

About the Author

John C. Brocklebank, Ph.D., Research and Development Director of Analytic Solutions at SAS, joined SAS in 1981 and has been a SAS user since 1978. Dr. Brocklebank received his Ph.D. in statistics and mathematics from North Carolina State University in 1981. He is often invited to conferences to speak about time series and statistical methods. David A. Dickey, Ph.D., is Professor of Statistics at North Carolina State University, where he teaches graduate courses in statistical methods and time series. An accomplished SAS user since 1976 and a prolific author, Dr. Dickey is the co-inventor of the Dickey-Fuller test used in SAS/ETS software. He received his Ph.D. in statistics from Iowa State University in 1976. He is a fellow of the American Statistical Association and a member of the Institute of Mathematical Statistics.

Review

This second edition of a 1986 publication contains additions that update this book with advances in time series forecasting. New topics include the Augmented Dickey-Fuller test, the model identification methods ESACF, SCAN and MINIC, unequal variances in time series models, and cointegration. The revisions and reorganization to chapter seven, Spectral Analysis, improve readability and comprehension. The addition of the final chapter, 'Data Mining and Forecasting', provides an introduction to the menu driven Time Series Forecasting System. SAS users who model and forecast time series data should add this book to their collection, including owners of the first edition. --Barry A. Evans, Ph.D., Manager, Forecasting GlaxoSmithKline

Drs. Brocklebank and Dickey have not only done a great job of explaining how to use SAS in forecasting time series, but have also written a good practitioner's text illustrating perils and pitfalls and how to detect them. The authors start at ground zero with illustrated explanations and build to more difficult concepts in a logical progression. For the SAS enthusiast, there is a wealth of SAS code, followed by the SAS output from that code and an abundance of graphs to illustrate what is being seen. If you need a review of time series forecasting or an understanding of how SAS treats time series forecasting, this would be a good book to have on your shelf. --Dr. Alex K. Thompson, Senior Statistician

Edition details

• Publisher: SAS Institute
• Publication date: 2003
• ISBN 10: 1590471822
• ISBN 13: 9781590471821
• Binding: Paperback
• Language: English
• Edition number: 2
• Number of pages: 420