SAS Forecasting 2e - Softcover

Brocklebank, John C.

Softcover

ISBN 10: 0471395668 ISBN 13: 9780471395669

Publisher: John Wiley & Sons, 2003

Synopsis

Easy-to-read and comprehensive, this book shows how the SAS System performs multivariate time series analysis and features the advanced SAS procedures STATSPACE, ARIMA, and SPECTRA. The interrelationship of SAS/ETS procedures is demonstrated with an accompanying discussion of how the choice of a procedure depends on the data to be analysed and the reults desired. Other topics covered include detecting sinusoidal components in time series models and performing bivariate corr-spectral analysis and comparing the results with the standard transfer function methodology. The authors? unique approach to integrating students in a variety of disciplines and industries. Emphasis is on correct interpretation of output to draw meaningful conclusions. The volume, co-pubished by SAS and JWS, features both theory and practicality, and accompanies a soon-to-be extensive library of SAS hands-on manuals in a multitude of statistical areas. The book can be used with a number of hardware-specific computing machines including CMS, Mac, MVS, Opem VMS Alpha, Opmen VMS VAX, OS/390, OS/2, UNIX, and Windows.

About this title

About the Author

John C. Brocklebank is Mgr. of Stats. Training at the SAS Institute. David A. Dickey is Associate Professor of Statistics at North Carolina State University.

From the Back Cover

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, STRATESPACE, 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 and vector ARMA processes using the STATE-SPACE 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
• Expanded discussion of frequency domain analysis and cycles in data
• Data mining and forecasting with examples using SAS IntelliVisor
• Using the HPF procedure to automatically generate forecasts for several time series in one step

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
• Expanded discussion of frequency domain analysis and cycles in data
• Data mining and forecasting with examples using SAS IntelliVisor
• Using the HPF procedure to automatically generate forecasts for several time series in one step

Edition details

• Publisher: John Wiley & Sons
• Publication date: 2003
• Language: English
• ISBN 10: 0471395668
• ISBN 13: 9780471395669
• Binding: Paperback
• Edition number: 2
• Number of pages: 424