SAS for Forecasting Time Series


Authors: John C. Brocklebank, David A. Dickey

Publisher: SAS Press/Wiley

A book that explains time series and SAS techniques for time series analysis to statisticians. The book includes many detailed examples to promote an intuitive understanding of time series.


2 Paperback (2003)

2 Paperback

Year: 2003

ISBN: 1-59047-182-2


Pages: 292

Publisher’s list price: 68.95


  • 1. Overview of Time Series
  • 2. Simple Models: Autoregression
  • 3. The General ARIMA Model
  • 4. The ARIMA Model: Introductory Applications
  • 5. The ARIMA Model: Special Applications
  • 6. State Space Modeling
  • 7. Spectral Analysis
  • 8. Data Mining and Forecasting

From the back cover

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.

Audience: Intermediate to advanced data analysts who use SAS software to perform univariate and multivariate time series analyses. This book is an ideal supplemental text for students in undergraduate- and graduate-level statistics courses.