SAS for Forecasting Time Series

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.

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 Associ ation and a member of the Institute of Mathematical Statistics.