# 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.

## Editions

2 Paperback (2003)

### 2 Paperback

**Year:** 2003

**ISBN:** 1-59047-182-2

**ISBN-13:**978-1-59047-182-1

**Pages:** 292

**Publisherâ€™s list price:** 68.95

#### Contents

- 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.