Automatic Time Series Forecasting

Introduction

Automatic Time Series Forecasting

The FORECAST procedure provides forecasting of univariate time series using automatic trend extrapolation. PROC FORECAST is an easy-to-use procedure for automatic forecasting that uses simple popular methods that do not require statistical modeling of the time series, such as exponential smoothing, time trend with autoregressive errors, and the Holt-Winters method.

The FORECAST procedure supplements the powerful forecasting capabilities of the econometric and time series analysis procedures described above. You can use PROC FORECAST when you have many series to forecast and want to extrapolate trends without developing a model for each series.

The FORECAST procedure includes the following features:

choice of the following four forecasting methods:
- exponential smoothing: single, double, triple, or Holt two-parameter smoothing
- stepwise autoregressive models with constant, linear, or quadratic trend and autoregressive errors to any order
- Holt-Winters forecasting method with constant, linear, or quadratic trend
- additive variant of the Holt-Winters method
support for up to three levels of seasonality for Holt-Winters method: time-of-year, day-of-week, or time-of-day
ability to forecast any number of variables at once
forecast confidence limits for all methods

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