Time Series Forecasting System
SAS/ETS software includes the Time Series Forecasting System,
a point-and-click application for exploring and analyzing univariate time series
data. You can use the automatic model selection facility to select the
best-fitting model for each time series, or you can use the system's diagnostic
features and time series modeling tools interactively to develop forecasting
models customized to best predict your time series. The system provides both
graphical and statistical features to help you choose the best forecasting method
for each series.
The system can be invoked from the Solutions menu under Analysis, by the Forecast
command, and by the Forecasting icon in the Data Analysis folder of the SAS
Desktop.
The following is a brief summary of the features of the Time Series Forecasting
system. With the system you can
- use a wide variety of forecasting methods, including several kinds of
exponential smoothing models, Winters method, and ARIMA (Box-Jenkins) models. You
can also produce forecasts by combining the forecasts from several models.
- use predictor variables in forecasting models. Forecasting models can
include time trend curves, regressors, intervention effects (dummy variables),
adjustments you specify, and dynamic regression (transfer function) models.
- view plots of the data, predicted versus actual values, prediction errors,
and forecasts with confidence limits. You can plot changes or transformations of
series, zoom in on parts of the graphs, or plot autocorrelations.
- use hold-out samples to select the best forecasting method.
- compare goodness-of-fit measures for any two forecasting models side by side
or list all models sorted by a particular fit statistic.
- view the predictions and errors for each model in a spreadsheet or view and
compare the forecasts from any two models in a spreadsheet.
- examine the fitted parameters of each forecasting model and their
statistical significance.
- control the automatic model selection process: the set of forecasting models
considered, the goodness-of-fit measure used to select the best model, and the
time period used to fit and evaluate models.
- customize the system by adding forecasting models for the automatic model
selection process and for point-and-click manual selection.
- save your work in a project catalog.
- print an audit trail of the forecasting process.
- save and print system output including spreadsheets and graphs.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
