SAS/Ets User's Guide 228. Provides detailed reference material for using SAS/ETS software and guides you through the analysis and forecasting of features such as univariate and multivariate time series, cross-sectional time series, seasonal adjustments, multiequational nonlinear models, discrete choice models, limited dependent variable models, portfolio analysis, and generation of financial reports, with introductory and advanced examples for each procedure. You can also find complete information about two easy-to-use point-and-click applications: the Time Series Forecasting System, for automatic and interactive time series modeling and forecasting, and the Investment Analysis System, for time-value of money analysis of a variety of investments | 2262 F Chapter 33 The X11 Procedure macurves dec 3x9 would require five additional December values to compute the seasonal moving average. Details of Model Selection If an ARIMA statement is present but no MODEL is given PROC X11 estimates and forecasts five predefined models and selects the best. This section describes the details of the selection criteria and the selection process. The five predefined models used by PROC X11 are the same as those used by X11ARIMA 88 from Statistics Canada. These particular models shown in Table were chosen on the basis of testing a large number of economics series Dagum 1988 and should provide reasonable forecasts for most economic series. Table Five Predefined Models Model Specification Multiplicative Additive 1 0 1 1 0 1 1 s log transform no transform 2 0 1 2 0 1 1 s log transform no transform 3 2 1 0 0 1 1 s log transform no transform 4 0 2 2 0 1 1 s log transform no transform 5 2 1 2 0 1 1 s no transform no transform The selection process proceeds as follows. The five models are estimated and one-step-ahead forecasts are produced in the order shown in Table . As each model is estimated the following three criteria are checked The mean absolute percent error MAPE for the last three years of the series must be less than 15 . The significance probability for the Box-Ljung chi-square for up to lag 24 for monthly 8 for quarterly must greater than . The over-differencing criteria must not exceed . The descriptions of these three criteria are given in the section Criteria Details on page 2263. The default values for these criteria are those used by X11ARIMA 88 from Statistics Canada these defaults can be changed by the MAPECR CHICR and OVDIFCR options. A model that fails any one of these three criteria is excluded from further consideration. In addition if the ARIMA estimation fails for a given model a warning is issued and the model is excluded. The final set of all models considered consists of those that pass
