Time Series Model Package
TSMSTAT Object
The TSMSTAT object collects model statistics of fit from a TSM object, TSMObj, and stores them in an output table. This information is useful for evaluating how well the model fits the dependent series. For more information about forecast fit statistics, see the section "Statistics of Fit" in Chapter 17, Forecasting Details (SAS Visual Forecasting: Time Series Packages).
Table 17 shows the contents of the TSMSTAT object.
Table 17: Contents of the TSMSTAT Object
| Column | Type | Description |
|---|---|---|
| _NAME_ | String | Name of the dependent variable |
| _REGION_ | String |
Region in which the fit statistics are calculated. You can specify the following values:
|
| _MODEL_ | String | Model name |
| AADJRSQ | Numeric | Amemiya’s adjusted R-square |
| ADJRSQ | Numeric | Adjusted R-square |
| AIC | Numeric | Akaike’s information criterion |
| AICC | Numeric | Finite sample corrected AIC |
| APC | Numeric | Amemiya’s prediction criterion |
| DFE | Numeric | Degrees of freedom error |
| GMAPE | Numeric | Geometric mean absolute percentage error |
| GMAPES | Numeric | Geometric mean absolute error as a percentage of standard deviation |
| GMAPPE | Numeric | Geometric mean absolute predictive percentage error |
| GMRAE | Numeric | Geometric mean relative absolute error |
| GMASPE | Numeric | Geometric mean absolute symmetric percentage error |
| IMASE | Numeric | In-sample mean absolute scaled error |
| MAE | Numeric | Mean absolute error |
| MAPE | Numeric | Mean absolute percentage error |
| MAPES | Numeric | Mean absolute error as a percentage of standard deviation |
| MAPPE | Numeric | Mean absolute predictive percentage error |
| MASE | Numeric | Mean absolute scaled error |
| MAXAPES | Numeric | Maximum absolute error as a percentage of standard deviation |
| MAXERR | Numeric | Maximum error |
| MAXPE | Numeric | Maximum percentage error |
| MAXPPE | Numeric | Maximum predictive percentage error |
| MAXRE | Numeric | Maximum relative error |
| MAXSPE | Numeric | Maximum symmetric percentage error |
| MDAPE | Numeric | Median absolute percentage error |
| MDAPES | Numeric | Median absolute error as a percentage of standard deviation |
| MDAPPE | Numeric | Median absolute predictive percentage error |
| MDASPE | Numeric | Median absolute symmetric percentage error |
| MDRAE | Numeric | Median relative absolute error |
| ME | Numeric | Mean error |
| MINAPES | Numeric | Minimum absolute error as a percentage of standard deviation |
| MINERR | Numeric | Minimum error |
| MINPE | Numeric | Minimum percentage error |
| MINPPE | Numeric | Minimum predictive percentage error |
| MINRE | Numeric | Minimum relative error |
| MINSPE | Numeric | Minimum symmetric percentage error |
| MPE | Numeric | Mean percentage error |
| MPPE | Numeric | Mean predictive percentage error |
| MRAE | Numeric | Mean relative absolute error |
| MRE | Numeric | Mean relative error |
| MSE | Numeric | Mean square error |
| MSPE | Numeric | Mean symmetric percentage error |
| N | Numeric | Number of observations that were used. This is the number of observations in the block of observations from the first to the last nonmissing error, which includes any embedded missing errors. |
| NMISSA | Numeric | Number of missing actual values |
| NMISSP | Numeric | Number of missing predicted values |
| NOBS | Numeric | Number of observations |
| NPARMS | Numeric | Number of parameters |
| RMSE | Numeric | Root mean square error |
| RMSSE | Numeric | Root mean square scaled error |
| RSQUARE | Numeric | R-square |
| RWRSQ | Numeric | Random walk R-square |
| SBC | Numeric | Schwarz Bayesian information criterion |
| SMAPE | Numeric | Symmetric mean absolute percentage error |
| SSE | Numeric | Sum of square error |
| SST | Numeric | Corrected total sum of squares |
| TSS | Numeric | Total sum of squares |
| UMSE | Numeric | Unbiased mean square error |
| URMSE | Numeric | Unbiased root mean square error |
Table 18 summarizes the methods that are associated with the TSMSTAT object.
Table 18: Methods of the TSMSTAT Object
Figure 12 illustrates the data flow through the TSMSTAT object.
Figure 12: TSMSTAT Object Data Flow
