The SSM Procedure (Experimental)
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Overview
- Getting Started
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Syntax
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DetailsState Space Model and NotationTypes of Data OrganizationOverview of Model Specification SyntaxLikelihood, Filtering, and SmoothingContrasting PROC SSM with Other SAS Procedures Predefined Trend ModelsPredefined Structural ModelsCovariance ParameterizationMissing ValuesComputational IssuesDisplayed OutputODS Table NamesODS Graph NamesOUT= Data Set
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ExamplesBivariate Basic Structural Model Two-Way Random-Effects and Autoregressive Model for Panel DataBackcasting, Forecasting, and InterpolationSmoothing of Repeated Measures DataA User-Defined Trend ModelModel with Multiple ARIMA ComponentsDynamic Factor ModelingDiagnostic PlotsVariable Bandwidth Smoothing
- References
EVAL Statement
EVAL name = number1*variable1 + number2*variable2 + …</ options> ;
The EVAL statement defines a linear combination, named name, of the terms used in the right-hand side of a MODEL statement. You can specify any variables (for example, predictor variables
and names of components) in the expression of the EVAL statement; however, you cannot specify in this expression any observation
disturbances that are specified by the IRREGULAR statement. Suppose C1 and C2 are two components (defined by COMPONENT statements elsewhere in the program), T1 is a trend component, and X1 is a regression variable used in a model. The following are valid examples of the EVAL statement:
eval e1 = c1 - c2; eval e2 = t1 + c1 + x1; eval e2 = t1 + 2*c1 - 1.5*x1;
The estimates of linear combinations defined by the EVAL statement (for example, E1, E2, and E3) are output to the OUT= data set that is specified in the OUTPUT statement. In addition, you can print these estimates by
using the following PRINT= options: