The SSM Procedure
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Overview
- Getting Started
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Syntax
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DetailsState Space Model and NotationTypes of Sequence DataOverview of Model Specification SyntaxFiltering, Smoothing, Likelihood, and Structural Break DetectionEstimation of User-Specified Linear Combination of State ElementsContrasting 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 Panel Data: Random-Effects and Autoregressive ModelsBackcasting, Forecasting, and InterpolationLongitudinal Data: Smoothing of Repeated MeasuresA User-Defined Trend ModelModel with Multiple ARIMA ComponentsDynamic Factor ModelingDiagnostic Plots and Structural Break AnalysisLongitudinal Data: Variable Bandwidth SmoothingA Transfer Function Model for the Gas Furnace DataPanel Data: Dynamic Panel Model for the Cigar DataMultivariate Modeling: Long-Term Temperature TrendsBivariate Model: Sales of Mink and Muskrat FursFactor Model: Now-Casting the US EconomyLongitudinal Data: Lung Function Analysis
- References
To define the model, you can use most of the programming statements that are allowed in the SAS DATA step. See the SAS Language Reference: Dictionary for more information. For the most part, the syntax of programming statements used in PROC SSM is identical to that used in the MODEL procedure (see Chapter 19: The MODEL Procedure) and the NLMIXED procedure (see Chapter 70: The NLMIXED Procedure in SAS/STAT 13.2 User's Guide). However, there are some restrictions: the DATA step lagging and differencing functions are not allowed, and the use of character variables in the DATA step expressions is not permitted. These are not serious restrictions; usually you can overcome them by adding the variables that are created by such operations to the input data set before its use in the SSM procedure.