The SSM Procedure (Experimental)
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Overview
- Getting Started
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Syntax
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Details
The State Space Model and Notation Types of Data Organization Overview of Model Specification Syntax Likelihood, Filtering, and Smoothing Contrasting PROC SSM with Other SAS Procedures Predefined Trend Models Predefined Structural Models Covariance Parameterization Missing Values Computational Issues Displayed Output ODS Table Names OUT= Data Set
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Examples
- References
| Functional Summary |
Table 27.1 summarizes the statements and options that control the SSM procedure. Most commonly needed scenarios are listed; see the individual statements for additional details.
Description |
Statement |
Option |
|---|---|---|
Data Set Options |
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Specifies the input data set |
DATA= |
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Writes series and component forecasts to an output data set |
OUT= |
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Model Specification |
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Specifies the index variable |
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Defines variables as model parameters |
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Specifies a response variable and the associated observation equation |
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Specifies a state subsection |
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Specifies the transition matrix of a state subsection |
T |
|
Specifies the disturbance covariance matrix of a state subsection |
COV |
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Specifies the size of the diffuse initial condition of a state subsection |
A1 |
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Specifies the initial covariance matrix of a state subsection |
COV1 |
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Specifies a state subsection for a predefined structural model |
TYPE= |
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Specifies a component |
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Specifies a predefined trend component |
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Controlling the Output |
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Specifies the significance level of the forecast confidence limits |
ALPHA= |
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Specifies a linear combination of components to be output |
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BY Groups |
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Specifies BY group processing |
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Note: This procedure is experimental.