The SSM Procedure (Experimental)
-
Overview
- Getting Started
-
Syntax
-
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
-
Examples
- References
| Covariance Parameterization |
The covariance matrices specified by the COV and COV1 options in the STATE statement must be positive semidefinite. When these matrices are of general form and are not user-specified, they are internally parameterized by their Cholesky root. Suppose that 
, an 
positive semidefinite matrix of rank 
, is such a covariance matrix. Then, can always be written as
 |
where the (generalized) Cholesky root, 
, is an 
lower triangular matrix with nonnegative diagonal elements (that is, 
and 
). The SSM procedure parameterizes by the elements of its Cholesky root, which adds 
elements to the parameter vector 
.
Note: This procedure is experimental.