The SYSLIN Procedure
- Overview
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Getting Started
An Example ModelVariables in a System of EquationsUsing PROC SYSLINOLS EstimationTwo-Stage Least Squares EstimationLIML, K-Class, and MELO EstimationSUR, 3SLS, and FIML EstimationComputing Reduced Form EstimatesRestricting Parameter EstimatesTesting ParametersSaving Residuals and Predicted ValuesPlotting Residuals -
Syntax
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Details
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Examples
- References
PROC SYSLIN does not compute new values for regressors. For example, if you need a lagged variable, you must create it with a DATA step. No values are computed by IDENTITY statements; all values must be in the input data set.
The input data set for most applications of the SYSLIN procedure contains standard rectangular data. However, PROC SYSLIN can also process input data in the form of a crossproducts, covariance, or correlation matrix. Data sets that contain such matrices are identified by values of the TYPE= data set option.
These special kinds of input data sets can be used to save computer time. It takes 
operations, where n is the number of observations and k is the number of variables, to calculate cross products; the regressions are of the order 
. When n is in the thousands and k is much smaller, you can save most of the computer time in later runs of PROC SYSLIN by reusing the SSCP matrix rather than
recomputing it.
The SYSLIN procedure can process TYPE=CORR, COV, UCORR, UCOV, or SSCP data sets. TYPE=CORR and TYPE=COV data sets, usually created by the CORR procedure, contain means and standard deviations, and correlations or covariances. TYPE=SSCP data sets, usually created in previous runs of PROC SYSLIN, contain sums of squares and cross products. See the SAS/STAT User’s Guide for more information about special SAS data sets.
When special SAS data sets are read, you must specify the TYPE= data set option. PROC CORR and PROC SYSLIN automatically set the type for output data sets; however, if you create the data set by some other means, you must specify its type with the TYPE= data set option.
When the special data sets are used, the DW (Durbin-Watson test) and PLOT options in the MODEL statement cannot be performed, and the OUTPUT statements are not valid.