By SAS Publishing

The REG approach is a general-purpose approach for linear regression.

**Read Online or Download SAS STAT 9.2 User's Guide: The REG Procedure (Book Excerpt) PDF**

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**Extra info for SAS STAT 9.2 User's Guide: The REG Procedure (Book Excerpt)**

**Sample text**

VIF produces variance inflation factors with the parameter estimates. Variance inflation is the reciprocal of tolerance. See the section “Collinearity Diagnostics” on page 5549 for more detail. WHITE See the HCC option. XPX displays the X0 X crossproducts matrix for the model. The crossproducts matrix is bordered by the X0 Y and Y0 Y matrices. MTEST Statement < label: > MTEST < equation < , . . , equation > > < / options > ; where each equation is a linear function composed of coefficients and variable names.

If you specify the RIDGE= option, RESTRICT statements are ignored. RSQUARE has the same effect as the EDF option. SIMPLE displays the sum, mean, variance, standard deviation, and uncorrected sum of squares for each variable used in PROC REG. SINGULAR=n tunes the mechanism used to check for singularities. The default value is machine dependent but is approximately 1E 7 on most machines. This option is rarely needed. Singularity checking is described in the section “Computational Methods” on page 5578.

GROUPn are assigned to groups encountered in the MODEL statement. Variables not enclosed by braces are used as groups of a single variable. For example: model y={x1 x2} x3 / selection=stepwise groupnames=’x1 x2’ ’x3’; Another example: model y={ht wgt age} bodyfat / selection=forward groupnames=’htwgtage’ ’bodyfat’; HCC requests heteroscedasticity-consistent standard errors of the parameter estimates. You can use the HCCMETHOD= option to specify the method used to compute the heteroscedasticityconsistent covariance matrix.