The SELECTION=ELASTICNET option specifies the elastic net method, an extension of LASSO that estimates parameters based on a version of ordinary least squares in which both the sum of the absolute regression coefficients and the sum of the squared regression coefficients are constrained. If the model contains classification variables, then these corresponding effects can be split.

The CHOOSE=CVEX suboption of the SELECTION option specifies the predicted residual sum of square with k-fold external cross validation as the criterion for choosing the model. The STOP=L1 suboption of the SELECTION option is available for SELECT ION=LASSO or SELECTION=ELASTICNET; it stops selection at the step where the L1 criterion is equal to the value specified by the L1=value option.