[size=1em]calculating PRESSp (prediction sum of squares) criterion

Hi all,

As I'm doing a regression in which I want to reduce my current amount of possible parameters, I wanted to run a kind of best-subset algorithm in that I want to evaluate (and plot) each possible combination of regression parameters using some model selection criteria as R2 (adjusted), MSE, Cp, AICp, SBCp and PRESSp.

As such, I am now able to generate a listing of all possible regression parameter combinations and evaluating them against R2, R2 adjusted, Cp, MSE and SSE using the following command:

proc reg data=model2 outest=temp;

model lny = X3-X8 X12-X23 X4X16 /selection=rsquare adjrsq cp press mse sse;

plot cp.*np.;

plot rsq.*np.;

plot mse.*np.;

run;

quit;

However, I would really like to have the PRESSp (preidction sum of squares) value calculated (which to former command apparently doesn't do?) and plotted and, if possible, also Akaike's information criterion (AICp) and Schwarz' Bayesian criterion (SBCp).

Could anyone please help?

Kind regards,

Peter