So many options, hard to decide what to do. Any bottom-line suggestions?
Tentatively the following looks promising:
/selection=lasso stop=none choose=cvex cvmethod=random (10) modelaverage refit showpvals;
Can you use the at most succinct code to test your data at first place ?
something like
proc glmselect data = sas_3.combined_sorted;
class i_Day;
model i_50503 = i_Open--i_23604 / selection=stepwise ;
run;
After that ,add some more option you need ,and see which one generate the ERROR information.
Use PROC PLS if you have lots of correlated X variables. PLS handles the correlation better than any method using OLS or variable selection methods.
But in response to your exact question, the options in GLMSELECT (and every other procedure) are all to be used in specific situations and not in other sitautions, and you've given us no information about your situation.
Agree with Paige.
After running PROC PLS, you could get a table of variable importance ,pick up variables which VIP>0.8
ERROR: No sample yielded a valid model.
How can we possibly help? You haven't explained what you are trying to do, and we don't have your data. Even worse, I have very little experience with GLMSELECT and lots of experience with PLS.
Can you use the at most succinct code to test your data at first place ?
something like
proc glmselect data = sas_3.combined_sorted;
class i_Day;
model i_50503 = i_Open--i_23604 / selection=stepwise ;
run;
After that ,add some more option you need ,and see which one generate the ERROR information.
Thanks Ksharp, and all others here. You folks are wonderful.
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