As no-one more qualified has responded, I’ll offer the following.  I don’t think that Autometrics will do what you want (I think it’s designed specifically to avoid doing what you describe). 
 
  On a hopefully more helpful note I’ve bashed out the ox code below which may help you get started with your bulk model estimation.  With more thought the combinatorics could be handled more elegantly but the below should do the trick.  Nb I haven’t tested it, it may not even run!
 
#include <oxstd.h>
#import <packages/PcGive/pcgive_ects>
 
main()
{
        decl model = new PcGive();
        decl b;
        model.Load("C:/Temp/YourDataset.in7");
        model.Deterministic(-1);
        model.SetMethod(M_OLS);
 
        for(decl a=1; a < 256; ++a)
        {
                b = a;
                model.Deselect();
                model.Select(Y_VAR, {"DEPVAR", 0, 0});
                model.Select(X_VAR), {"CONSTANT", 0, 0}); //You may not want this
               
                if(b >= 128)
                {
                         model.Select(X_VAR, {"INDVAR8", 0, 0});
                        b -=128;
                }
                if(b >= 64)
                {
                         model.Select(X_VAR, {"INDVAR7", 0, 0});
                        b -=64;
                }
                if(b >= 32)
                {
                         model.Select(X_VAR, {"INDVAR6", 0, 0});
                        b -=32;
                }
                if(b >= 16)
                {
                         model.Select(X_VAR, {"INDVAR5", 0, 0});
                        b -=16;
                }
                if(b >= 8)
                {
                         model.Select(X_VAR, {"INDVAR4", 0, 0});
                        b -=8;
                }
                if(b >= 4)
                {
                         model.Select(X_VAR, {"INDVAR3", 0, 0});
                        b -=4;
                }
                if(b >= 2)
                {
                         model.Select(X_VAR, {"INDVAR2", 0, 0});
                        b -=2;
                }
                if(b >= 1)
                {
                         model.Select(X_VAR, {"INDVAR1", 0, 0});
                        b -=1;
                }
               
                //You need to adjust the sample selection as appropriate
                model.SetSelSampleByIndex(0,99);
               
                model.Estimate();
                println("Model " ~ sprint(a));
                model.TestSummary();
        }
 
        delete model;
}
 
Hope this helps
 
George Taylor
 
Senior Forecasting Analyst
Demand Forecasting
Eon Energy Solutions
 
 
 

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