chi2gof function combines bins even with EMin set to zero

While running a chi-square test for certain data (with respect to the t-distribution) I set a certain number of bins as a standrd (5) and wanted to keep this despite low count in certain bins, which I did by setting EMin = 0 (as specified by the documentation). However even while doing this the function combines neighbouring bins from 5 to 2 (I assume due to the poor fit of the distribution to the data distibution).

This is what I wrote, given t a certain data set:

nparams = 0;
nbins = 5;

tdist = @(x) tpdf(x,n-2);

[H,p,stats] = chi2gof(t,'CDF',tdist,'nbins',nbins,'nparams',nparams,'emin',0);
disp(stats)
disp([H p])

This returns:

    chi2stat: 103.7404
          df: 1
       edges: [-4.0438 0.9718 2.2257]
           O: [47 11]
           E: [13.8933 44.1067]

where data is divided in 2 bins, despite the fact that I set nbins = 5 and emin = 0. Why does this happen? Can I change it to do it the way I want to? (I know this won't change the result, i.e. the null hypothesis is rejected at the given confidence level, but I still would want it to give the result I expect)

Answer 1

[Aditya Patil]

I have brought this issue to the notice of concerned developers. It might be fixed in any of the upcoming releases.

[Roberto Gargiulo]

Thanks a lot! I'm still very much interested in a fix (I had to do it "by hand" in this case, but it takes more time and lines to write the necessary code).