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Re: simultaneous nonlinear regression of a lot of data


Thanks all!  this is what i ended up doing:

estvar[t_?NumericQ] :=
Total[EstimatedVariance /.
Table[NonlinearRegress[croppedcorrelation[[i]],
1/nn(y / (1 + t/m1) + (1 - y) / (1 + t/m2) ), t, {nn, y},
RegressionReport -> EstimatedVariance], {i, Length[gooddata]}];

then i found the minimum of estvar with respect to t.  it worked pretty
well.  thanks!


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