[EMAIL PROTECTED] (akhan) wrote in message news:<[EMAIL PROTECTED]>... > Sorry for cross-posting. > > I'm trying to fit the sum of two or three normal distributions to the > frequency distributions of my datasets. And I used the Nonlinear Least > Square Fitting in OriginPro 7.0 to acquire the values of the > parameters of the two functions for each dataset. I want to know is > there any way to know whether one model fitted the data better than > the other one. Someone has used F-test to do this, but I failed to get > access to any literature associated with that. Can anyone tell me the > formulation of the F-test in this situdation? > > BTW, as the models (especially the three-peak one) didn't fit some > datas very well, and I got several sets of values of the parameters > for one dataset, can F-test be applied here to select the best set of > values of the parameters? >
Nonlinear models can be touchy. I like an approximate randomization approach (or exact if the sample is small) and testing whether the SSerror is smaller than X% of the random permutations' SSerror for the test statistic. With different models I believe that that would translate to simply taking the one with the smallest p-value (for tests done with, say, 5000 permutations), although if there's a reference on that it would be helpful if someone posted it. . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
