"David Jones" <[EMAIL PROTECTED]> wrote in message news:<[EMAIL PROTECTED]>... > praxis wrote: > > Hi all. > > > > Assuming I do a multiple regression using ML estimation instead of > > OLS, do I still need to meet all the assumptions like normal > > distribution assumption, linearity assumption, and/or > > homoscadesticity assumption? If yes, could anyone explain why? > > > > Thanks in advance. > > > > praxis > > No, or perhaps yes. > > If you are unable to "meet all the assumptions like normal > distribution assumption, linearity assumption, and/or > homoscadesticity assumption", then you need to be able to write down > a model which reflects the assumptions you are prepared to make, and > to be able to parameterise this model using few enough parameters that > ML estimation will be able to produce sensible estimates. You should > bear in mind the usual simple example cases where ML estimation > doesn't work (produces non-consistent estimates as the sample size > increases). > > BTW you forgot to mention the "independence of residuals" assumption.
I think you mean independence of something else, possibly errors, since the residuals are not independent (for starters, at least for normal theory regression, they add to zero). Glen . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
