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.

David Jones


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