Glen wrote:
> "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

No, I meant residuals, as opposed to fitted residuals (which may be
what you mean by "residuals").

David Jones


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