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Re: st: How does STATA compute e(ll) ??
From
Nick Cox <[email protected]>
To
[email protected]
Subject
Re: st: How does STATA compute e(ll) ??
Date
Thu, 21 Feb 2013 14:56:56 +0000
First off, please note the correct spelling "Stata", as explained in
the Statalist FAQ you were asked to read before posting.
As you say, the simplest uses of the -regress- command can be thought
of straight applications of ordinary least-squares. But particularly
as a link to more advanced or more general work, Stata reports the
same results as they would be obtained under an equivalent assumption
of maximum likelihood and normal (Gaussian) errors.
Most of the code for -regress- is part of the executable and not .ado
code. So, my understanding is that -regress- is not built upon any use
of -ml-, but it's safe to assume that key results are exactly
equivalent to that way of writing the command. Somewhere in the
documentation, if I recollect correctly, this is used as an example.
Nick
On Thu, Feb 21, 2013 at 2:47 PM, Hsien-Yuan Hsu <[email protected]> wrote:
> When I use commend "regress", I assume OLS regression is conducted.
> Why does STATA report "e(ll) log likelihood under additional
> assumption of i.i.d. normal errors."? Does STATA automatically
> estimate parameter by using ML?
On Thu, Feb 21, 2013 at 6:08 PM, Nick Cox <[email protected]> wrote:
>> In addition, there is a book-length treatment at
>>
>> http://www.stata.com/bookstore/maximum-likelihood-estimation-stata/index.html
>>
>> and Stata's machinery for computing (log) likelihood is documented
>> under heading such as -ml-.
On Thu, Feb 21, 2013 at 9:21 AM, Nick Cox <[email protected]> wrote:
>>> e(ll) is what it says, the log likelihood. Any decent intermediate
>>> statistics text will explain.
On Thu, Feb 21, 2013 at 8:47 AM, Mark (Hsien-Yuan Hsu)
>>>> I apply commend "regress Y X" to analyze my data set.
>>>> I notice that STATA provide "e(ll) log likelihood under additional
>>>> assumption of i.i.d. normal errors."
>>>>
>>>> Does anyone know how STATA compute e(ll)? What does it mean? Any
>>>> information is appreciated.
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