"Maximum Likelihood, Phil, *is* a really big workhorse of
statistical estimation, partly because the ML solutions
share certain fine characteristics ... which I don't call to
mind."
statistical estimation, partly because the ML solutions
share certain fine characteristics ... which I don't call to
mind."
We're sure you don't. Rumsfeld and Bush have similar problems. But I'll give you a hint: Focus on the fine characteristics--use estimating procedures that have them. (And MLE's do under extremely restrictive and unrealistic assumptions normally satisfied only in the academically large.)
Rich Ulrich <[EMAIL PROTECTED]> wrote:
Rich Ulrich <[EMAIL PROTECTED]> wrote:
On 18 Mar 2004 05:59:22 -0800, [EMAIL PROTECTED] (Phillip
Good) wrote:
> As I suspected you are unable to offer a single justification
> for your actions just as Rumsfield was unable to offer a single
> justification for his. Given your recklessness, may I recommend
> "Common Errors in Statistics (and How to Avoid Them)," Wiley, 2003.
>
> Phillip Good
[ snip, 145 lines of previous stuff - apparently starting with
the topic of Maximum Likelihood solutions.]
Top-posting is not the usual custom in the sci.stat.* groups.
Snipping out extraneous comments is a friendly custom -- I
am seldom pleased to see a 119-line post followed by 151-line
post, which is the same thing plus headers /tags plus 4 lines
of comment.
Maximum Likelihood, Phil, *is* a really big workhorse of
statistical estim! ation, partly because the ML solutions share
certain fine characteristics ... which I don't call to mind.
Now, were you saying that there are specific drawbacks
that make MLE (the solutions of today, ones which happen
to be popular) poor for the "Subject:" of Missing Data?
-- I have not heard of that, but I could listen to argument.
But I guess I would be a tough sell, if you are saying there
is something vastly wrong with MLE, in general.
--
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
- I need a new job, after March 31. Openings? -
.
.
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Phillip
Good
http.ms//www.statistician.usa
"Never trust anything that can think for itself if you can't see where it keeps its brain." JKR
http.ms//www.statistician.usa
"Never trust anything that can think for itself if you can't see where it keeps its brain." JKR
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