Bookmark and Share

Notice: On March 31, it was announced that Statalist is moving from an email list to a forum. The old list will shut down at the end of May, and its replacement, statalist.org is already up and running.


[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

st: Why does specifying "ml search" results in different estimates?


From   <kirin_guess@yahoo.com.tw>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Why does specifying "ml search" results in different estimates?
Date   Wed, 10 Apr 2013 05:07:50 +0100

Dear Statalists,

I’m compiling a model by using the command, “ml”, and the method is “d0”. (I don’t have analytical formulae of the score and hessian, so I can’t use “d1” or “d2”. The method “lf” is not suitable for my model.)

When maximising the log-likelihood, I found that specifying “ml search” resulted in different estimates, and the differences of some estimates were quite obvious. I’ve tried to specify more rigorous convergence criteria, but that didn’t solve the problem. Hence I’m seeking your advice. What would be the causes of this problem? How to solve/minimise it? Is it always better to use “ml search”, if I don’t care about the extra computation time?

Any suggestions are welcome, and thank you very much in advance.

Kirin

*
*   For searches and help try:
*   http://www.stata.com/help.cgi?search
*   http://www.stata.com/support/faqs/resources/statalist-faq/
*   http://www.ats.ucla.edu/stat/stata/


© Copyright 1996–2014 StataCorp LP   |   Terms of use   |   Privacy   |   Contact us   |   Site index