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Re: st: [Mata newbie] optimize() vs -ml-


From   Antoine Terracol <Antoine.Terracol@univ-paris1.fr>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: [Mata newbie] optimize() vs -ml-
Date   Wed, 17 Oct 2007 10:54:14 +0200

Jeff,

again, thanks for your answer (I did post a reply to your answer a few hours ago, but it hasn't appearedon the list yet).

Playing with your code, I noticed that -optimize- is indeed faster than -ml- for small sample sizes, but that the reverse seems to be true for larger N

I ran a few simulations (-simulate-, 100 replications) with varying N.

Below is the results using -v2- and -d2- (the same pattern can be found with v1/d1 and v0/d0):

N=100
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
optimize | 100 .00423 .0069947 0 .016
ml | 100 .05278 .0082298 .046 .078

N=1000
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
optimize | 100 .03333 .0061727 .015 .062
ml | 100 .07604 .0079085 .062 .094

N=5000
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
optimize | 100 .16598 .015475 .14 .218
ml | 100 .18982 .014276 .171 .25

N=10000
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
optimize | 100 .33812 .0282104 .296 .422
ml | 100 .33324 .0244937 .296 .406

N=50000
Variable | Obs Mean Std. Dev. Min Max
-------------+--------------------------------------------------------
optimize | 100 2.00641 .2400445 1.625 2.875
ml | 100 1.73035 .2316291 1.406 2.719

Antoine


Jeff Pitblado, StataCorp LP wrote:


If Antoine can derive formulas for producing the gradient for an -ml- type
-d1- evaluator and the parameter level scores for an -optimize()- type -v1-
evaluator, a speed comparison will show that -ml- with -d1- and -optimize()-
with -v1- will be faster than -lf- and -v0-, respectively, and -optimize()-
will tend to be faster than -ml-.
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