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st: During simulations, what to do if the regression-based model does not converge?


From   "Tiago V. Pereira" <tiago.pereira@mbe.bio.br>
To   "Tiago V. Pereira" <tiago.pereira@mbe.bio.br>
Subject   st: During simulations, what to do if the regression-based model does not converge?
Date   Tue, 19 Jun 2012 18:42:55 -0300 (BRT)

Dear statalisters,

I am running some simulations and need to run -mvmeta-. In some cases,
-mvmeta- fails to converge, and the simulation stucks at a certain point
and doesn't finish until I manually cancel it.

Example (data given below):

[simulate data]

mvmeta b V, reml


Note: using method reml
Note: using variables b1 b2
Note: 22 observations on 2 variables

initial:       log likelihood = -6.0965061
rescale:       log likelihood = -6.0965061
rescale eq:    log likelihood =  1.5713054
Iteration 0:   log likelihood =  1.5713054
Iteration 1:   log likelihood =  1.5735159  (not concave)
Iteration 2:   log likelihood =  1.5735286  (not concave)
Iteration 3:   log likelihood =  1.5735293  (not concave)
Iteration 4:   log likelihood =  1.5735293  (not concave)
Iteration 5:   log likelihood =  1.5735293  (not concave)
Iteration 6:   log likelihood =  1.5735293  (not concave)
Iteration 7:   log likelihood =  1.5735293  (not concave)
.
.
.
.
[neverending]

If I run instead

. mvmeta b V, mm

I get the method-of-moments approach, which would be the best estimate if
the reml option doest not work.



The most intuitive algorithm would be

if [mvmeta b V, reml takes too much time to run] {

break

and continue as

mvmeta b V, mm
}

I have failed to find a solution to that Can you tell me if it is possible?

All the best,

Tiago

*/ ------------ example data ---------------------------------
input b1 b2 V11 V22 V12
.233144 .1990245 .13194766 .00934892 .00169556
-.28375212 .19690602 .21868578 .01441359 .00277669
.00327333 .01059937 .22549555 .01792554 .00327333
.50068392 .1364699 .16447968 .01013253 .00197968
.17374169 .24701389 .24077677 .02068396 .00466566
.50303291 .06834434 .20411383 .01143459 .00219075
-.45014787 .26331932 .14863599 .01185804 .00217135
.65685769 .33265554 .31337754 .01162247 .00226642
1.1248355 .06663273 .44921284 .02497867 .0047684
1.2422897 .2806992 .32947018 .01348576 .00254711
-.48948849 .24811046 .16104793 .01191982 .0022244
.260668 .3046892 .20409032 .01089658 .00207011
.31184814 .11819502 .19728779 .01629585 .00284334
-.34414868 .31684138 .28063149 .01408479 .00285371
-.01790121 .48026602 .21454526 .01923754 .00343415
.11029605 .06801034 .1932147 .01195094 .0023056
.04299536 .2128944 .28981034 .02116782 .00409606
-.30519299 .31617451 .24653605 .02153186 .00367891
.31049675 .10128629 .19748667 .01613425 .00304222
-.22549042 .15365738 .12865038 .00878746 .00166625
-.10485559 .15266178 .13572105 .00932605 .00179248
.62737876 .18297067 .1572774 .00949862 .00172184
end

*/ ------------ example data ---------------------------------













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