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st: RE : different results with mL : a seed problem?
From
Valerie Orozco <Valerie.Orozco@toulouse.inra.fr>
To
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject
st: RE : different results with mL : a seed problem?
Date
Wed, 28 Sep 2011 18:34:33 +0000
Dear all,
I have a question concerning my ml program. I obtain different results whether I run ml check and ml search or not or dependingon the initial seed given.
In the 3 examples below, I show you that the results really differ (opposite sign for tau1 and tau2). It will be more reasonablethat Tau1 and Tau2 were positive and between
0 and 1 (but I don't want to impose it).
Do you have some idea? How to justify that and what can I do ?
Thank you very much for your help.
Valérie
CASE 1 : OK
/* log likelihood -193.6561493493679*/
set seed A
ml model d0 MyProg (mode=$ensx $ensz,nocons) /tau1 /tau2 ,technique(dfp)
ml maximize , iterate(200) ltolerance(1e-3)
------------------------------------------------------------------------------
mode | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
eq1 |
IndAir | 6.042543 1.198887 5.04 0.000 3.692767 8.392319
IndTrain | 5.06453 .6620514 7.65 0.000 3.766933 6.362127
IndBus | 4.096175 .615164 6.66 0.000 2.890476 5.301874
gc | -.0315903 .0081573 -3.87 0.000 -.0475784 -.0156023
ttme | -.1126117 .0141289 -7.97 0.000 -.1403039 -.0849196
air_inc | .0153227 .0093814 1.63 0.102 -.0030646 .03371
-------------+----------------------------------------------------------------
tau1 |
_cons | .5860276 .1406654 4.17 0.000 .3103285 .8617267
-------------+----------------------------------------------------------------
tau2 |
_cons | .3889992 .123669 3.15 0.002 .1466124 .631386
------------------------------------------------------------------------------
CASE 2 : Pb with ml check and ml search when seed A
/* log likelihood -208.2651378345047*/
set seed A
ml model d0 MyProg (mode=$ensx $ensz,nocons) /tau1 /tau2 ,technique(dfp)
ml check
ml search
ml maximize , iterate(200) ltolerance(1e-3)
------------------------------------------------------------------------------
10
mode | Coef. Std. Err. z P>|z| [95% Conf.
Interval]
-------------+----------------------------------------------------------------
eq1 |
IndAir | 6.466593 2.519553 2.57 0.010 1.52836 11.40483
IndTrain | 1.720836 .7418628 2.32 0.020 .266812 3.174861
IndBus | .1836824 .7124329 0.26 0.797 -1.21266 1.580025
gc | -.069042 .0123095 -5.61 0.000 -.0931682 -.0449158
ttme | .0127155 .013757 0.92 0.355 -.0142478 .0396787
air_inc | .0366201 .0097708 3.75 0.000 .0174698 .0557705
-------------+----------------------------------------------------------------
tau1 |
_cons | -.8089981 .3672655 -2.20 0.028 -1.528825 -.0891709
-------------+----------------------------------------------------------------
tau2 |
_cons | -.430628 .2085702 -2.06 0.039 -.839418 -.0218379
------------------------------------------------------------------------------
CASE 3 : OK with ml check and ml search when other seed
/* log likelihood -193.6562582125274 */
set seed B
ml model d0 MyProg (mode=$ensx $ensz,nocons) /tau1 /tau2 ,technique(dfp)
ml check
ml search
ml maximize , iterate(200) ltolerance(1e-3)
------------------------------------------------------------------------------
mode | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
eq1 |
IndAir | 6.040651 1.201523 5.03 0.000 3.685708 8.395594
IndTrain | 5.068941 .6620243 7.66 0.000 3.771397 6.366485
IndBus | 4.09906 .6151253 6.66 0.000 2.893437 5.304684
gc | -.0316954 .0081707 -3.88 0.000 -.0477096 -.0156812
ttme | -.1126556 .0141305 -7.97 0.000 -.1403508 -.0849604
air_inc | .0153522 .0093765 1.64 0.102 -.0030254 .0337297
-------------+----------------------------------------------------------------
tau1 |
_cons | .5843276 .1401245 4.17 0.000 .3096886 .8589666
-------------+----------------------------------------------------------------
tau2 |
_cons | .3879414 .1233578 3.14 0.002 .1461646 .6297182
------------------------------------------------------------------------------
-------------------------------
Valérie OROZCO
Toulouse School of Economics (INRA-GREMAQ)
21, allée de Brienne
F-31000 Toulouse, France
MF 219
+33 5 61 12 85 91
-------------------------------
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