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| Danming An posted on Thursday, December 01, 2016 - 3:43 pm
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I am running a simulation study for Beyesian SEM. I constrained some priors using model constraint because in this case there's a strong prior belief that some parameters are larger than zero.
I get a few error messages as below in Tech9 output and wonder how to interpret them.
REPLICATION 230:
THE MODEL ESTIMATION DID NOT TERMINATE NORMALLY.
UNABLE TO GENERATE PARAMETERS SATISFYING THE CONSTRAINTS.
CHECK THE STARTING VALUES.
THE PROBLEM OCCURRED IN CHAIN 1.
Thank you! |
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| Danming An posted on Thursday, December 01, 2016 - 3:46 pm
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For reference here's the model setup:
MONTECARLO:
NAMES ARE x1 x2 y1 y2;
NOBSERVATIONS = 100;
NREPS = 1000;
SEED = 1109;
MODEL POPULATION:
[x1*0];
[x2*0];
[y1*0];
[y2*0];
x1*1;
x2*1;
y1*.978;
y2*.978;
y1 on x1*.1 x2*.1;
y2 on x1*.1 x2*.1;
x1 with x2*.1;
y1 with y2*.1;
ANALYSIS:
ESTIMATOR = BAYES;
FBITERATIONS = 1000;
MODEL:
[x1*0](m);
[x2*0](m);
[y1*0](m);
[y2*0](m);
x1*1(varx1);
x2*1(varx2);
y1*.978(residy1);
y2*.978(residy2);
y1 on x1*.1(a1);
y1 on x2*.1(p1);
y2 on x1*.1(p2);
y2 on x2*.1(a2);
x1 with x2*.1 (rx);
y1 with y2*.1 (ry);
MODEL PRIORS:
a1~N(0,.05);
p1~N(0,.05);
a2~N(0,.05);
p2~N(0,.05);
rx~N(0,.01);
ry~N(0,.01);
m~N(0,0.01);
varx1~IG(.001,.001);
varx2~IG(.001,.001);
residy1~IG(.001,.001);
residy2~IG(.001,.001);
model constraint:
a1>0; a2>0;
p1>0; p2>0; |
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