Code 6
During the workshop you introduced the mxTryHard() command instead of mxRun(), which I read
can be useful when mxRun() returns a code 6.
I am running a bivariate saturated model with binary data. The main saturated model I run seems to run better, but when I use mxTryHard() for sub-models the messages look like this:
Begin fit attempt 1 of at maximum 11 tries
Lowest minimum so far: 3159.84949759196
OpenMx status code 6 not in list of acceptable status codes, 0
OpenMx status code 6 not in list of acceptable status codes, 0
Not all eigenvalues of Hessian are greater than 0: 857539769.124727, 779.642587546502, 519.066582133804, 435.512846233224, 323.277652451376, 272.947636007993, 231.580861937549, 199.287427329626, 182.359108855876, 173.067247762125, 130.141272120151, 102.045389085597, 98.4601557344951, -4511164.96705233
New attempts then either return code 6s or "fit attempt generated errors".
Each time I re-run the model like this, I get different -2LL and p-values, when I compare models. I am not sure how to react to these error messages and the fact that estimates change from run to run. Also, I don't know what this tells me about my data.
Any guidance would be appreciated!
Concerning status code 6
In your case specifically...
mxTryHardOrdinal()
instead ofmxTryHard()
; it has default argument values intended specifically for threshold data.Without seeing the script you're using, I can't really suggest anything further.
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In reply to Concerning status code 6 by AdminRobK
mxTryHardOrdinal()
mxTryHardOrdinal()
instead ofmxTryHard()
, or at least, usemxTryHard()
with argumentfinetuneGradient=FALSE
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In reply to Concerning status code 6 by AdminRobK
Thank you! This has helped!
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Try tweaking integration parameters
http://openmx.psyc.virginia.edu/thread/3868
However, I would note that code 6 is very common with ordinal data problems, even after try hard. Usually the solution IS a global minimum, or extremely close to it, but the precision isn't quite there for the optimizer to declare happiness with the solution.
That said, we are exploring alternatives to FIML analysis as currently implemented. You may want to check out the weighted least squares approaches now available, or wait to see what the next 6 months of development bring ;).
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In reply to Try tweaking integration parameters by neale
Thank you!!
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code 6
Hello all
when I want to fit my model, I receive this warning message:
In model 'group1' Optimizer returned a non-zero status code 6. The model does not satisfy the first-order optimality conditions to the required accuracy, and no improved point for the merit function could be found during the final linesearch (Mx status RED)
I would be really happy, if someone helped me.
thanks
yenni
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In reply to code 6 by yenni
mxTryHard
A hint to help you code:
HTHmanifestVars<-paste0("V",1:16)
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