the number of observed statistics in the mixture models
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Hi,
I am fitting a mixture model for a genetic association test that includes sibships of variable sizes, with observed and missing genotypes; the model specification is based on the Acemix2.R script.
I would like to know if it is possible to obtain the correct number of observed statistics without being necessary to specify it manually in the summary() function.
Also, the mixture models for 4 sibs are very slow (the sibship=4 mixture is a 27 component mixture). Could you give me some suggestions on how to optimize the code for running the scripts faster?
Thanks,
camelia
I am fitting a mixture model for a genetic association test that includes sibships of variable sizes, with observed and missing genotypes; the model specification is based on the Acemix2.R script.
I would like to know if it is possible to obtain the correct number of observed statistics without being necessary to specify it manually in the summary() function.
Also, the mixture models for 4 sibs are very slow (the sibship=4 mixture is a 27 component mixture). Could you give me some suggestions on how to optimize the code for running the scripts faster?
Thanks,
camelia
With regards to improving
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Camelia You make a good point
You make a good point - openMx should automatically detect that the same data are being used in different mxModel() mxData() commands, but only score the observed statistics ONCE. Something for Michael S to look at, methinks.
As far as making them run faster, you could try turning off standard errors and Hessian calculation with an mxOption
model <- mxOption(model, "Standard Errors", "No")
model <- mxOption(model, "Calculate Hessian", "No")
I would have thought the Hessian sufficient, as Standard Errors need the Hessian...
Of course if you want the errors, this won't help.
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In reply to Camelia You make a good point by neale
Oh, that's not a bug it's a
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In reply to Oh, that's not a bug it's a by mspiegel
Wow, cool, I didn't know
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your suggestions were very
camelia
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