[R-sig-ME] Avoid errors in pwrssUpdate ?

Ben Bolker bbolker at gmail.com
Wed Jun 13 10:54:45 CEST 2012


Pierre Morel <pier.morel at ...> writes:

> I am getting a lot of pwrssUpdate errors when trying to model my
> data with gmler (using the most recent version from svn... I don't
> know if the previous versions were affected).
 
> These errors are "PIRLS step failed" or "pwrssUpdate did not
> converge in 30 iterations". I understand that these means that the
> algorithm does not manage to work with my data, but there is a
> peculiar behavior, and my data doesn't seem too unreasonable to fit
> with the model I want to use, so I am wondering if the problem is on
> my side !
 
 [snip to make gmane happier]

> Here is the model I want to fit, which doesn't seem unreasonable
> given the figure (random slopes and intercepts for subjects) :
 
>  model<-glmer(cbind(RuleReach,NTrials-RuleReach)~RuleWeight+
>  (RuleWeight|Subject),data=rewardalldirsub,family=binomial)
 
> However this gives me the "pwrssUpdate did not converge in 30
> iterations" error.  What is surprinsing, is that if I do not use the
> rightmost points (RuleWeight of 1), the model converges, even though
> there are less datapoints and the remaining points are the noisiest
> (subjects follow the rule quite reliably when it has a weight of 1
> as you can see).
 
> Removing the correlation in the random effects works sometimes (but
> not on all my sub data sets), and having a random intercept only
> (which is obviously not correct) is the only thing that seems to
> work in all cases.
 
> Centering RuleWeight (ie having it between -1 and 1 instead of 0 and
> 1) doesn't work.  Any ideas on why this doesn't work / how to make
> it work ?

  Thanks for the report: this is an issue the developers are
(painfully) aware of, and working on.  The issue arises mostly when
the predictions for some observations are very close to 0 or 1 (which
explains why using the rightmost points helps ...)  You have tried all
the obvious things I know of.  I would additionally try (1) setting
starting values by hand and/or (2) trying out glmmADMB ...

  Ben Bolker



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