[R-sig-ME] new R user struggling with error and convergence issues
bbolker at gmail.com
Mon Feb 15 21:21:03 CET 2016
It is admittedly hard to increase the "maxstephalfit" parameter, but
part of the reason we haven't put much effort into making it easier is
that in our experience it rarely helps. Log-binomial models in
particular are tricky because the log link (i.e. the exponential
inverse-link) doesn't naturally constrain the response to the allowed
range of (0,1), so these models are hard to fit (the same applies to
inverse-link Gamma models). The bigger your data set, the more likely
you are to run into cases where the predicted value is >1. We could
admittedly do a much better job giving useful warnings about when and
where this problem occurred, and (more controversially) allow users to
clamp the output of the inverse-link function to the allowable domain
dd <- data.frame(x=seq(-4,4,length=500),
dd$y <- simulate(~x+(1|f),family=binomial,
m1 <- glmer(y~x+(1|f), dd, family=binomial)
m2 <- glmer(y~x+(1|f), dd, family=binomial(link="log")) ## PIRLS
On Mon, Feb 15, 2016 at 2:22 PM, Jennifer Yourkavitch via
R-sig-mixed-models <r-sig-mixed-models at r-project.org> wrote:
> I am fitting multilevel log-binomial models for a very large dataset (>53,000 observations), using glmer. I am getting this-- Error: (maxstephalfit) PIRLS step-halvings failed to reduce deviance in pwrssUpdate.
> And the model is not converging.
> I think that increasing the number of iterations may remediate the convergence issue. But I can’t find the right syntax for that online.
> Any advice re these two issues?
> Many thanks,
> R-sig-mixed-models at r-project.org mailing list
More information about the R-sig-mixed-models