Addendum: I tried a gamma fit in glmmPQL and got the same errors. *Ben Caldwell*
PhD Candidate University of California, Berkeley On Tue, May 17, 2011 at 3:51 PM, Benjamin Caldwell <btcaldw...@berkeley.edu>wrote: > Hello > After seeing this ( > https://stat.ethz.ch/pipermail/r-sig-mixed-models/2011q1/005213.html) email > I thought I would check the issue with a gamma family in lme4 hadn't been > fixed; can I fit a hierarchical gamma model in lme4 at this time? There > doesn't seem to be another package capable of it at this time. > > My thought process: > 1. took a look at the response variable and some subsets to see what it > looked like, ("bppfcl" and "transformed response var"), attached > 2. took a look at a gamma and gaussian fit to the response variable. > 3. ran hierarchical gaussian model in nlme to look at residuals > (more familiar with graphs from that package) ("qqnorm" and "residuals") > > Given the residual output for the gaussian model it looks like I could > remove the values at the end of the distribution and get a decent fit. I'd > still like to try a gamma model though, if that's possible. Is it possible > in lme4 or another package I don't know about? > > ---This is the code I'm running--- > > rws30.BL$site <- factor(rws30.BL$site) > rws30.BL$transect <- interaction(rws30.BL$site, rws30.BL$transect, drop = > TRUE) > rws30.BL$plot <- interaction(rws30.BL$site, rws30.BL$transect, > rws30.BL$plot, drop = TRUE) > hist(rws30.BL$post.f.crwn.length) > rws30.BL$gpost.f.crwn.length > > library("nlme") > burnedmodel1.3<-lme(post.f.crwn.length~lg.shigo.av+dbh+leaf.area+ > bark.thick.bh+ht.any+ht.alive, > random=(~1|site/transect/plot),na.action=na.omit, data=rws30.BL) > Error: no valid set of coefficients has been found: please supply starting > values > In addition: Warning message: > In log(ifelse(y == 0, 1, y/mu)) : NaNs produced > > --- I thought the problem might be a convergence error, and so tried a > reduced model ---- > glmer(gpost.f.crwn.length~dbh+leaf.area+(1|site/transect/plot), > family=Gamma, na.action=na.omit, data=rws30.BL) > Error in mer_finalize(ans) : > mu[i] must be positive: mu = -0.00780625, i = 3 > > Any clarity I could get would be much appreciated. > > Best > > *Ben Caldwell* > > PhD Candidate > University of California, Berkeley > > > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
