[R-sig-ME] previous posts about error message in glmmADMB

Lena mwiederm at mtu.edu
Wed May 14 18:35:25 CEST 2014


Dear list,
I am still stuck on this. I am trying to run a GLMM on my data. 
Here are my models:
Test$N<-factor(Test$N)
Test$plot<-factor(Test$plot)
Test$subplot<-factor(Test$subplot)
resp<-cbind(Test$D,Test$A)
m1<glmmadmb(resp~N*T+(1|plot/subplot),data=Test,zeroInflation=FALSE,
family="binomial")
m2<glmmadmb(resp~N+T+
(1|pl/subplot),data=Test,zeroInflation=FALSE,family="binomial")

First (see my last post) I ran it using “glmmadmb” with zeroInflation, with
the known Error message. However, the calculations went through using the
same model but without zeroInflation. Now there were no significant
interactions, so I attempted to reduce the model by throwing them out. But
N+T again yielded in the previous error term: 

Parameters were estimated, but not standard errors were not: the most likely
problem is that the curvature at MLE was zero or negative Error in
glmmadmb(resp ~ N + T + (1 | plot/subplot), data = Test, zeroInflation =
FALSE,  : The function maximizer failed (couldn't find STD file)
Troubleshooting steps include (1) run with 'save.dir' set and inspect output
files; (2) change run parameters: see '?admbControl'
In addition: Warning message:
running command 'C:\WINDOWS\system32\cmd.exe /c "C:/Program
Files/R/R-3.0.2/library/glmmADMB/bin/windows32/glmmadmb.exe" -maxfn 500
-maxph 5 -noinit -shess' had status 1 

For the heck of it I also tried the glmmPQL and encountered the same problem
more or less instantly though (N*T worked N+T did not)

m3<-glmmPQL(resp~N*T,random=~1|plot/subplot,family=binomial,data=Test)
m4<-glmmPQL(resp~N+T,random=~1|plot/subplot,family=binomial,data=Test)

The glmer had, with more than 4 hours the longest calculation time and ended
with the longest error message. 

m5<-glmer(resp~N*T+(plot|subplot),data=Test,family=binomial)

Warning messages:
1: In commonArgs(par, fn, control, environment()) :
  maxfun < 10 * length(par)^2 is not recommended.
2: In optwrap(optimizer, devfun, start, rho$lower, control = control,  :
  convergence code 1 from bobyqa: bobyqa -- maximum number of function
evaluations exceeded
3: In (function (fn, par, lower = rep.int(-Inf, n), upper = rep.int(Inf,  :
  failure to converge in 10000 evaluations
4: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
  Model failed to converge with max|grad| = 269.495 (tol = 0.001)
5: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv,  :
  Model failed to converge: degenerate  Hessian with 26 negative eigenvalues

I have a hard time interpreting these error messages. Did anybody bump into
similar issues or is that just me? Any ideas on how to go about it are much
appreciated!
Thanks, Lena



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