[R-sig-ME] Lmer-model fails to converge

Ivar Herfindal ivar.herfindal at bio.ntnu.no
Thu Sep 4 17:06:38 CEST 2008


Dear Mixed-list

I am trying to fit a mixed linear model with the lmer-function in the 
lme4-packages. After fitting the model, I get this warning:
Warning message:
In mer_finalize(ans) : iteration limit reached without convergence (9)

By searching the R-archive, I found some sort of solution posted by 
Douglas Bates 
(http://finzi.psych.upenn.edu/R/Rhelp02a/archive/138008.html) which will 
provide a greater number of iterations. I therefore tried:

(newmodel <- .Call("mer_optimize", mylmermodel, PACKAGE = "lme4"))

The "FALSE" argument in Douglas Bates suggestion caused an error 
message, but it works fine without, and the model do now converge. 
However, I cannot figure out how to get the model from the last part of 
the iterations. That is, the .Call("mer_optimize"...) only print the 
verbose from the fitting process, but does not give an mer-object that I 
can evaluate and extract random and fixed effects from. Does anyone know 
if this "horrible hack" (Bates' own words) can give a mer-object or can 
I only use it to evaluate how far my initial model was from convergence? 
I am sorry that I cannot provide any example from my own data (the 
dataset is too large to attach), but I assume that any solution should 
be independent of the model or data.

Cheers

Ivar

SessionInfo
sessionInfo()
R version 2.7.2 (2008-08-25)
i386-pc-mingw32

locale:
LC_COLLATE=Norwegian (Bokmål)_Norway.1252;LC_CTYPE=Norwegian 
(Bokmål)_Norway.1252;LC_MONETARY=Norwegian 
(Bokmål)_Norway.1252;LC_NUMERIC=C;LC_TIME=Norwegian (Bokmål)_Norway.1252

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base    

other attached packages:
[1] mgcv_1.4-1         splancs_2.01-24    sp_0.9-26          
lme4_0.999375-26   Matrix_0.999375-13 lattice_0.17-13  

loaded via a namespace (and not attached):
[1] grid_2.7.2
 >




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