[R] fitting generalized linear models using glmmPQL

[Spencer Graves]

	  I have not seen your particular error message often enough to be 
confident I know what caused it:
 >
 > Error: NA/NaN/Inf in foreign function call (arg 1)
 > In addition: Warning message:
 > step size truncated due to divergence 	

	  In this case, the "Warning" seems more informative to me than the 
actual "Error".  The function "glmmPQL" is an iterative algorithm.  The 
"warining says that "step size truncated due to divergence.  This kind 
of warning might occur when the iteration found a long, gently sloping 
plateau and tried to take a giant step to get beyond it.  The algorithm 
decided that the giant step was too large, and so tried to truncate it.

	  Since I don't have your data, I can only guess at what might have 
caused it.  My first guess is that you have the wrong model.  Have you 
considered the following:

modelo1a<-glmmPQL(DE ~ POB*TEMP*SALINITA, data = datos, random =
  ~ POB|CLON, family = poisson)

	  Putting nesting with the random effect in the 'fixed' model makes not 
sense to me and generates an explosion of the number of "fixed effect" 
parameters to be estimated.  This might cause your problem all by itself.

	  If that doesn't solve the problem, have you tried to get a separate 
fit for each level of "CLON" of the same fixed model, something like the 
following:

(CLON.count <- table(datos$CLON))
n.CLON <- length(CLON.count)
glm.fits <- vector(n.CLON, mode="list")
for(i in 1:n.CLON)
    glm.fits[[i]] <- try(glm(DE ~ POB*TEMP*SALINITA, data = 
datos[datos$CLON==names(CLON.count[i])))

	  Under certain circumstances, "glmmPQL" could still return a good 
answer even if "glm" returned an error for every level of CLON in this 
loop.  However, that's far from certain.

	  Also, have you tried changing the two "*" operators to "+" in the 
fixed formula?  This reduces the number of parameters to be estimated 
and might give you sensible results.

	  If you are NOT using the latest version of R with the latest versions 
of MASS and nlme, please upgrade before submitting another post.  And 
PLEASE do read the posting guide! 
"www.R-project.org/posting-guide.html", especialy the bit about 
providing a simple, self contained example.  I sometimes solve problems 
like this in the course of trying to prepare a simple example.

	  hope this helps.
	  spencer graves	

Eduardo.Garcia at uv.es wrote:

> Hi, I have tried to run the following (I know it's a huge data set but 
> I tried to perform it with a 1 GB RAM computer):
> 
> library(foreign)
> library(MASS)
> library(nlme)
> datos<-read.spss(file="c:\\Documents and 
> Settings\\Administrador\\Escritorio\\datosfin.sav",to.data.frame=TRUE)
> str(datos)
> 
> `data.frame':   1414 obs. of  5 variables:
>  $ POB     : Factor w/ 6 levels "CHI","HOS","HYR",..: 1 1 1 1 1 1 1 1 
> 1 1 ...
>  $ CLON    : num  1 1 1 1 1 1 1 1 2 2 ...
>  $ TEMP    : Factor w/ 2 levels "20 C","25 C": 1 1 1 1 2 2 2 2 1 1 ...
>  $ SALINITA: Factor w/ 2 levels "15 g/l","30 g/l": 1 1 2 2 1 1 2 2 1 
> 1 ...
>  $ DE      : num  17 0 7 1 15 28 4 14 13 16 ...
>  - attr(*, "variable.labels")= Named chr  "" "" "" "" ...
>   ..- attr(*, "names")= chr  "POB" "CLON" "TEMP" "SALINITA" ...
> 
> datos$CLON<-as.factor(datos$CLON)
> 
> modelo1<-glmmPQL(DE ~ (POB/CLON)*TEMP*SALINITA, data = datos, random = 
> ~ 1|CLON, family = poisson)
> 
> And I have obtained the following:
> 
> Error: NA/NaN/Inf in foreign function call (arg 1)
> In addition: Warning message:
> step size truncated due to divergence 
> 
> This is the first time I've observed such a message and I have no idea 
> about what does it mean. Is it possible that the process failed 
> because of the size of the data set (180 levels of the CLON factor)? 
> Or maybe is it a syntax problem?
> 
> Thank you in advance.
> 
> 
> ********************************
> Eduardo Moisés García Roger
> 
> Institut Cavanilles de Biodiversitat i Biologia
> Evolutiva - ICBIBE.
> Tel. +34963543664
> Fax  +34963543670
> 
> ______________________________________________
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