[R-sig-ME] taking in account results of a gmml in despite of error warning about memory?

[ONKELINX, Thierry]

Dear Glenda,

As Chris allready mentioned: if spp has a lot of levels, then you are estimating a huge covariance matrix. Which might be the problem. Do you have different values for spp within a tree? If spp stands for species then that would be rarely the case (except for misclassification). If you have only on level of spp per tree, then you probably want something like (1|spp/tree) which stands for tree nested in spp.

Furthermore you might want to think again on the 3-way interaction term. Do you need it? And if so can you give a biological explanation? If not, I would omit it.

Best regards,

Thierry

ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
Thierry.Onkelinx at inbo.be
www.inbo.be

To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey

-----Oorspronkelijk bericht-----
Van: r-sig-mixed-models-bounces at r-project.org [mailto:r-sig-mixed-models-bounces at r-project.org] Namens glenda mendieta
Verzonden: maandag 28 november 2011 16:18
Aan: r-sig-mixed-models at r-project.org
Onderwerp: [R-sig-ME] taking in account results of a gmml in despite of error warning about memory?

Hi to everyone,

I have being trying to fit aglmm on binay and poisson data and when I run this model, with poisson data, the error below shows up. But still gives me results. Does this means that those are only partial results and shouldn't be taking into account, because the model didn't run fully?

>  glmmab.FMv<-glmer(abundance~c.census*avail.surface*abundance.prev 
> +(0+spp|tree), data=db.e_St, family=poisson(link=log))
Error: cannot allocate vector of size 183 Kb In addition:Warning messages:
1: In structure(list(message = as.character(message), call = call),  :
   Reached total allocation of 4061Mb: see help(memory.size)
2: In structure(list(message = as.character(message), call = call),  :
   Reached total allocation of 4061Mb: see help(memory.size)


I am using the latest version of R and R studio. As I have seen before that some complicated models don't run at all if I had already many other models as objects in the workspace, I did run this one with the minimum use of memory (just the database as an object). I also read that R is suppose to do not have memory problems any more, but I don't really know how to expand the use of memory by R on my pc. For what I observed with mem.limits() it appears unlimited (NA), but then if I type mem.limit(), 4061 shows up. Does that mean that I can not run those models in my pc at al?.
Here, some more info in the data:

Number of obs: 23407, groups:tree,89


Thanks to anyone who can shed some light on this,

Glenda Mendieta-Leiva
PhD candidate
University of Oldenburg


On 28/11/2011 12:00, r-sig-mixed-models-request at r-project.org wrote:
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>     1. Population fit with glm works fine: totally off with	glmer
>        (Dieter Menne)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Mon, 28 Nov 2011 08:21:44 +0000 (UTC)
> From: Dieter Menne<dieter.menne at menne-biomed.de>
> To: r-sig-mixed-models at r-project.org
> Subject: [R-sig-ME] Population fit with glm works fine: totally off
> 	with	glmer
> Message-ID:<loom.20111128T091939-576 at post.gmane.org>
> Content-Type: text/plain; charset=us-ascii
>
> Ben Bolker<bbolker at ...>  writes:
>
>>    This (using the aforementioned Dorie package)
>>
>> library(blme)
>> (fitbglmer<-   summary(g3<- bglmer(Satiated~MealVol*Group+(1|Subject),
>>                           family=binomial, data=sdata)))
>>
>> ## requires LATEST version of coefplot2 from r-forge:
>> ##  packages won't be rebuilt until tomorrow, probably
>> library(coefplot2)
>> coefplot2(list(gf1,gf2,gf3),col=c(1,2,4))
>> coefplot2(list(gf1,gf2,gf3),xlim=c(-0.05,0.15))
>>
> Thanks, Ben, I had already started with MCMCglmm, but did not know about blme.
>
> Dieter
>
>
>
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> End of R-sig-mixed-models Digest, Vol 59, Issue 39
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