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

[Chris Howden]

Hi Glenda,

Try the following with a fresh session of R to maximise memory:
memory.limit(size=4095)
# report memory limit
memory.limit(size=NA)
# maximum amount of memory obtained from the OS is reported
memory.limit(size=TRUE)
# amount currently in use
memory.limit(size=FALSE)


When u clean your workspace using rm(), u may need to run gc() to free up
space.


Also to double check its size, and not something else try running it on a
subset of the data. Although as U have random effects U'll need to insure
the subset has the right data that the random component makes sense.

It may also be due to U estimating a huge covariance matrix, think about
how big it would be.

Chris Howden B.Sc. (Hons) GStat.
Founding Partner
Evidence Based Strategic Development, IP Commercialisation and Innovation,
Data Analysis, Modelling and Training
(mobile) 0410 689 945
(fax) +612 4782 9023
chris at trickysolutions.com.au




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-----Original Message-----
From: r-sig-mixed-models-bounces at r-project.org
[mailto:r-sig-mixed-models-bounces at r-project.org] On Behalf Of glenda
mendieta
Sent: Tuesday, 29 November 2011 2:18 AM
To: r-sig-mixed-models at r-project.org
Subject: [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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