[R-sig-ME] problems with allocate memory

[cumuluss at web.de]

Hi Douglas,

thanky you for your reply. This is "mydata"

'data.frame':   3909896 obs. of  19 variables:
 $ gr.b            : int  0 0 0 0 0 0 0 0 0 0 ...
 $ o.ag      : num  -0.651 -0.651 -0.651 -0.651 -0.651 ...
 $ o.rar      : num  -0.935 -0.935 -0.935 -0.935 -0.935 ...
 $ si       : num  0.299 0.299 0.299 0.299 0.299 ...
 $ f.ag       : num  -1.25 -1.36 -1.33 -1.26 -1.21 ...
 $ f.se       : Factor w/ 2 levels "F","M": 1 2 1 2 2 2 1 1 1 1 ...
 $ o.se       : Factor w/ 2 levels "F","M": 1 1 1 1 1 1 1 1 1 1 ...
 $ diff        : num  -0.536 -0.514 -0.521 -0.534 -0.545 ...
 $ exp.r           : num  -0.168 -0.168 -0.163 -0.168 -0.168 ...
 $ f.rar      : num  -0.911 0.215 1.224 -1.086 1.107 ...
 $ f.si: num  1.0008 1.1583 0.0561 -0.4163 0.371 ...
 $ kl              : Factor w/ 3 levels "mat","nonkin",..: 1 2 2 2 3 2 1 2 2 2 ...
 $ sn          : Factor w/ 2 levels "BS","MS": 1 1 1 1 1 1 1 1 1 1 ...
 $ MP_y_n          : Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ...
 $ ratio       : num  -0.0506 -0.0506 -0.0506 -0.0506 -0.0506 ...
 $ f           : Factor w/ 55 levels "0A0","0A1","0A2",..: 1 6 7 8 9 10 11 13 15 16 ...
 $ o           : Factor w/ 552 levels "","00T","00Z",..: 2 2 2 2 2 2 2 2 2 2 ...
 $ d            : int  9099 9099 9099 9099 9099 9099 9099 9099 9099 9099 ...
 $ MP              : num  6 6 6 6 5 4 6 6 6 6 ...
 
 
formula for the model:
mfit=lmer(gr.b ~ o.ag + o.rar + si + ((f.ag + I(f.ag^2)) * (f.se * (o.se + diff + exp.r + f.rar + f.si + kl + sn + MP_y_n + ratio))) + (1|f)+(1|o)+(1|d) + offset(log(MP)), data=c.data, family=binomial)

I hope this is what you want to see. Thank you for your help.

Cheers
Paul



-------- Original-Nachricht --------
> Datum: Mon, 19 Dec 2011 14:50:06 -0600
> Von: Douglas Bates <bates at stat.wisc.edu>
> An: cumuluss at web.de
> CC: r-sig-mixed-models at r-project.org
> Betreff: Re: [R-sig-ME] problems with allocate memory

> On Sun, Dec 18, 2011 at 3:17 PM,  <cumuluss at web.de> wrote:
> > Hi to everyone,
>
> > I have been trying to fit a glmm with a binomial error structure. My
> model is a little bit complex. I have 8 continuous predictor variables one of
> them as nonlinear term, 5 categorical predictor variables with some
> three-way interactions between them. Additional I have 3 random effects and one
> offset variable in the model. Number of obs is greater than 3million.
> > I’m working with the latest version of R 2.14.0 on a 64 bit windows
> system with 8Gb ram.
> > Everything I tried (reducing model complexity, different 64bit PC with
> even more memory) nothing leads to a fitted model, always the Error occurs:
> cannot allocate vector of size 2GB.
> > Is there anything I can do? I would be very grateful for any commentary.
>
> You probably have multiple copies of some large objects hanging
> around.  Can you send us the output of
>
> str(myData)
>
> where 'myData' is the name of the model frame containing the data you
> are using and the formula for the model you are trying to fit?