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?