Hi Rui,
Yes you are right, there is no argument 'data".
Mistakenly, I wrote only 'data' in the email. but in the r script, I have
written newdata.
As you suggested, I did trying one prediction at a time, but still- same
problem. It is really big data set. May be - should I go 'Matlab' for this big
data set?
thanks
> Date: Wed, 22 May 2013 15:56:18 +0100
> From: ruipbarra...@sapo.pt
> To: kristi.glo...@hotmail.com
> CC: r-help@r-project.org
> Subject: Re: [R] Code overloading PC
>
> Hello,
>
> In predict.glm, there's no argument 'data', it's 'newdata'.
> As for your problem, maybe try doing one prediction at a time, write the
> results to file, then the next.
>
> Hope this helps,
>
> Rui Barradas
>
> Em 22-05-2013 15:20, Kristi Glover escreveu:
> > Hi R user,
> > I was trying to develop a model (logistic regression) for 4001 dependent
> > variables using 15 environmental variables (45000 rows); and then trying to
> > use the models to predict in future. I used following code but it took so
> > much time and consumed 100% of the PC memory. Even though- analysis was not
> > complete. I got a following message
> > " Reached total allocation of 8098Mb: see help(memory.size)". I increased
> > memory size to 8GB. but still I could not complete the analysis.
> > Any suggestion to reduce the memory and compute the big data set.
> >
> > #------------------------------------------------------------------
> > data=spec.Env
> >
> > models <- list()
> > PredictModelsCur<-list()
> > PredictModelsA1<-list()
> > PredictModelsA2<-list()
> > PredictModelsA3<-list()
> > dvnames <- paste("V", 2:4003, sep="")
> > ivnames <- paste("env", 1:15, sep="",collapse="+") ## for some value of n
> >
> > for (y in dvnames){
> > form <- formula(paste(y,"~",ivnames))
> > models[[y]] <- glm(form, data=spec.Env, family='binomial')
> > PredictModelsCur[[y]]<-predict(models[[y]], type="response")
> > PredictModelsA1[[y]]<-predict(models[[y]], data = a1.Futute,
> > type="response")
> > PredictModelsA2[[y]]<-predict(models[[y]], data = a2.Futute,
> > type="response")
> > PredictModelsA3[[y]]<-predict(models[[y]], data = a3.Futute,
> > type="response")
> > }
> >
> > write.csv(PredictModelsCur, "PredictModelsCur.csv", row.names=F)
> > write.csv(PredictModelsA1, "PredictModelsA1.csv", row.names=F)
> > write.csv(PredictModelsA2, "PredictModelsA2.csv", row.names=F)
> > write.csv(PredictModelsA3, "PredictModelsA3.csv", row.names=F)
> >
> >
> > [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> >
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