And of course using rm(...) to clean up objects you no longer need.  No
amount of physical memory can save you from grossly inefficient code and
large memory leaks.  For example, lets say I have a large testMat object
that I use time period.  I loop though each month using for loops.  Even
though the object has the same name each month, and thus gets overwritten,
the memory management seems to go better by manually removing the object at
the end of each loop.  Also, I sometimes call gc() at the end of each loop,
but I don't know if that actually helps or not.  I figure it can't hurt.





On 2/23/06, Liaw, Andy <andy_liaw@merck.com> wrote:
>
> There are plenty in the the list archive, one of which is to switch to a
> run
> 64-bit R on a 64-bit platform with lots of physical RAM.  Such hardware is
> quite affordable these days (certainly cheaper than most commercial
> software
> that you'd have to buy if you didn't have R).
>
> Andy
>
> From: r user
> >
> > I am using R 2.2.1 in a Windowes XP environment.
> >
> > I work with very large datasets, and occassionally run
> > out of memory.
> >
> > I have modified my boot.ini file to use the "/3gb
> > switch".
> >
> > I also run the following line after I launch R ( I am
> > unsure if it is helpful).
> >
> > "memory.limit(size = 4095)"
> >
> > Please point me to useful references on how to better
> > manage memory, or suggestother actions.
> >
> > ______________________________________________
> > R-help@stat.math.ethz.ch mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide!
> > http://www.R-project.org/posting-guide.html
> >
> >
>
> ______________________________________________
> R-help@stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
> http://www.R-project.org/posting-guide.html
>

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