I have a question concerning the working memory used by R.
I am running a simulation job (a function which replicates a simulation) which calls
several other functions that I have written. Something like this:
name1<-function(number of replications){
for(i in 1:replication)
name2(parameters)
name3()
# get results and aggregate
open..
write(..., append=T)
}
}
name2<-function(parameters){
# simulate data
...
# save data and parameters
write...
}
name3<-function(){
# get data and parameters
open...
# analyse data
...
# save results
write..
}
name1(100)
However, after a couple of replications working memory seems to be full.
Error: cannot allocate vector of size ...Kb
In addition: Warning message:
Reached total allocation of 126Mb: see help(memory.size)
This puzzles me, because all arrays (Note: large arrays, i.e., 500x500) are defined
locally (within each function) and redefined every replication (the meta-function). So
my question is: Why is R eating up my working memory while I think I am redefining the
same (local) arrays? Any thoughts on how this can be circumvented?
Thanks,
Peter.
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