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. ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help