Thanks for the help, the wrapper function was very useful. I managed to solve the problem using Spencer Graves' suggestion. I am analyzing the interarrival times between HTTP packets on a campus network. The dataset actually has more than 14 Million entries! It represents the traffic generated by approximately 3000 users browsing the web for 30 days. I have to be careful to always remove unused objects from my workspace, but otherwise I have so far managed to cope with 512Mb of memory on a Pentium 600Mhz.
Lourens On Tue, 2003-09-30 at 23:25, Ben Bolker wrote: > PS. 11 MILLION entries?? > > On Tue, 30 Sep 2003, Ben Bolker wrote: > > > > > Spencer Graves's suggestion of using shape and scale parameters on a log > > scale is a good one. > > > > To do specifically what you want (check values for which the objective > > function is called and see what happens) you can do the following > > (untested!), which makes a local copy of dgamma that you can mess with: > > > > dgamma.old <- dgamma > > dgamma <- function(x,shape,rate,...) { > > d <- dgamma.old(x,shape,rate,...) > > cat(shape,rate,d,"\n") > > return(d) > > } ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help