Dear list, A while ago, Vadim asked opinions on improving efficiency of sample() with prob, e.g. sample with replacement with weight. ( https://stat.ethz.ch/pipermail/r-devel/2004-September/030844.html ) He did not post what he ended up with this problem though.
I am having exactly the same problem. I need to sample with replacement from a population of size 10 million with fitness values for each individual. sample() is too slow for this purpose. I implement a bisection search algorithm. It is about 30% faster than the linear search one but still not good enough to me. (I can post the function if needed). Does anybody have some good ideas? The only other idea I have is using a faster (but worse) random number generator just for this application. Thanks. Bo ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
