Hello, I have a question regarding how to speed up the t.test on large dataset. For example, I have a table "tab" which looks like:
a b c d e f g h.... 1 2 3 4 5 ... 100000 dim(tab) is 100000 x 100 I need to do the t.test for each row on the two subsets of columns, ie to compare a b d group against e f g group at each row. subset 1: a b d 1 2 3 4 5 ... 100000 subset 2: e f g 1 2 3 4 5 ... 100000 100000 t.test's for each row for these two subsets will take around 1 min. The prblem is that I have around 10000 different combinations of such a subsets. therefore 1min*10000 =10000min in the case if I will use "for" loop like this: n1=10000 #number of subset combinations for (i1 in 1:n1) { n2=100000 # number of rows i2=1 for (i2 in 1:n1) { t.test(tab[i2,v5],tab[i2,v6])$p.value #v5 and v6 are vectors containing the veriable names for the two subsets (they are different for each loop) } } My question is there more efficient way how to do this computations in a short period of time? Any packages, like plyr? May be direct calculations isted of using t.test function? Thank you. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.