Greetings all, I am curious to know if either of these two sets of code is more efficient?
Example1: ## t-test ## colA <- temp [ , j ] colB <- temp [ , k ] ttr <- t.test ( colA, colB, var.equal=TRUE) tt_pvalue [ i ] <- ttr$p.value or Example2: tt_pvalue [ i ] <- t.test ( temp[ , j ], temp[ , k ], var.equal=TRUE) ------------- I have three loops, i, j, k. One to test the all of <i> files in a directory. One to tease out column <j> and compare it by means of t-test to column <k> in each of the files. --------------- for ( i in 1:num_files ) { temp <- read.table ( files_to_test [ i ], header=TRUE, sep="\t") num_cols <- ncol ( temp ) ## Define Columns To Compare ## for ( j in 2 : num_cols ) { for ( k in 3 : num_cols ) { ## t-test ## colA <- temp [ , j ] colB <- temp [ , k ] ttr <- t.test ( colA, colB, var.equal=TRUE) tt_pvalue [ i ] <- ttr$p.value } } } -------------------------------- I am a novice writer of code and am interested to hear if there are any (dis)advantages to one way or the other. M Matt Curcio M: 401-316-5358 E: matt.curcio...@gmail.com ______________________________________________ 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.