Folks, I recently was given a simulated data set like the following subset:
sim_sub<-structure(list(V11 = c(0.01, 0, 0, 0.01, 0, 0.01, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), V12 = c(0, 0, 0, 0.01, 0.03, 0, 0, 0, 0, 0, 0, 0.01, 0, 0.01, 0, 0, 0, 0, 0, 0.04), V13 = c(0, 0, 0, 0.01, 0, 0, 0, 0, 0, 0.01, 0, 0, 0, 0, 0.01, 0, 0, 0, 0, 0.01), V14 = c(0, 0.01, 0.01, 0.01, 0.01, 0, 0, 0, 0, 0.03, 0, 0, 0.01, 0.01, 0.04, 0.01, 0.02, 0, 0.01, 0.03), V15 = c(0, 0.01, 0, 0, 0.01, 0, 0, 0, 0.01, 0.02, 0.01, 0, 0, 0.01, 0, 0, 0, 0.01, 0.01, 0.04), V16 = c(0, 0, 0, 0.03, 0.02, 0.01, 0, 0, 0.02, 0.02, 0, 0.02, 0.02, 0, 0.01, 0.01, 0, 0, 0.03, 0.01), V17 = c(0, 0.01, 0, 0.01, 0, 0, 0, 0.01, 0.05, 0.03, 0, 0.01, 0, 0.02, 0.02, 0, 0, 0.01, 0.02, 0.04), V18 = c(0, 0.01, 0, 0.03, 0.03, 0, 0, 0, 0.02, 0.01, 0, 0.02, 0.01, 0.02, 0.03, 0.02, 0, 0, 0.04, 0.04 ), V19 = c(0, 0.01, 0.01, 0.02, 0.07, 0, 0, 0, 0.04, 0.01, 0.02, 0, 0, 0, 0.04, 0, 0, 0, 0, 0.05), V20 = c(0, 0, 0, 0.01, 0.04, 0.01, 0, 0, 0.02, 0.04, 0.01, 0, 0.02, 0, 0.03, 0, 0.02, 0.01, 0.03, 0.03)), .Names = c("V11", "V12", "V13", "V14", "V15", "V16", "V17", "V18", "V19", "V20"), row.names = c(NA, 20L), class = "data.frame") > sim_sub V11 V12 V13 V14 V15 V16 V17 V18 V19 V20 1 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2 0.00 0.00 0.00 0.01 0.01 0.00 0.01 0.01 0.01 0.00 3 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.01 0.00 4 0.01 0.01 0.01 0.01 0.00 0.03 0.01 0.03 0.02 0.01 5 0.00 0.03 0.00 0.01 0.01 0.02 0.00 0.03 0.07 0.04 6 0.01 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.01 7 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 8 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 9 0.00 0.00 0.00 0.00 0.01 0.02 0.05 0.02 0.04 0.02 10 0.00 0.00 0.01 0.03 0.02 0.02 0.03 0.01 0.01 0.04 11 0.00 0.00 0.00 0.00 0.01 0.00 0.00 0.00 0.02 0.01 12 0.00 0.01 0.00 0.00 0.00 0.02 0.01 0.02 0.00 0.00 13 0.00 0.00 0.00 0.01 0.00 0.02 0.00 0.01 0.00 0.02 14 0.00 0.01 0.00 0.01 0.01 0.00 0.02 0.02 0.00 0.00 15 0.00 0.00 0.01 0.04 0.00 0.01 0.02 0.03 0.04 0.03 16 0.00 0.00 0.00 0.01 0.00 0.01 0.00 0.02 0.00 0.00 17 0.00 0.00 0.00 0.02 0.00 0.00 0.00 0.00 0.00 0.02 18 0.00 0.00 0.00 0.00 0.01 0.00 0.01 0.00 0.00 0.01 19 0.00 0.00 0.00 0.01 0.01 0.03 0.02 0.04 0.00 0.03 20 0.00 0.04 0.01 0.03 0.04 0.01 0.04 0.04 0.05 0.03 Every 5 rows represents one block of simulated data. What would be the best way to average the blocks? My way was to reshape sim_sub, average over the columns and then reshape back like so: > matrix(colSums(matrix(t(sim_sub), byrow = TRUE, ncol = 50)), byrow = TRUE, > ncol = 10)/4 [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 0.0050 0.0000 0.0000 0.0025 0.0025 0.005 0.0000 0.0050 0.0050 0.0050 [2,] 0.0000 0.0025 0.0000 0.0075 0.0025 0.005 0.0050 0.0075 0.0025 0.0050 [3,] 0.0000 0.0000 0.0000 0.0050 0.0025 0.005 0.0050 0.0025 0.0025 0.0075 [4,] 0.0025 0.0050 0.0025 0.0075 0.0075 0.020 0.0250 0.0275 0.0150 0.0150 [5,] 0.0000 0.0175 0.0075 0.0275 0.0175 0.015 0.0225 0.0275 0.0425 0.0350 How bad is "t(sim_sub)" in the above? Thanks for your time, KW -- ______________________________________________ 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.