How to calculate the row wise means for grouped columns in matrix?
adapted from the help files of rowsum x <- matrix(runif(100), ncol=5) group <- sample(1:8, 20, TRUE) xsum <- rowsum(x, group) sweep(xsum, 1, table(group), "/") or aggregate(x, list(group), mean)[-1] b 2010/1/15 Joel F?rstenberg-H?gg <joel_furstenberg_hagg at hotmail.com>:
Hi all, I want to calculate the row wise mean of groups of columns in a matrix M. All columns belonging to the same group have the same column name. My idea is to create a new vector V containing these column names, but after first removing the duplicates. Then I would calculate the means using for instance rowMean() and by comparing the column names of M with the vector V, getting the indices of the columns to use. What do you think, is it a good idea or not? If yes, any suggestions how to do it? If no, is there any alternative solution that might work better? All the best, Joel
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