Calculates the weighted means for each row (column) in a matrix
Calculates the weighted means for each row (column) in a matrix.
rowWeightedMeans(x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE, ...) colWeightedMeans(x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE, ...)
The implementations of these methods are optimized for both speed and
memory. If no weights are given, the corresponding
rowMeans()/colMeans() is used.
Henrik Bengtsson
See rowMeans() and colMeans() in
colSums() for non-weighted means. See also
weighted.mean.
x <- matrix(rnorm(20), nrow = 5, ncol = 4) print(x) # Non-weighted row averages mu_0 <- rowMeans(x) mu <- rowWeightedMeans(x) stopifnot(all.equal(mu, mu_0)) # Weighted row averages (uniform weights) w <- rep(2.5, times = ncol(x)) mu <- rowWeightedMeans(x, w = w) stopifnot(all.equal(mu, mu_0)) # Weighted row averages (excluding some columns) w <- c(1, 1, 0, 1) mu_0 <- rowMeans(x[, (w == 1), drop = FALSE]) mu <- rowWeightedMeans(x, w = w) stopifnot(all.equal(mu, mu_0)) # Weighted row averages (excluding some columns) w <- c(0, 1, 0, 0) mu_0 <- rowMeans(x[, (w == 1), drop = FALSE]) mu <- rowWeightedMeans(x, w = w) stopifnot(all.equal(mu, mu_0)) # Weighted averages by rows and columns w <- 1:4 mu_1 <- rowWeightedMeans(x, w = w) mu_2 <- colWeightedMeans(t(x), w = w) stopifnot(all.equal(mu_2, mu_1))
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