rowWeightedMeans: Calculates the weighted means for each row (column) in a matrix

Description

Calculates the weighted means for each row (column) in a matrix.

Usage

rowWeightedMeans(x, w = NULL, rows = NULL, cols = NULL,
  na.rm = FALSE, ...)
colWeightedMeans(x, w = NULL, rows = NULL, cols = NULL,
  na.rm = FALSE, ...)

Arguments

A numeric NxK matrix.

A numeric vector of length K (N).

rows, cols

A vector indicating subset of rows (and/or columns) to operate over. If NULL, no subsetting is done.

na.rm

If TRUE, missing values are excluded from the calculation, otherwise not.

...

Not used.

Value

Returns a numeric vector of length N (K).

Details

The implementations of these methods are optimized for both speed and memory. If no weights are given, the corresponding rowMeans()/colMeans() is used.

Examples

Run this code

# NOT RUN {
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))
# }