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

View source: R/rowWeightedMeans.R

rowWeightedMeansR Documentation

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,
  ..., useNames = TRUE)

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

Arguments

x

An NxK matrix or, if dim. is specified, an N * K vector.

w

A numeric vector of length K (N).

rows

A vector indicating subset of rows to operate over. If NULL, no subsetting is done.

cols

A vector indicating subset of columns to operate over. If NULL, no subsetting is done.

na.rm

If TRUE, missing values are excluded.

...

Not used.

useNames

If TRUE (default), names attributes of the result are set, otherwise not.

Details

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

Value

Returns a numeric vector of length N (K).

Author(s)

Henrik Bengtsson

See Also

See rowMeans() and colMeans() in colSums() for non-weighted means. See also weighted.mean.

Examples

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))

matrixStats documentation built on Nov. 7, 2023, 5:07 p.m.