matrixStats (version 1.4.1)

rowWeightedMedians: Calculates the weighted medians for each row (column) in a matrix

Description

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

Usage

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

Value

Returns a numeric

vector of length N (K).

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.

...

Additional arguments passed to weightedMedian().

useNames

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

Author

Henrik Bengtsson

Details

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

See Also

Internally, weightedMedian() is used. See rowMedians() and colMedians() for non-weighted medians.

Examples

x <- matrix(rnorm(20), nrow = 5, ncol = 4)
print(x)

# Non-weighted row averages
mu_0 <- rowMedians(x)
mu <- rowWeightedMedians(x)
stopifnot(all.equal(mu, mu_0))

# Weighted row averages (uniform weights)
w <- rep(2.5, times = ncol(x))
mu <- rowWeightedMedians(x, w = w)
stopifnot(all.equal(mu, mu_0))

# Weighted row averages (excluding some columns)
w <- c(1, 1, 0, 1)
mu_0 <- rowMedians(x[, (w == 1), drop = FALSE])
mu <- rowWeightedMedians(x, w = w)
stopifnot(all.equal(mu, mu_0))

# Weighted row averages (excluding some columns)
w <- c(0, 1, 0, 0)
mu_0 <- rowMedians(x[, (w == 1), drop = FALSE])
mu <- rowWeightedMedians(x, w = w)
stopifnot(all.equal(mu, mu_0))

# Weighted averages by rows and columns
w <- 1:4
mu_1 <- rowWeightedMedians(x, w = w)
mu_2 <- colWeightedMedians(t(x), w = w)
stopifnot(all.equal(mu_2, mu_1))