matrixStats (version 1.3.0)

weightedMad: Weighted Median Absolute Deviation (MAD)

Description

Computes a weighted MAD of a numeric vector.

Usage

weightedMad(x, w = NULL, idxs = NULL, na.rm = FALSE, constant = 1.4826,
  center = NULL, ...)
rowWeightedMads(x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE,
  constant = 1.4826, center = NULL, ..., useNames = TRUE)
colWeightedMads(x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE,
  constant = 1.4826, center = NULL, ..., useNames = TRUE)

Value

Returns a numeric scalar.

Arguments

x

vector of type integer, numeric, or logical.

w

a vector of weights the same length as x giving the weights to use for each element of x. Negative weights are treated as zero weights. Default value is equal weight to all values.

idxs

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

na.rm

If TRUE, missing values are excluded.

constant

A numeric scale factor, cf. mad.

center

Optional numeric scalar specifying the center location of the data. If NULL, it is estimated from data.

...

Not used.

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.

useNames

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

Missing values

Missing values are dropped at the very beginning, if argument na.rm is TRUE, otherwise not.

Author

Henrik Bengtsson

See Also

For the non-weighted MAD, see mad. Internally weightedMedian() is used to calculate the weighted median.

Examples

x <- 1:10
n <- length(x)

m1 <- mad(x)
m2 <- weightedMad(x)
stopifnot(identical(m1, m2))

w <- rep(1, times = n)
m1 <- weightedMad(x, w)
stopifnot(identical(m1, m2))

# All weight on the first value
w[1] <- Inf
m <- weightedMad(x, w)
stopifnot(m  == 0)

# All weight on the first two values
w[1:2] <- Inf
m1 <- mad(x[1:2])
m2 <- weightedMad(x, w)
stopifnot(identical(m1, m2))

# All weights set to zero
w <- rep(0, times = n)
m <- weightedMad(x, w)
stopifnot(is.na(m))