colWeightedMads {DelayedMatrixStats}R Documentation

Weighted Median Absolute Deviation (MAD)

Description

Computes a weighted MAD of a numeric vector.

Usage

colWeightedMads(x, w = NULL, rows = NULL, cols = 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, ...)

## S4 method for signature 'DelayedMatrix'
colWeightedMads(x, w = NULL, rows = NULL,
  cols = NULL, na.rm = FALSE, constant = 1.4826, center = NULL,
  force_block_processing = FALSE, ...)

## S4 method for signature 'DelayedMatrix'
rowWeightedMads(x, w = NULL, rows = NULL,
  cols = NULL, na.rm = FALSE, constant = 1.4826, center = NULL,
  force_block_processing = FALSE, ...)

Arguments

x

A NxK DelayedMatrix.

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.

rows

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

cols

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

na.rm

a logical value indicating whether NA values in x should be stripped before the computation proceeds, or not. If NA, no check at all for NAs is done. Default value is NA (for efficiency).

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.

...

Additional arguments passed to specific methods.

force_block_processing

FALSE (the default) means that a seed-aware, optimised method is used (if available). This can be overridden to use the general block-processing strategy by setting this to TRUE (typically not advised). The block-processing strategy loads one or more (depending on getOption("DelayedArray.block.size")) columns (colFoo()) or rows (rowFoo()) into memory as an ordinary base::array.

Value

Returns a numeric scalar.

Missing values

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

See Also

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

Examples

# A DelayedMatrix with a 'matrix' seed
dm_matrix <- DelayedArray(matrix(c(rep(1L, 5),
                                   as.integer((0:4) ^ 2),
                                   seq(-5L, -1L, 1L)),
                                 ncol = 3))

colWeightedMads(dm_matrix, w = 1:5)

rowWeightedMads(dm_matrix, w = 3:1)
[Package DelayedMatrixStats version 1.2.0 Index]