colWeightedVars: Calculates the weighted standard deviation for each row...

In DelayedMatrixStats: Functions that Apply to Rows and Columns of 'DelayedMatrix' Objects

Description

Calculates the weighted standard deviation for each row (column) of a matrix-like object.

Usage

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

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

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

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

Arguments

x	A NxK DelayedMatrix.
w	A numeric vector of length K (N) that specifies by how much each element is weighted.
rows	A vector indicating the subset of rows (and/or columns) to operate over. If NULL, no subsetting is done.
cols	A vector indicating the subset of rows (and/or columns) to operate over. If NULL, no subsetting is done.
na.rm	If TRUE, NAs are excluded first, otherwise not.
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 \link[DelayedArray]{getAutoBlockSize}()) columns (colFoo()) or rows (rowFoo()) into memory as an ordinary base::array.
...	Additional arguments passed to specific methods.

Details

The S4 methods for x of type matrix, array, or numeric call matrixStats::rowWeightedSds / matrixStats::colWeightedSds.

Value

Returns a numeric vector of length N (K).

Author(s)

Peter Hickey

Peter Hickey

See Also

• matrixStats::rowWeightedSds() and matrixStats::colWeightedSds() which are used when the input is a matrix or numeric vector.

• See also rowSds for the corresponding unweighted function.

Examples

# A DelayedMatrix with a 'SolidRleArraySeed' seed
dm_Rle <- RleArray(Rle(c(rep(1L, 5),
                         as.integer((0:4) ^ 2),
                         seq(-5L, -1L, 1L))),
                   dim = c(5, 3))

colWeightedSds(dm_Rle, w = 1 / rowMeans2(dm_Rle))

# Specifying weights inversely proportional to rowwise means
colWeightedVars(dm_Rle, w = 1 / rowMeans2(dm_Rle))

# Specifying weights inversely proportional to columnwise means
rowWeightedSds(dm_Rle, w = 1 / colMeans2(dm_Rle))

# Specifying weights inversely proportional to columnwise means
rowWeightedVars(dm_Rle, w = 1 / colMeans2(dm_Rle))

DelayedMatrixStats documentation built on Feb. 5, 2021, 2:04 a.m.