colWeightedMeans: Calculates the weighted mean for each row (column) of a...

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

Calculates the weighted mean for each row (column) of a matrix-like object

Description

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

Usage

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

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

Arguments

x	A NxK DelayedMatrix.
w	A numeric vector of length K (N) that specifies by how much each element is weighted.
rows, cols	A vector indicating the subset of rows (and/or columns) to operate over. If NULL, no subsetting is done.
na.rm	If TRUE, missing values (NA or NaN) are omitted from the calculations.
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.
useNames	If TRUE (default), names attributes of result are set. Else if FALSE, no naming support is done.

Details

The S4 methods for x of type matrix, array, table, or numeric call matrixStats::rowWeightedMeans / matrixStats::colWeightedMeans.

Value

Returns a numeric vector of length N (K).

Author(s)

Peter Hickey

See Also

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

• See also rowMeans2 for the corresponding unweighted function.

Examples

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

colWeightedMeans(dm_Matrix)
# Specifying weights inversely proportional to rowwise variances
colWeightedMeans(dm_Matrix, w = 1 / rowVars(dm_Matrix))
rowWeightedMeans(dm_Matrix, w = 1:3)

PeteHaitch/DelayedMatrixStats documentation built on May 6, 2024, 10:25 p.m.