colWeightedSds-xgCMatrix-method: Calculates the weighted standard deviation for each row...

In const-ae/sparseMatrixStats: Summary Statistics for Rows and Columns of Sparse Matrices

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

Description

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

Usage

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

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

Arguments

x	An NxK matrix-like object.
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.
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::rowWeightedSds / matrixStats::colWeightedSds.

Value

Returns a numeric vector of length N (K).

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

mat <- matrix(rnorm(15), nrow = 5, ncol = 3)
mat[2, 1] <- NA
mat[3, 3] <- Inf
mat[4, 1] <- 0

print(mat)
w <- rnorm(n = 5, mean = 3)
rowWeightedSds(mat, w = w[1:3])
colWeightedSds(mat, w = w)

const-ae/sparseMatrixStats documentation built on April 12, 2025, 11:58 p.m.