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

colWeightedSds,xgCMatrix-method {sparseMatrixStats}

R Documentation

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)

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

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`	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`, `NA`s are excluded first, otherwise not.

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).

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)

[Package sparseMatrixStats version 1.2.1 Index]