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

In sparseMatrixStats: Summary Statistics for Rows and Columns of Sparse Matrices

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, NAs 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).

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)

sparseMatrixStats documentation built on Feb. 4, 2021, 2 a.m.