colSds-xgCMatrix-method: Calculates the standard deviation for each row (column) of a...

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

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

Description

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

Usage

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

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

Arguments

x	An NxK matrix-like object.
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.
center	(optional) the center, defaults to the row means
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::rowSds / matrixStats::colSds.

Value

Returns a numeric vector of length N (K).

See Also

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

• For mean estimates, see rowMeans2() and rowMeans().

• For variance estimates, see rowVars().

Examples

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

print(mat)

rowSds(mat)
colSds(mat)

const-ae/sparseMatrixStats documentation built on June 15, 2024, 9:36 a.m.