colSdDiffs-dgCMatrix-method: Calculates the standard deviation of the difference between...

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

Description

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

Usage

## S4 method for signature 'dgCMatrix'
colSdDiffs(x, rows = NULL, cols = NULL, na.rm = FALSE, diff = 1L, trim = 0)

## S4 method for signature 'dgCMatrix'
rowSdDiffs(x, rows = NULL, cols = NULL, na.rm = FALSE, diff = 1L, trim = 0)

Arguments

x	An NxK matrix-like object.
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.
diff	An integer specifying the order of difference.
trim	A double in [0,1/2] specifying the fraction of observations to be trimmed from each end of (sorted) x before estimation.

Details

The S4 methods for x of type matrix, array, or numeric call matrixStats::rowSdDiffs / matrixStats::colSdDiffs.

Value

Returns a numeric vector of length N (K).

See Also

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

• for the direct standard deviation see rowSds().

Examples

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

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