colMadDiffs-dgCMatrix-method: Calculates the mean absolute deviation of the difference...

Description Usage Arguments Details Value See Also Examples

Description

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

Usage

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## S4 method for signature 'dgCMatrix'
colMadDiffs(
  x,
  rows = NULL,
  cols = NULL,
  na.rm = FALSE,
  diff = 1L,
  trim = 0,
  constant = 1.4826
)

## S4 method for signature 'dgCMatrix'
rowMadDiffs(
  x,
  rows = NULL,
  cols = NULL,
  na.rm = FALSE,
  diff = 1L,
  trim = 0,
  constant = 1.4826
)

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.

constant

A scale factor. See mad for details.

Details

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

Value

Returns a numeric vector of length N (K).

See Also

Examples

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

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