colMadDiffs-dgCMatrix-method: Calculates the mean absolute deviation of the difference...
In sparseMatrixStats: Summary Statistics for Rows and Columns of Sparse Matrices

Description Usage Arguments Details Value See Also Examples

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

## 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
)

`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`, `NA`s 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.

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

Returns a numeric vector of length N (K).

matrixStats::rowMadDiffs() and matrixStats::colMadDiffs() which are used when the input is a matrix or numeric vector.

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)