colWeightedMads,dgCMatrix-method {sparseMatrixStats} | R Documentation |
Calculates the weighted median absolute deviation for each row (column) of a matrix-like object.
## S4 method for signature 'dgCMatrix' colWeightedMads( x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE, constant = 1.4826, center = NULL, useNames = NA ) ## S4 method for signature 'dgCMatrix' rowWeightedMads( x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE, constant = 1.4826, center = NULL, useNames = NA )
x |
An NxK matrix-like object. |
w |
A |
rows |
A |
cols |
A |
na.rm |
|
constant |
A scale factor. See |
center |
Not supported at the moment. |
useNames |
If |
The S4 methods for x
of type matrix
,
array
, or numeric
call
matrixStats::rowWeightedMads
/ matrixStats::colWeightedMads
.
Returns a numeric
vector
of length N (K).
matrixStats::rowWeightedMads()
and
matrixStats::colWeightedMads()
which are used when the input is a matrix
or numeric
vector.
See also rowMads for the corresponding unweighted function.
mat <- matrix(0, nrow=10, ncol=5) mat[sample(prod(dim(mat)), 25)] <- rpois(n=25, 5) sp_mat <- as(mat, "dgCMatrix") weights <- rnorm(10, mean=1, sd=0.1) # sparse version sparseMatrixStats::colWeightedMads(sp_mat, weights) # Attention the result differs from matrixStats # because it always uses 'interpolate=FALSE'. matrixStats::colWeightedMads(mat, weights)