colWeightedMads,dgCMatrix-method | 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 = TRUE
)
## S4 method for signature 'dgCMatrix'
rowWeightedMads(
x,
w = NULL,
rows = NULL,
cols = NULL,
na.rm = FALSE,
constant = 1.4826,
center = NULL,
useNames = TRUE
)
x |
An NxK matrix-like object. |
w |
A |
rows , cols |
A |
na.rm |
If |
constant |
A scale factor. See |
center |
Not supported at the moment. |
useNames |
If |
The S4 methods for x
of type matrix
,
array
, table
, 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)
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