| colWeightedSds,DelayedMatrix-method {DelayedMatrixStats} | R Documentation |
Calculates the weighted standard deviation for each row (column) of a matrix-like object.
## S4 method for signature 'DelayedMatrix' colWeightedSds( x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE, force_block_processing = FALSE, ..., useNames = NA ) ## S4 method for signature 'DelayedMatrix' colWeightedVars( x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE, force_block_processing = FALSE, ..., useNames = NA ) ## S4 method for signature 'DelayedMatrix' rowWeightedSds( x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE, force_block_processing = FALSE, ..., useNames = NA ) ## S4 method for signature 'DelayedMatrix' rowWeightedVars( x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE, force_block_processing = FALSE, ..., useNames = NA )
x |
A NxK DelayedMatrix. |
w |
A |
rows |
A |
cols |
A |
na.rm |
|
force_block_processing |
|
... |
Additional arguments passed to specific methods. |
useNames |
If |
The S4 methods for x of type matrix,
array, or numeric call
matrixStats::rowWeightedSds
/ matrixStats::colWeightedSds.
Returns a numeric vector of length N (K).
Peter Hickey
Peter Hickey
matrixStats::rowWeightedSds() and
matrixStats::colWeightedSds()
which are used when the input is a matrix or numeric vector.
See also rowSds for the corresponding unweighted function.
# A DelayedMatrix with a 'SolidRleArraySeed' seed
dm_Rle <- RleArray(Rle(c(rep(1L, 5),
as.integer((0:4) ^ 2),
seq(-5L, -1L, 1L))),
dim = c(5, 3))
colWeightedSds(dm_Rle, w = 1 / rowMeans2(dm_Rle))
# Specifying weights inversely proportional to rowwise means
colWeightedVars(dm_Rle, w = 1 / rowMeans2(dm_Rle))
# Specifying weights inversely proportional to columnwise means
rowWeightedSds(dm_Rle, w = 1 / colMeans2(dm_Rle))
# Specifying weights inversely proportional to columnwise means
rowWeightedVars(dm_Rle, w = 1 / colMeans2(dm_Rle))