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))