colWeightedMeans {DelayedMatrixStats} | R Documentation |
Calculates the weighted means for each row (column) in a matrix.
colWeightedMeans(x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE, ...) rowWeightedMeans(x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE, ...) ## S4 method for signature 'DelayedMatrix' colWeightedMeans(x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE, force_block_processing = FALSE, ...) ## S4 method for signature 'DelayedMatrix' rowWeightedMeans(x, w = NULL, rows = NULL, cols = NULL, na.rm = FALSE, force_block_processing = FALSE, ...)
x |
A NxK DelayedMatrix. |
w |
|
rows |
A |
cols |
A |
na.rm |
If |
... |
Additional arguments passed to specific methods. |
force_block_processing |
|
The implementations of these methods are optimized for both speed and
memory. If no weights are given, the corresponding
rowMeans()
/colMeans()
is used.
Returns a numeric
vector
of
length N (K).
See rowMeans()
and colMeans()
in
colSums
() for non-weighted means. See also
weighted.mean
.
# A DelayedMatrix with a 'Matrix' seed dm_Matrix <- DelayedArray(Matrix::Matrix(c(rep(1L, 5), as.integer((0:4) ^ 2), seq(-5L, -1L, 1L)), ncol = 3)) colWeightedMeans(dm_Matrix) # Specifying weights inversely proportional to rowwise variances colWeightedMeans(dm_Matrix, w = 1 / rowVars(dm_Matrix)) rowWeightedMeans(dm_Matrix, w = 1:3)