colQuantiles {DelayedMatrixStats} | R Documentation |
Estimates quantiles for each row (column) in a matrix.
colQuantiles(x, rows = NULL, cols = NULL, probs = seq(from = 0, to = 1, by = 0.25), na.rm = FALSE, type = 7L, ..., drop = TRUE) rowQuantiles(x, rows = NULL, cols = NULL, probs = seq(from = 0, to = 1, by = 0.25), na.rm = FALSE, type = 7L, ..., drop = TRUE) ## S4 method for signature 'DelayedMatrix' colQuantiles(x, rows = NULL, cols = NULL, probs = seq(from = 0, to = 1, by = 0.25), na.rm = FALSE, type = 7L, force_block_processing = FALSE, ..., drop = TRUE) ## S4 method for signature 'DelayedMatrix' rowQuantiles(x, rows = NULL, cols = NULL, probs = seq(from = 0, to = 1, by = 0.25), na.rm = FALSE, type = 7L, force_block_processing = FALSE, ..., drop = TRUE)
x |
A NxK DelayedMatrix. |
rows |
A |
cols |
A |
probs |
|
na.rm |
|
type |
An |
... |
Additional arguments passed to specific methods. |
drop |
If TRUE, singleton dimensions in the result are dropped, otherwise not. |
force_block_processing |
|
Returns a numeric
NxJ (KxJ)
matrix
, where N (K) is the number of rows (columns) for
which the J quantiles are calculated.
# A DelayedMatrix with a 'data.frame' seed dm_df <- DelayedArray(data.frame(C1 = rep(1L, 5), C2 = as.integer((0:4) ^ 2), C3 = seq(-5L, -1L, 1L))) # colnames, if present, are preserved as rownames on output colQuantiles(dm_df) # Input has no rownames so output has no rownames rowQuantiles(dm_df)