colSdDiffs,dgCMatrix-method {sparseMatrixStats} | R Documentation |
Calculates the standard deviation of the difference between each element of a row (column) of a matrix-like object.
## S4 method for signature 'dgCMatrix' colSdDiffs( x, rows = NULL, cols = NULL, na.rm = FALSE, diff = 1L, trim = 0, useNames = NA ) ## S4 method for signature 'dgCMatrix' rowSdDiffs( x, rows = NULL, cols = NULL, na.rm = FALSE, diff = 1L, trim = 0, useNames = NA )
x |
An NxK matrix-like object. |
rows |
A |
cols |
A |
na.rm |
|
diff |
An integer specifying the order of difference. |
trim |
A double in [0,1/2] specifying the fraction of observations to be trimmed from each end of (sorted) x before estimation. |
useNames |
If |
The S4 methods for x
of type matrix
,
array
, or numeric
call
matrixStats::rowSdDiffs
/ matrixStats::colSdDiffs
.
Returns a numeric
vector
of length N (K).
matrixStats::rowSdDiffs()
and
matrixStats::colSdDiffs()
which are
used when the input is a matrix
or numeric
vector.
for the direct standard deviation see rowSds()
.
mat <- matrix(rnorm(15), nrow = 5, ncol = 3) mat[2, 1] <- NA mat[3, 3] <- Inf mat[4, 1] <- 0 print(mat) rowSdDiffs(mat) colSdDiffs(mat)