covMat {scPCA} | R Documentation |
Compute Sample Covariance Matrix
Description
covMat
computes the sample covariance matrix of a data
set. If a variable in the dataset has zero variance, then its
corresponding row and column in the covariance matrix are zero vectors.
Usage
covMat(data, center = TRUE, scale = TRUE, scaled_matrix = FALSE)
Arguments
data |
The data for which to compute the sample covariance matrix.
|
center |
A logical indicating whether the target and background
data sets should be centered to mean zero.
|
scale |
A logical indicating whether the target and background
data sets should be scaled to unit variance.
|
scaled_matrix |
A logical indicating whether to output a
ScaledMatrix object. The centering and scaling
procedure is delayed until later, permitting more efficient matrix
multiplication and row or column sums downstream. However, this comes at the
at the cost of numerical precision. Defaults to FALSE .
|
Value
the covariance matrix of the data.
[Package
scPCA version 1.8.0
Index]