dot-computePca: Compute the eigendecomposition of 'R %*% t(R)' for a residual...

In rafalab/smallcount: Methods for Small Counts Stored in a Sparse Matrix

Compute the eigendecomposition of R %*% t(R) for a residual matrix R

Description

Compute the eigendecomposition of R %*% t(R) for a residual matrix R

Usage

.computePca(rtr, k, y, offset1 = NULL, offset2 = NULL)

Arguments

rtr	Cross product of residual matrix R = y - offset1 %*% offset2
k	Number of principal components to return
y	Sparse matrix
offset1, offset2	Vectors whose product is the difference between y and the residual matrix

Value

List with components:

• sdevStandard deviations of principal components

• rotationMatrix of variable loadings (i.e., matrix containing the eigenvectors of the covariance/correlation matrix as columns)

• xMatrix of rotated data (rotated after applying the transformations specified)

rafalab/smallcount documentation built on June 1, 2025, 2:10 p.m.