randSVD {randPedPCA} | R Documentation |
Singular value decomposition in sparse triangular matrix
Description
Uses randomised linear algebra, see Halko et al. (2010). Singular value
decomposition (SVD) decomposes a matrix X=U\Sigma W^T
Usage
randSVD(L, rank, depth, numVectors, cent = FALSE)
Arguments
L |
a pedigree's L inverse matrix in sparse 'spam' format |
rank |
An |
depth |
|
numVectors |
An |
cent |
|
Value
A list of three: u
(=U), d
(=Sigma), and v
(=W^T)
[Package randPedPCA version 1.1.3 Index]