canonicalSVD {SplitKnockoff} | R Documentation |
singular value decomposition
Description
Computes a reduced SVD without sign ambiguity. Our convention is that the sign of each vector in U is chosen such that the coefficient with largest absolute value is positive.
Usage
canonicalSVD(X)
Arguments
X |
the input matrix |
Value
S
U
V
Examples
nu = 10
n = 350
m = 100
A_gamma <- rbind(matrix(0,n,m),-diag(m)/sqrt(nu))
svd.result = canonicalSVD(A_gamma)
S <- svd.result$S
S <- diag(S)
V <- svd.result$V
[Package SplitKnockoff version 2.1 Index]