PCAmixdata (version 3.0)

svd.triplet: Singular Value Decomposition of a Matrix

Description

Compute the singular-value decomposition of a rectangular matrix with weights for rows and columns. Borrowed from the 'FactoMineR' package and, used as internal function

Usage

svd.triplet(X, row.w=NULL, col.w=NULL, ncp=Inf)

Arguments

X

a data matrix

row.w

vector with the weights of each row (NULL by default and the weights are uniform)

col.w

vector with the weights of each column (NULL by default and the weights are uniform)

ncp

the number of components kept for the outputs

Value

vs

a vector containing the singular values of 'x';

u

a matrix whose columns contain the left singular vectors of 'x';

v

a matrix whose columns contain the right singular vectors of 'x'.

Details

This function has been taken from the package FactoMineR. It is then identical.

See Also

svd