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
vsa vector containing the singular values of 'x';
ua matrix whose columns contain the left singular vectors of 'x';
va matrix whose columns contain the right singular vectors of 'x'.