svd.triplet function

Singular Value Decomposition of a Matrix

Compute the singular-value decomposition of a rectangular matrix with weights for rows and columns.

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

Returns

• 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'.

See Also

svd