pickSVD function

Pick which generalized SVD (or related) decomposition to use.

This function is an interface for the user to a general SVD or related decomposition. It provides direct access to svd and eigen. Future decompositions will be available.

pickSVD(datain, is.mds = FALSE, decomp.approach = "svd", k = 0)

Arguments

• datain: a data matrix to decompose.
• is.mds: a boolean. TRUE for a MDS decomposition.
• decomp.approach: a string. 'svd' for singular value decomposition, 'eigen' for an eigendecomposition. All approaches provide identical output. Some approaches are (in some cases) faster than others.
• k: numeric. The number of components to return.

Returns

A list with the following items:

• u: Left singular vectors (rows)

• v: Right singular vectors (columns)

• d: Singular values

• tau: Explained variance per component

Author(s)

Derek Beaton