pickSVD {ExPosition}

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

Description

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.

Usage

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.

Value

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