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

In ExPosition: Exploratory Analysis with the Singular Value Decomposition

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

ExPosition documentation built on May 1, 2019, 7:06 p.m.