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)a data matrix to decompose.
a boolean. TRUE for a MDS decomposition.
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.
numeric. The number of components to return.
A list with the following items:
Left singular vectors (rows)
Right singular vectors (columns)
Singular values
Explained variance per component