Svd() provides a singular valued
decomposition. It is a direct translation of the EISPACK routine
with the same name ([24]). The routine decomposes an
rxc matrix A as A = UDV', where
U'U = UU' = Ir,
V'V = VV' = Ic, and a vector S containing the diagonal elements
of D, which are the square roots of the eigenvalues of A'A.
The default is to produce U and V, but this may be turned
off by supplying makev=FFALSE or makeu=FFALSE.
Ginv() produces a generalized inverse of
A using the singular valued decomposition:
A+ = VD+U'. The
matrix D+ is a diagonal matrix with the reciprocals of the
nonzero singular values of A.