TITLE(svd @@ Singular Value Decomposition of a Matrix )
USAGE(
svd(x, nu=min(n,p), nv=min(n,p))
)
ALIAS(svd)
ARGUMENTS(
ARG(x @@ a matrix whose SVD decomposition is to be computed.)
ARG(nu @@ the number of left eigenvectors to be computed.
This must be one of LANG(0), LANG(nrow(x)) and LANG(ncol(x)).)
ARG(nv @@ the number of right eigenvectors to be computed.
This must be one of LANG(0), and LANG(ncol(x)).)
)
DESCRIPTION(
LANG(svd) provides an interface to the LINPACK routine DSVDC.
The singular value decompostion plays an important role in many
statistical techniques.
)
VALUES(
The SVD decomposition of the matrix
as computed by LINPACK.
The components in the returned value correspond directly
to the values returned by DSVDC. @@
ARG(d @@ a vector containing the singular values of LANG(x).)
ARG(u @@ a matrix whose columns contain the left eigenvectors of LANG(x).)
ARG(v @@ a matrix whose columns contain the right eigenvectors of LANG(x).)
)
REFERENCES(
Dongarra, J. J., J. R. Bunch, C. B. Moler and G. W. Stewart (1978).
ITALIC(LINPACK Users Guide), SIAM Publications, Philadelphia.
)
SEEALSO(
LANG(LINK(qr)).
)
