| svd {kazaam} | R Documentation |
svd
Description
Singular value decomposition.
Usage
## S4 method for signature 'shaq'
svd(x, nu = min(n, p), nv = min(n, p), LINPACK = FALSE)
Arguments
x |
A shaq. |
nu |
number of left singular vectors to return. |
nv |
number of right singular vectors to return. |
LINPACK |
Ignored. |
Details
The factorization works by first forming the crossproduct X^T X
and then taking its eigenvalue decomposition. In this case, the square root
of the eigenvalues are the singular values. If the left/right singular
vectors U or V are desired, then in either case, V is
computed (the eigenvectors). From these, U can be reconstructed, since
if X = U\Sigma V^T, then U = XV\Sigma^{-1}.
Value
A list of elements d, u, and v, as with R's own
svd(). The elements are, respectively, a regular vector, a shaq, and
a regular matrix.
Communication
The operation is completely local except for forming the crossproduct, which
is an allreduce() call, quadratic on the number of columns.
Examples
## Not run:
library(kazaam)
x = ranshaq(runif, 10, 3)
svd = svd(x)
comm.print(svd$d) # a globally owned vector
svd$u # a shaq
comm.print(svd$v) # a globally owned matrix
finalize()
## End(Not run)