| runRandomSVD {BiocSingular} | R Documentation |
Perform a randomized singular value decomposition.
runRandomSVD(x, k=5, nu=k, nv=k, center=FALSE, scale=FALSE, deferred=FALSE,
..., fold=Inf, BPPARAM=SerialParam())
x |
A numeric matrix-like object to use in the SVD. |
k |
Integer scalar specifying the number of singular values to return. |
nu |
Integer scalar specifying the number of left singular vectors to return. |
nv |
Integer scalar specifying the number of right singular vectors to return. |
center |
A logical scalar indicating whether columns should be centered.
Alternatively, a numeric vector or |
scale |
A logical scalar indicating whether columns should be scaled.
Alternatively, a numeric vector or |
deferred |
Logical scalar indicating whether centering/scaling should be deferred, see |
... |
Further arguments to pass to |
fold |
Numeric scalar specifying the minimum fold difference between dimensions of |
BPPARAM |
A BiocParallelParam object specifying how parallelization should be performed. |
All multiplication operations in rsvd involving x will be parallelized according to the supplied BPPARAM.
The dimensionality of the working subspace is defined as the maximum of k, nu and nv, plus the q specified in ....
A list containing:
d, a numeric vector of the first k singular values.
u, a numeric matrix with nrow(x) rows and nu columns.
Each column contains a left singular vector.
u, a numeric matrix with ncol(x) rows and nv columns.
Each column contains a right singular vector.
Aaron Lun
rsvd for the underlying algorithm.
a <- matrix(rnorm(100000), ncol=20) out <- runRandomSVD(a) str(out)