View source: R/multiscaleSVDxpts.R
initializeSimlr | R Documentation |
Four initialization approaches for simlr. Returns either a single matrix
derived from dimensionality reduction on all matrices bound together
(jointReduction=TRUE
) or a list of reduced
dimensionality matrices, one for each input. Primarily, a helper function
for SiMLR.
initializeSimlr(
voxmats,
k,
jointReduction = FALSE,
zeroUpper = FALSE,
uAlgorithm = "svd",
addNoise = 0
)
voxmats |
list that contains the named matrices. |
k |
rank of U matrix |
jointReduction |
boolean determining whether one or length of list bases are returned. |
zeroUpper |
boolean determining whether upper triangular part of initialization is zeroed out |
uAlgorithm |
either |
addNoise |
scalar value that adds zero mean unit variance noise, multiplied
by the value of |
A single matrix or list of matrices
BB Avants.
set.seed(1500)
nsub <- 3
npix <- c(10, 6, 13)
nk <- 2
outcome <- initializeSimlr(
list(
matrix(rnorm(nsub * npix[1]), ncol = npix[1]),
matrix(rnorm(nsub * npix[2]), ncol = npix[2]),
matrix(rnorm(nsub * npix[3]), ncol = npix[3])
),
k = 2, uAlgorithm = "pca"
)
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