View source: R/multiscaleSVDxpts.R
simlrU | R Documentation |
simlr minimizes reconstruction error across related modalities. One crucial component of the reconstruction is the low-dimensional cross-modality basis. This function computes that basis, given a mixing algorithm.
simlrU(
projections,
mixingAlgorithm,
initialW,
orthogonalize = FALSE,
connectors = NULL
)
projections |
A list that contains the low-dimensional projections. |
mixingAlgorithm |
the elected mixing algorithm. see |
initialW |
initialization matrix size |
orthogonalize |
boolean |
connectors |
a list ( length of projections or number of modalities ) that indicates which modalities should be paired with current modality |
u matrix for modality i
BB Avants.
simlr
set.seed(1500)
nsub <- 25
npix <- c(100, 200, 133)
nk <- 5
outcome <- matrix(rnorm(nsub * nk), ncol = nk)
outcome1 <- matrix(rnorm(nsub * nk), ncol = nk)
outcome2 <- matrix(rnorm(nsub * nk), ncol = nk)
u <- simlrU(list(outcome, outcome1, outcome2), 2, "avg")
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