initializeSimlr: Initialize simlr

In neuroconductor-devel/ANTsR: ANTs in R: Quantification Tools for Biomedical Images

Description

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.

Usage

initializeSimlr(
  voxmats,
  k,
  jointReduction = FALSE,
  zeroUpper = FALSE,
  uAlgorithm = "svd",
  addNoise = 0
)

Arguments

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 "svd", "random", "randomProjection", eigenvalue, "pca" (default), "ica" or "cca"
addNoise	scalar value that adds zero mean unit variance noise, multiplied by the value of addNoise

Value

A single matrix or list of matrices

Author(s)

BB Avants.

Examples

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' )

neuroconductor-devel/ANTsR documentation built on April 1, 2021, 1:02 p.m.