simlr.perm: Assess Significance of SiMLR Call
In stnava/ANTsR: ANTs in R: Quantification Tools for Biomedical Images

simlr.perm

R Documentation

Assess Significance of SiMLR Call

Description

This function performs permutation tests to assess the significance of a SiMLR analysis. For more detail on input parameters, see the original function.

Usage

simlr.perm(
  voxmats,
  smoothingMatrices,
  iterations = 10,
  sparsenessQuantiles,
  positivities,
  initialUMatrix,
  mixAlg = c("svd", "ica", "avg", "rrpca-l", "rrpca-s", "pca", "stochastic"),
  orthogonalize = FALSE,
  repeatedMeasures = NA,
  lineSearchRange = c(-10000000000, 10000000000),
  lineSearchTolerance = 0.00000001,
  randomSeed,
  constraint = c("none", "Grassmann", "Stiefel"),
  energyType = c("cca", "regression", "normalized", "ucca", "lowRank",
    "lowRankRegression"),
  vmats,
  connectors = NULL,
  optimizationStyle = c("lineSearch", "mixed", "greedy"),
  scale = c("centerAndScale", "sqrtnp", "np", "center", "norm", "none", "impute",
    "eigenvalue", "robust"),
  expBeta = 0,
  jointInitialization = TRUE,
  sparsenessAlg = NA,
  verbose = FALSE,
  nperms = 50,
  FUN = "mean"
)

Arguments

`voxmats`	A list of voxel matrices.
`smoothingMatrices`	A list of smoothing matrices.
`iterations`	Number of iterations. Default is 10.
`sparsenessQuantiles`	A vector of sparseness quantiles.
`positivities`	A vector of positivity constraints.
`initialUMatrix`	Initial U matrix for the algorithm.
`mixAlg`	The mixing algorithm to use. Default is 'svd'.
`orthogonalize`	Logical indicating whether to orthogonalize. Default is FALSE.
`repeatedMeasures`	Repeated measures data. Default is NA.
`lineSearchRange`	Range for line search. Default is c(-1e+10, 1e+10).
`lineSearchTolerance`	Tolerance for line search. Default is 1e-08.
`randomSeed`	Seed for random number generation.
`constraint`	The constraint type. Default is 'none'.
`energyType`	The energy type. Default is 'cca'.
`vmats`	List of V matrices - optional initialization matrices
`connectors`	List of connectors. Default is NULL.
`optimizationStyle`	The optimization style. Default is 'lineSearch'.
`scale`	Scaling method. Default is 'centerAndScale'.
`expBeta`	Exponential beta value. Default is 0.
`jointInitialization`	Logical indicating joint initialization. Default is TRUE.
`sparsenessAlg`	Sparseness algorithm. Default is NA.
`verbose`	Logical indicating whether to print verbose output. Default is FALSE. values > 1 lead to more verbosity
`nperms`	Number of permutations for significance testing. Default is 50.
`FUN`	function for summarizing variance explained