computeDimReduction: Compute dimensionality reduction

In HannahVMeyer/drStable: Estimating the stability of dimensionality reduction results

Description

Compute low-dimensional representation of dataset.

Usage

computeDimReduction(Y, method, optN = NULL, ndim = NULL, kmin = 1,
  kmax = 40, verbose = FALSE, parallel = FALSE,
  is.list.ellipsis = FALSE, ...)

Arguments

Y	\[N x P\] data matrix for which the dimensionality of P should be reduced
method	Dimensionality reduction method [character] to be applied; one of DiffusionsMaps, DRR, ICA, LLE, Isomap, LaplacianEigenmap, MDS, PCA, kPCA, nMDS, tSNE and UMAP.
optN	optimal number [integer] of neighbours to consider for dimensionality reduction; relevant for methods LLE, LaplacianEigenmaps, Isomap and tSNE. If not provided, will be estimated via calc_k.
ndim	maximum dimensionality [integer] to retain in the data; large values can cause long computation times; if not provided max(P,N) is chosen.
kmin	if optN is not provided, kmin [integer] specifies the minimum number of neighbours supplied to calc_k.
kmax	if optN is not provided, kmax [integer] specifies the maximum number of neighbours supplied to calc_k.
verbose	[logical] If set, progress messages are printed to standard out.
parallel	[logical] if optN is not provided and parallel TRUE, parallel computation on multiple cpu cores is used with calc_k.
is.list.ellipsis	[logical] if ... arguments are provided as list, set TRUE.
...	Additional arguments passed to dimensionality reduction methods. For possible arguments, check function decomentation. See details for relevant packages and functions.

Value

named list of results from dimensionality reduction: Y_red: named list with dimensionality reduced phenotypes (reducedY) and object returned by specified dimensionality reduction method (results) with additional output M: vector [double] with Trustworthiness and Continuity estimates for the dimensionality reduction

Examples

# Generate some data
x <- matrix(rnorm(10000), nrow=10, ncol=100)
y <- x %*% diag(nrow=100) * rnorm(100)
dr <- computeDimReduction(y, method="MDS")

HannahVMeyer/drStable documentation built on Jan. 29, 2021, 11:42 a.m.