opnmfR_test_ranksel_synthetic: Rank selection test on synthetic data Runs all three avilable...

In kaurao/opnmfR: Orthogonal Projective Non-negative Matrix Factorization

Description

Rank selection test on synthetic data Runs all three avilable rank selection methods.

Usage

opnmfR_test_ranksel_synthetic(
  n = 100,
  r = 10,
  p = 100,
  rs = NULL,
  W0 = "nndsvd",
  nrepeat = 1
)

Arguments

n	A number, number of rows (default 100)
r	A number, true rank (default 10)
p	A number, number of columns (default 100)
rs	A vector with the ranks you wish to test for selection, if rs=NULL then 1:min(nrow(X), round(r+r*0.5)) is used (default NULL)
W0	A string or matrix for initialization (default "nndsvd")
nrepeat	A number, number of iterations for rank selection, i.e. number of permutations for opnmfR_ranksel_perm and number of split-halves for opnmfR_ranksel_splithalf (default 1)

Value

A list with rank selection outputs from opnmfR_ranksel_perm, opnmfR_ranksel_ooser, and opnmfR_ranksel_splithalf

See Also

opnmfR_ranksel_perm, opnmfR_ranksel_ooser, and opnmfR_ranksel_splithalf

Examples

result <- opnmfR_test_ranksel_synthetic()

kaurao/opnmfR documentation built on March 12, 2021, 4:15 a.m.