sLEDOnePermute: One permutation of sLED

Description Usage Arguments Value See Also

Description

One permutation of sLED

Usage

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sLEDOnePermute(i, Z, n1, n2, seeds = NULL, sumabs.seq = 0.2,
  adj.beta = -1, rho = 1000, verbose = TRUE, niter = 20,
  trace = FALSE)

Arguments

i

the i-th permutation

Z

(n1+n2)-by-p matrix, containing the pooled samples from two populations. Columns are features.

n1

the first n1 rows in Z represent the first population

n2

the (n1+1):(n1+n2) rows in Z represent the second population

seeds

a numeric vector, where seeds[i] specifies the seeding for the i-th permutation. Set to NULL if do not want to specify.

sumabs.seq

a numeric vector specifing the sequence of sparsity parameters to use, each between 1/sqrt(p) and 1.

adj.beta

a positive number representing the power to transform correlation matrices to weighted adjacency matrices by A_{ij} = |r_ij|^adj.beta, where r_ij represents the Pearson correlation. When adj.beta=0, the correlation marix is used. When adj.beta<0, the covariance matrix is used. The default value is adj.beta=-1.

rho

a large positive constant such that A(X)-A(Y)+diag(rep(rho, p)) is positive definite.

verbose

whether to print the progress during permutation tests

niter

the number of iterations to use in the PMD algorithm (see symmPMD())

trace

whether to trace the progress of PMD algorithm (see symmPMD())

Value

A list containing the following components:

Tn.permute

A number represents the test statistic in this permutation.

Tn.permute.sign

A string, "pos" if the test statistic is given by sEig(D), and "neg" if is given by sEig(-D), where sEig denotes the sparse leading eigenvalue.

See Also

sLEDpermute().


lingxuez/sLED documentation built on May 7, 2019, 2:55 a.m.