cosinePerm: Computes the cosine similarity and significance using...

In CoreGx: Classes and Functions to Serve as the Basis for Other 'Gx' Packages

Description

Computes the cosine similarity and significance using permutation test

Usage

cosinePerm(x, y, nperm = 1000, alternative = c("two.sided", "less",
  "greater"), include.perm = FALSE, setseed = 12345, nthread = 1)

Arguments

x	[factor] is the factors for the first variable
y	[factor] is the factors for the second variable
nperm	[integer] is the number of permutations to comput ethe null distribution of MCC estimates
alternative	[string] indicates the alternative hypothesis and must be one of ‘"two.sided"’, ‘"greater"’ or ‘"less"’. You can specify just the initial letter. ‘"greater"’ corresponds to positive association, ‘"less"’ to negative association. Options are "two.sided", "less", or "greater"
include.perm	[boolean] indicates whether the estimates for the null distribution should be returned. Default set to 'FALSE'
setseed	[integer] is the seed specified by the user. Defaults is '12345'
nthread	[integer] is the number of threads to be used to perform the permutations in parallel

Value

[list] estimate of the cosine similarity, p-value and estimates after random permutations (null distribution) in include.perm is set to 'TRUE'

Examples

x <- factor(c(1,2,1,2,1))
y <- factor(c(2,2,1,1,1))
cosinePerm(x, y)

CoreGx documentation built on Dec. 20, 2019, 1:08 a.m.