permutation_test: Permutation test for (partial) correlation on non-Gaussian...

In kpj/dce: Pathway Enrichment Based on Differential Causal Effects

Permutation test for (partial) correlation on non-Gaussian data

Description

Computes the significance of (partial) correlation based on permutations of the observations

Usage

permutation_test(x, y, iter = 1000, fun = pcor, mode = 1, ...)

Arguments

x	wild type data set
y	mutant data set
iter	number of iterations (permutations)
fun	function to compute the statistic, e.g., cor or pcor
mode	either 1 for a function that takes a single data set and produces an output of class matrix, and 2, if the function takes two data sets
...	additional arguments for function 'fun'

Value

matrix of p-values

Examples

x <- matrix(rnorm(100),10,10)
y <- matrix(rnorm(100),10,10)
permutation_test(x,y,iter=10)

kpj/dce documentation built on Oct. 29, 2022, 1:40 a.m.