dot-wassersteinTestSp: Semi-parametric test using the 2-Wasserstein distance to...

Description Usage Arguments Details Value References

Description

Two-sample test to check for differences between two distributions using the 2-Wasserstein distance: Semi-parametric implementation using a permutation test with a generalized Pareto distribution (GPD) approximation to estimate small p-values accurately

Usage

1
.wassersteinTestSp(x, y, permnum = 10000)

Arguments

x

sample (vector) representing the distribution of condition A

y

sample (vector) representing the distribution of condition B

permnum

number of permutations used in the permutation testing procedure

Details

This is the semi-parametric version of wasserstein.test, for the asymptotic theory-based procedure see .wassersteinTestAsy.

Details concerning the permutation testing procedure with GPD approximation to estimate small p-values accurately can be found in Schefzik et al. (2020).

Value

A vector of 15, see Schefzik et al. (2020) for details:

References

Schefzik, R., Flesch, J., and Goncalves, A. (2020). waddR: Using the 2-Wasserstein distance to identify differences between distributions in two-sample testing, with application to single-cell RNA-sequencing data.


goncalves-lab/diffexpR documentation built on Oct. 26, 2021, 5:08 p.m.