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Computes the p-value of a multivariate dataset, which informs the user if the sample is exchangeable at a given significance level, while simultaneously accounting for feature dependencies. See Aw, Spence and Song (2021) for details.

distDataPValue(dist_list, largeP = FALSE, nruns = 1000, type = "unbiased")

Arguments

dist_list

The list of distances.

largeP

Boolean indicating whether to use large P asymptotics. Default is FALSE.

nruns

Resampling number for exact test. Default is 1000.

type

Either an unbiased estimate of (`'unbiased'`, default), or valid, but biased estimate of, (`'valid'`) p-value (see Hemerik and Goeman, 2018), or both (`'both'`). Default is `'unbiased'`.

Value

The p-value to be used to test the null hypothesis of exchangeability.

Details

This version takes in a list of distance matrices recording pairwise distances between individuals across B independent features.

Dependencies: distDataLargeP and distDataPermute from auxiliary.R