The V test computes the p-value of a multivariate dataset, which informs the user about one of two decisions: (1) whether the sample is exchangeable at a given significance level, assuming that the feature dependencies are known; or (2) whether the features or groups of features are independent at a given significance level, assuming that the sample is exchangeable. This version takes in a list of distance matrices recording pairwise distances between individuals across \(B\) independent features. It can be used to test one of two hypotheses: (H1) the sample is exchangeable, assuming that each feature whose pairwise distance data is available is statistically independent of any other feature, or (H2) the \(B\) features whose pairwise distance data is available are independent, assuming that the sample is exchangeable.
distDataPValue(dist_list, largeP = FALSE, nruns = 1000, type = "unbiased")The p-value to be used to test the null hypothesis of exchangeability.
The list of distances.
Boolean indicating whether to use large \(P\) asymptotics. Default is FALSE.
Resampling number for exact test. Default is 1000.
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'. Note that unbiased estimate can return \(0\).
Dependencies: distDataLargeP and distDataPermute from auxiliary.R