distcov.test: Performs a distance covariance test
In jofie/DistCov: Functions for distance correlations

Performs a distance covariance test

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distcov.test(X, Y, test = "permutation", b = 499L, affine = FALSE,
  bias.corr = TRUE, type.X = "sample", type.Y = "sample",
  metr.X = "euclidean", metr.Y = "euclidean", use = "all")

`X`	contains either the first sample or its corresponding distance matrix. In the first case, this input can be either a vector of positive length, a matrix with one column or a data.frame with one column. In this case, type.X must be specified as "sample". In the second case, the input must be a distance matrix corresponding to the sample of interest. In this second case, type.X must be "distance".
`Y`	see X.
`test`	specifies the type of test that is performed, "permutation" performs a Monte Carlo Permutation test. "gamma" performs a test based on a gamma approximation of the test statistic under the null.
`b`	specifies the number of random permutations used for the permutation test. Ignored when test="gamma"
`affine`	logical; indicates if the affinely transformed distance covariance should be calculated or not.
`bias.corr`	logical; indicates if the bias corrected version of the sample distance covariance should be calculated, currently ignored when test="gamma"
`type.X`	either "sample" or "distance"; specifies the type of input for X.
`type.Y`	see type.X.
`metr.X`	specifies the metric which should be used for X to analyse the distance covariance. TO DO: Provide details for this.
`metr.Y`	see metr.X.
`use`	: "all" uses all observations, "complete.obs" excludes NA's