moments.for.pearson

<p>the means of the distance matrices</p>

mmean

<p>computes the moments as required for Pearson's approximation</p>

internal

Distance multivariance is a measure of dependence which can be used to detect
and quantify dependence of arbitrarily many random vectors. The necessary functions are
implemented in this packages and examples are given. It includes: distance multivariance,
distance multicorrelation, dependence structure detection, tests of independence and
copula versions of distance multivariance based on the Monte Carlo empirical transform.
Detailed references are given in the package description, as starting point for the
theoretic background we refer to:
B. B<c3><b6>ttcher, Dependence and Dependence Structures: Estimation and Visualization Using
the Unifying Concept of Distance Multivariance. Open Statistics, Vol. 1, No. 1 (2020),
<doi:10.1515/stat-2020-0001>.

Bj<c3><b6>rn B<c3><b6>ttcher

moments.for.pearson: computes the moments as required for Pearson's approximation

Description

Usage

Arguments

Details