emp.transf: Monte Carlo empirical transform

In multivariance: Measuring Multivariate Dependence Using Distance Multivariance

Description

Transforms a matrix (rows: samples, columns: variables) into a matrix of uniform samples with the same dependence structure via the Monte Carlo empirical transform.

Usage

emp.transf(x, continuous = FALSE)

Arguments

x	data matrix (rows: samples, columns: variables)
continuous	boolean, if TRUE it provides the classical (non-Monte-Carlo) transformation by the empirical distribution function, which is a reasonable choice for data of continuous distributions.

References

For the theoretic background see the reference [5] given on the main help page of this package: multivariance-package.

multivariance documentation built on Oct. 6, 2021, 5:08 p.m.