mvnt: Multivariate normality test with copula entropy

In copent: Estimating Copula Entropy and Transfer Entropy

Multivariate normality test with copula entropy

Description

Estimating the statistic for testing multivariate normality based on copula entropy.

Usage

mvnt(x,k=3,dt=2)

Arguments

x	data with each row as a sample of d-dimensional random variables
k	kth nearest neighbour, default = 3
dt	the type of distance between samples, 1 for Eclidean distance; 2 for Maximum distance

Details

This program involves estimating the statistic for testing multivariate normality based on copula entropy. It was proposed in Ma (2022). The test statistic is defined as the difference between the copula entropies of unknown distribution and the Gaussian distribution with same covariance.

The argument x is for the data with each row as a sample of d-dimensional random variables. The argument k and dt is used in the kNN method for estimating entropy. k is for the kth nearest neighbour (default = 3) and dt is for the type of distance between samples which has currently two value options (1 for Eclidean distance, and 2(default) for Maximum distance).

Value

The function returns the statistic for testing multivariate normality of x.

References

Ma, Jian. Multivariate Normality Test with Copula Entropy. arXiv preprint arXiv:2206.05956, 2022.

Examples

library(mnormt)
rho <- 0.5
sigma <- matrix(c(1,rho,rho,1),2,2)
x <- rmnorm(1000,c(0,0),sigma)
mvnt(x)

copent documentation built on June 22, 2024, 9:56 a.m.