| mvnt {copent} | R Documentation |
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)