MINTperm: MINTknown In IndepTest: Nonparametric Independence Tests Based on Entropy Estimation

Description

Performs an independence test without knowledge of either marginal distribution using permutations.

Usage

 1 MINTperm(x, y, k, w = FALSE, B = 1000) 

Arguments

 x The n \times d_X data matrix of X values. y The n \times d_Y data matrix of Y values. k The value of k to be used for estimation of the joint entropy H(X,Y). w The weight vector to used for estimation of the joint entropy H(X,Y), with the same options as for the KLentropy function. B The number of permutations to use, set at 1000 by default.

Value

The p-value corresponding the independence test carried out.

References

\insertRef

2017arXiv171106642BIndepTest

Examples

  1 2 3 4 5 6 7 8 9 10 11 # Independent univariate normal data x=rnorm(1000); y=rnorm(1000) MINTperm(x,y,k=20,B=100) # Dependent univariate normal data library(mvtnorm) data=rmvnorm(1000,sigma=matrix(c(1,0.5,0.5,1),ncol=2)) MINTperm(data[,1],data[,2],k=20,B=100) # Dependent multivariate normal data Sigma=matrix(c(1,0,0,0,0,1,0,0,0,0,1,0.5,0,0,0.5,1),ncol=4) data=rmvnorm(1000,sigma=Sigma) MINTperm(data[,1:3],data[,4],k=20,w=TRUE,B=100) 

IndepTest documentation built on May 1, 2019, 10:24 p.m.