MINTauto {IndepTest} | R Documentation |
MINTauto
Description
Performs an independence test without knowledge of either marginal distribution using permutations and using a data-driven choice of k
.
Usage
MINTauto(x, y, kmax, B1 = 1000, B2 = 1000)
Arguments
x |
The |
y |
The response vector of length |
kmax |
The maximum value of |
B1 |
The number of repetitions used when choosing |
B2 |
The number of permutations to use for the final test, set at 1000 by default. |
Value
The p
-value corresponding the independence test carried out and the value of k
used.
References
Berrett, T. B. and Samworth R. J. (2017). “Nonparametric independence testing via mutual information.” ArXiv e-prints. 1711.06642.
Examples
# Independent univariate normal data
x=rnorm(1000); y=rnorm(1000);
MINTauto(x,y,kmax=200,B1=100,B2=100)
# Dependent univariate normal data
library(mvtnorm)
data=rmvnorm(1000,sigma=matrix(c(1,0.5,0.5,1),ncol=2))
MINTauto(data[,1],data[,2],kmax=200,B1=100,B2=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)
MINTauto(data[,1:3],data[,4],kmax=50,B1=100,B2=100)
[Package IndepTest version 0.2.0 Index]