RperT2: Robust Permutation Hotelling T^2 Test in High Dimensional...

In MVTests: Multivariate Hypothesis Tests

Robust Permutation Hotelling T^2 Test in High Dimensional Data

Description

Robust Permutation Hotelling T^2 Test for Two Independent Samples in high Dimensional Data

Usage

RperT2(X1, X2, alpha = 0.75, N = 100)

Arguments

X1	the data matrix for the first group. It must be matrix or data.frame.
X2	the data matrix for the first group. It must be matrix or data.frame.
alpha	numeric parameter controlling the size of the subsets over which the determinant is minimized. Allowed values are between 0.5 and 1 and the default is 0.75.
N	the permutation number

Details

RperT2 function performs a robust permutation Hotelling T^2 test for two independent samples in high dimensional test based on the minimum regularized covariance determinant estimators.

Value

a list with 2 elements:

T2	The calculated value of Robust Hotelling T^2 statistic based on MRCD estimations
p.value	p value obtained from test process

Author(s)

Hasan BULUT <[e-mail]>

References

Bulut, H (2023). A robust Hotelling test statistic for two samples case in high dimensional data. (Unpublished)

Examples

library(rrcov)
x<-mvtnorm::rmvnorm(n=10,sigma=diag(20),mean=rep(0,20))
y<-mvtnorm::rmvnorm(n=10,sigma=diag(20),mean=rep(1,20))
RperT2(X1=x,X2=y)$p.value

MVTests documentation built on Nov. 3, 2023, 5:11 p.m.