| RperT2 {MVTests} | R Documentation |
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 <hasan.bulut@omu.edu.tr>
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 (Unpublished)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