RobCat: Robust CAT Algorithm

In MVTests: Multivariate Hypothesis Tests

Robust CAT Algorithm

Description

RobCat computes p value based on robust CAT algorithm to compare two means vectors under multivariate Behrens-Fisher problem.

Usage

RobCat(X, Y, M = 1000, alpha = 0.75)

Arguments

X	a matrix or data frame for first group.
Y	a matrix or data frame for second group.
M	iteration number and the default is 1000.
alpha	numeric parameter controlling the size of the subsets over which the determinant is minimized; roughly alpha*n, observations are used for computing the determinant. Allowed values are between 0.5 and 1 and the default is 0.75.

Details

This function computes p value based on robust CAT algorithm to compare two means vectors under multivariate Behrens-Fisher problem. When p value<0.05, it means the difference of two mean vectors is significant statistically.

Value

a list with 2 elements:

Cstat	Calculated value of test statistic
pval	The p value

Author(s)

Hasan BULUT <[e-mail]>

Examples

data(iris)
RobCat(X=iris[1:20,-5],Y=iris[81:100,-5])

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