mmcm: Use the Mahalnobis-type multisample test based on optimal...

In multicross: A Graph-Based Test for Comparing Multivariate Distributions in the Multi Sample Framework

Description

Use the Mahalnobis-type multisample test based on optimal matching to compare K different multivariate distributions

Usage

mmcm(data_list, level)

Arguments

data_list	is list of multifeature matrices corresponding to the K different classes, so each element of the list is a matrix, for a total of K matrices.
level	is the cutoff value (alpha) for hypothesis testing

Value

The p-value corresponding to rejection of the alternative, along with the decision of the hypothesis testing (Null being accepted versus rejected)

Examples

# Simulation Example when the user wants to test whether K=3 multivariate distributions are equal:
X1 = MASS::mvrnorm(10,rep(0,4),diag(2,4),tol=1e-6, empirical=FALSE, EISPACK=FALSE)
X2 = MASS::mvrnorm(10,rep(0,4),diag(1,4),tol=1e-6, empirical=FALSE, EISPACK=FALSE)
X3 = MASS::mvrnorm(10,rep(0,4),diag(3,4),tol=1e-6, empirical=FALSE, EISPACK=FALSE)
mmcm(list(X1,X2,X3), 0.05)

multicross documentation built on July 8, 2020, 7:29 p.m.