Description Usage Arguments Value Examples

In this packcage, we present a framework inspired by Rosenbaum's crossmatch idea to tackle the nonparametric, multisample problem wherein one is concerned with testing the equality of K unknown multivariate probability distributions. We implement two tests: the first is a multisample generalization of Rosenbaum's crossmatch (MCM), and the other further introduces a Malahnobis-type modification to the test (MMCM).

1 | ```
mcm(data_list, level)
``` |

`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. Each matrix contains observations as the rows and features as the columns |

`level` |
is the level alpha for hypothesis testing |

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

1 2 3 4 5 | ```
# 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)
mcm(list(X1,X2,X3),0.05)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.