SimX

<p>A simulated dataset with 2 groups and 80 observations. Each group consists of 40 observations, 5 of which are outliers.</p>

datasets

Implements finite mixtures of matrix-variate contaminated normal distributions via expectation conditional-maximization algorithm for model-based clustering, as described in Tomarchio et al.(2020) <arXiv:2005.03861>. One key advantage of this model is the ability to automatically detect potential outlying matrices by computing their a posteriori probability of being typical or atypical points. Finite mixtures of matrix-variate t and matrix-variate normal distributions are also implemented by using expectation-maximization algorithms.

Michael P.B. Gallaugher

MatrixMixtures

Model-Based Clustering via Matrix-Variate Mixture Models

Salvatore D. Tomarchio

Antonio Punzo

Paul D. McNicholas

SimX function

<p>An object of class <code>list</code> of length 80.</p>

Format

Simulated Data — SimX

Simulated Data

SimX: Simulated Data

Description

Usage

Arguments

Format