Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
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Authors: Volodymyr Melnykov, Wei-Chen Chen, Ranjan Maitra
Title: MixSim: An R Package for Simulating Data to Study Performance of Clustering Algorithms
Abstract: The R package MixSim is a new tool that allows simulating mixtures of Gaussian distributions with different levels of overlap between mixture components. Pairwise overlap, defined as a sum of two misclassification probabilities, measures the degree of interaction between components and can be readily employed to control the clustering complexity of datasets simulated from mixtures. These datasets can then be used for systematic performance investigation of clustering and finite mixture modeling algorithms. Among other capabilities of MixSim, there are computing the exact overlap for Gaussian mixtures, simulating Gaussian and non-Gaussian data, simulating outliers and noise variables, calculating various measures of agreement between two partitionings, and constructing parallel distribution plots for the graphical display of finite mixture models. All features of the package are illustrated in great detail. The utility of the package is highlighted through a small comparison study of several popular clustering algorithms.

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Paper: MixSim: An R Package for Simulating Data to Study Performance of Clustering Algorithms     Download PDF (Downloads: 10540)
MixSim_1.0-8.tar.gz: R source package Download (Downloads: 600; 39KB)
v51i12.R: R example code from the paper Download (Downloads: 647; 7KB)

DOI: 10.18637/jss.v051.i12

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.