MixSim: Simulating Data to Study Performance of Clustering Algorithms

The utility of this package is in 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.

Install the latest version of this package by entering the following in R:
AuthorVolodymyr Melnykov [aut], Wei-Chen Chen [aut, cre], Ranjan Maitra [aut], Robert Davies [ctb] (quadratic form probabilities), Stephen Moshier [ctb] (eigenvalue calculations), Rouben Rostamian [ctb] (memory allocation)
Date of publication2015-10-22 15:23:14
MaintainerWei-Chen Chen <wccsnow@gmail.com>
LicenseGPL (>= 2)

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