mixtools: An R Package for Analyzing Finite Mixture Models

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Authors Tatiana Benaglia, Didier Chauveau, David R. Hunter, D. S. Young
Journal/Conference Name Journal of Statistical Software
Paper Category
Paper Abstract The mixtools package for R provides a set of functions for analyzing a variety of nite mixture models. These functions include both traditional methods, such as EM algorithms for univariate and multivariate normal mixtures, and newer methods that reect some recent research in nite mixture models. In the latter category, mixtools provides algorithms for estimating parameters in a wide range of dierent mixture-of-regression contexts, in multinomial mixtures such as those arising from discretizing continuous multivariate data, in nonparametric situations where the multivariate component densities are completely unspecied, and in semiparametric situations such as a univariate location mixture of symmetric but otherwise unspecied densities. Many of the algorithms of the mixtools package are EM algorithms or are based on EM-like ideas, so this article includes an overview of EM algorithms for nite mixture models.
Date of publication 2009
Code Programming Language R
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