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: Tatiana Benaglia, Didier Chauveau, David R. Hunter, Derek S. Young
Title: mixtools: An R Package for Analyzing Mixture Models
Abstract: The mixtools package for R provides a set of functions for analyzing a variety of finite mixture models. These functions include both traditional methods, such as EM algorithms for univariate and multivariate normal mixtures, and newer methods that reflect some recent research in finite mixture models. In the latter category, mixtools provides algorithms for estimating parameters in a wide range of different 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 unspecified, and in semiparametric situations such as a univariate location mixture of symmetric but otherwise unspecified 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 finite mixture models.

Page views:: 40235. Submitted: 2009-04-28. Published: 2009-10-21.
Paper: mixtools: An R Package for Analyzing Mixture Models     Download PDF (Downloads: 43574)
mixtools_0.4.3.tar.gz: R source package Download (Downloads: 1630; 555KB)
v32i06.R: R example code from the paper Download (Downloads: 1873; 4KB)

DOI: 10.18637/jss.v032.i06

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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.