Current Volume | Browse | Search | RSSHome | Instructions for Authors | JSS Style Guide | Editorial Board

Authors: Tatiana Benaglia, Didier Chauveau, David R. Hunter, Derek S. Young
Title: [download]
(23506)
mixtools: An R Package for Analyzing Mixture Models
Reference: Vol. 32, Issue 6, Oct 2009
Submitted 2009-04-28, Accepted 2009-08-18
Type: Article
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.

Paper: [download]
(23506)
mixtools: An R Package for Analyzing Mixture Models
(application/pdf, 1.3 MB)
Supplements: [download]
(1142)
mixtools_0.4.3.tar.gz: R source package
(application/x-gzip, 555.5 KB)
[download]
(1271)
v32i06.R: R example code from the paper
(application/octet-stream, 4.1 KB)
Resources: BibTeX | OAI
Creative Commons License
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3)
Current Volume | Browse | Search | RSSHome | Instructions for Authors | JSS Style Guide | Editorial Board