<b>mixtools</b>: An<i>R</i>Package for Analyzing Finite Mixture Models 论文

2009Journal of Statistical Software引用 1300顶会
Bayesian Methods and Mixture ModelsDiverse Scientific and Engineering ResearchStatistical Methods and Bayesian Inference

详细信息

发表期刊/会议
Journal of Statistical Software
发表日期
2009-01-01
发表年份
2009

关键词

Bayesian Methods and Mixture ModelsDiverse Scientific and Engineering ResearchStatistical Methods and Bayesian Inference

摘要

The <b>mixtools</b> package for <code>R</code> 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, <b>mixtools</b> 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 <b>mixtools</b> package are EM algorithms or are based on EM-like ideas, so this article includes an overview of EM algorithms for finite mixture models.