单变量
多元统计
R包
编码(集合论)
航程(航空)
组分(热力学)
计算机科学
离散化
混合模型
非参数统计
多项式分布
数学
算法
应用数学
集合(抽象数据类型)
统计
程序设计语言
工程类
航空航天工程
数学分析
物理
热力学
作者
Tatiana Benaglia,Didier Chauveau,David R. Hunter,Derek S. Young
标识
DOI:10.18637/jss.v032.i06
摘要
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.
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