Robust mixture modelling using the t distribution
Robust mixture modelling using the t distribution
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DOI：
10.1023/a:1008981510081
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发表时间：
2000-10-01
影响因子：
2.2
通讯作者：
McLachlan, GJ
中科院分区：
文献类型：
--
作者：
Peel, D;McLachlan, GJ
正态混合模型正越来越多地用于模拟各种随机现象的分布和聚类连续多变量数据集。然而，对于包含一组或多组比正态尾长的观测值或非典型观测值的数据集，使用正态分量可能会过度影响混合模型的拟合。在本文中，我们考虑了一个更强大的方法，通过模拟数据的混合t分布。使用ECM算法来适应这个t混合模型的描述和使用的例子中给出的背景噪声的形式存在的非典型观测的聚类多变量数据的上下文中。
Normal mixture models are being increasingly used to model the distributions of a wide variety of random phenomena and to cluster sets of continuous multivariate data. However, for a set of data containing a group or groups of observations with longer than normal tails or atypical observations, the use of normal components may unduly affect the fit of the mixture model. In this paper, we consider a more robust approach by modelling the data by a mixture of t distributions. The use of the ECM algorithm to fit this t mixture model is described and examples of its use are given in the context of clustering multivariate data in the presence of atypical observations in the form of background noise.