变量的有限混合模型对有序数据的Bayes聚类分析

本文基于隐变量的有限混合模型, 提出了一种用于有序数据的Bayes聚类方法\bd 我们采用EM算法获得模型参数的估计, 用BIC准则确定类数, 用类似于Bayes判别的方法对各观测分类\bd 模拟研究结果表明, 本文提出的方法有较好的聚类效果, 对于中等规模的数据集, 计算量是可以接受的.

Bayesian Clustering for Ordinal Data Based on Finite Mixture Models of Latent Variables

Based on finite mixture models of latent variables, we propose a Bayesian clustering metnod for ordinal data. EM algorithm is employed to compute the estimates of model parameters, BIC criterion is adopted to determine the number of clusters, and an analogue procedure of Bayesian discrimination is used to classify each observation. The results of a simulation study show that the method works well, and the computing efficiency is acceptable for a dataset of moderate size.