arrow
返回

Clustering using objective functions and stochastic search

delete2008-01-04
delete71
delete
OA
AI
J
James G. Booth *
G
George Casella
J
James P. Hobert
DOI:10.1111/j.1467-9868.2007.00629.xdelete
delete原文链接
delete分享
delete收藏
查看原文
摘要

摘要

En 中文
A new approach to clustering multivariate data, based on a multilevel linear mixed model, is proposed. A key feature of the model is that observations from the same cluster are correlated, because they share cluster-specific random effects. The inclusion of cluster-specific random effects allows parsimonious departure from an assumed base model for cluster mean profiles. This departure is captured statistically via the posterior expectation, or best linear unbiased predictor. One of the parameters in the model is the true underlying partition of the data, and the posterior distribution of this parameter, which is known up to a normalizing constant, is used to cluster the data. The problem of finding partitions with high posterior probability is not amenable to deterministic methods such as the EM algorithm. Thus, we propose a stochastic search algorithm that is driven by a Markov chain that is a mixture of two Metropolis-Hastings algorithms-one that makes small scale changes to individual objects and another that performs large scale moves involving entire clusters. The methodology proposed is fundamentally different from the well-known finite mixture model approach to clustering, which does not explicitly include the partition as a parameter, and involves an independent and identically distributed structure.
Keyword:
Bayesian model
best linear unbiased predictor
cluster analysis
linear mixed model
Markov chain Monte Carlo methods
Metropolis-Hastings algorithm
microarray
quadratic penalized splines
set partition
yeast cell cycle
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

J
Journal of the Royal Statistical Society Series B-Statistical Methodology
IF:
3.6
论文数:
1.5K
被引数:
3.2W

机构

State University System of Florida 封面图
State University System of Florida
学者数:
12.8W
论文数: 10.9W
被引数: 130
C
Cornell University
学者数:
6.3W
论文数: 5.4W
被引数: 10.9W
引用论文

引用论文

Gencore: an efficient tool to generate consensus reads for error suppressing and duplicate removing of NGS data
err2019-12-27
err0
errOAAI
errShifu Chen; Yanqing Zhou; Yaru Chen; Tanxiao Huang; Wenting Liao; Yun Xu; Zhicheng Li; Jia Gu
err分享
err收藏
Counterion-Mediated Decompaction of Liquid Crystalline Chromosomes
err2012-12-01
err0
PREAI
errShiyong Sun; Joseph T.Y. Wong; Mingxue Liu; Faqin Dong
err分享
err收藏
学者 查看更多内容