A consistent procedure for determining the number of clusters in regression clustering

DOI10.1016/j.jspi.2004.04.021zbMath1074.62042OpenAlexW2052976402MaRDI QIDQ2573524

Qing Shao, Yuehua Wu

Publication date: 22 November 2005

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2004.04.021

zbMATH Keywords

ClusteringModel selectionConsistencyMultiple regression

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Linear regression; mixed models (62J05)

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Uses Software

• Algorithm 39

Cites Work

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• A maximum likelihood methodology for clusterwise linear regression
• A fast algorithm for clusterwise linear regression
• Model selection with data-oriented penalty
• A strongly consistent procedure for model selection in a regression problem
• Clustering Objects Generated by Linear Regression Models