A consistent procedure for determining the number of clusters in regression clustering. (English) Zbl 1074.62042

Summary: An information-based criterion for determining the number of clusters in the problem of regression clustering is proposed. It is shown that, under a probabilistically structured population, the proposed criterion selects the true number of regression hyperplanes with probability one among all class-growing sequences of classifications, when the number of observations \(n\) from the population increases to infinity. Results from a simulation study are also presented.


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


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