Journal
JOURNAL OF STATISTICAL PLANNING AND INFERENCE
Volume 135, Issue 2, Pages 461-476Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jspi.2004.04.021
Keywords
clustering; multiple regression; model selection; consistency
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In this paper, 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. (c) 2004 Elsevier B.V. All rights reserved.
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