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Assessing the Number of Components in Mixture Models: a Review

Ana Oliveira-Brochado () and Francisco Vitorino Martins ()
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Ana Oliveira-Brochado: Faculdade de Economia, Universidade do Porto
Francisco Vitorino Martins: Faculdade de Economia, Universidade do Porto

FEP Working Papers from Universidade do Porto, Faculdade de Economia do Porto

Abstract: Despite the widespread application of finite mixture models, the decision of how many classes are required to adequately represent the data is, according to many authors, an important, but unsolved issue. This work aims to review, describe and organize the available approaches designed to help the selection of the adequate number of mixture components (including Monte Carlo test procedures, information criteria and classification-based criteria); we also provide some published simulation results about their relative performance, with the purpose of identifying the scenarios where each criterion is more effective (adequate).

Keywords: Finite mixture; number of mixture components; information criteria; simulation studies. (search for similar items in EconPapers)
JEL-codes: C15 C52 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2005-11
New Economics Papers: this item is included in nep-ecm
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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