Ana Oliveira-Brochado () (Faculdade de Economia, Universidade do Porto) Francisco Vitorino Martins () (Faculdade de Economia, Universidade 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).
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Publisher Info
Paper provided by Universidade do Porto, Faculdade de Economia do Porto in its series FEP Working Papers with number
194.
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