An Overview of Semiparametric Extensions of Finite Mixture Models

• Sijia Xiang ^[2] ; Weixin Yao ^[3] ; Guangren Yang ^[1]
  1. [1] Jinan University

     Jinan University

     China

     
  2. [2] University of Finance & Economics, Hangzhou
  3. [3] University of California

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• Localización: Statistical science, ISSN 0883-4237, Vol. 34, Nº. 3, 2019, págs. 391-404
• Idioma: inglés
• DOI: 10.1214/19-sts698
• Texto completo no disponible (Saber más ...)
• Resumen

  • Finite mixture models have offered a very important tool for exploring complex data structures in many scientific areas, such as economics, epidemiology and finance. Semiparametric mixture models, which were introduced into traditional finite mixture models in the past decade, have brought forth exciting developments in their methodologies, theories, and applications. In this article, we not only provide a selective overview of the newly-developed semiparametric mixture models, but also discuss their estimation methodologies, theoretical properties if applicable, and some open questions. Recent developments are also discussed.