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August 2019 An Overview of Semiparametric Extensions of Finite Mixture Models
Sijia Xiang, Weixin Yao, Guangren Yang
Statist. Sci. 34(3): 391-404 (August 2019). DOI: 10.1214/19-STS698

Abstract

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.

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Sijia Xiang. Weixin Yao. Guangren Yang. "An Overview of Semiparametric Extensions of Finite Mixture Models." Statist. Sci. 34 (3) 391 - 404, August 2019. https://doi.org/10.1214/19-STS698

Information

Published: August 2019
First available in Project Euclid: 11 October 2019

zbMATH: 07162129
MathSciNet: MR4017520
Digital Object Identifier: 10.1214/19-STS698

Rights: Copyright © 2019 Institute of Mathematical Statistics

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Vol.34 • No. 3 • August 2019
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