Nonparametric estimation of finite mixtures from repeated measurements

Koen Jochmans, Stéphane Bonhomme and Jean-Marc Robin
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Stéphane Bonhomme: University of Chicago

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Abstract: This paper provides methods to estimate finite mixtures from data with repeated measurements non-parametrically. We present a constructive identification argument and use it to develop simple two-step estimators of the component distributions and all their functionals. We discuss a computationally efficient method for estimation and derive asymptotic theory. Simulation experiments suggest that our theory provides confidence intervals with good coverage in small samples.

Keywords: Finite mixture; Repeated measurement data; Reweighting; Two-step estimation (search for similar items in EconPapers)
Date: 2015-02
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Published in Journal of the Royal Statistical Society: Series B, 2015, 78 (1), ⟨10.1111/rssb.12110⟩

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Related works:
Journal Article: Non-parametric estimation of finite mixtures from repeated measurements (2016)
Working Paper: Nonparametric estimation of finite mixtures from repeated measurements (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:hal:spmain:hal-03568247

DOI: 10.1111/rssb.12110

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