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The doubly smoothed maximum likelihood estimation for location-shifted semiparametric mixtures

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  • Seo, Byungtae

Abstract

Finite mixture of a location family of distributions are known to be identifiable if the component distributions are common and symmetric. In such cases, several methods have been proposed for estimating both the symmetric component distribution and the model parameters. In this paper, we propose a new estimation method using the doubly smoothed maximum likelihood, which can effectively eliminate potential biases while maintaining a high efficiency. Some numerical examples are presented to demonstrate the performance of the proposed method.

Suggested Citation

  • Seo, Byungtae, 2017. "The doubly smoothed maximum likelihood estimation for location-shifted semiparametric mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 27-39.
    • Handle: RePEc:eee:csdana:v:108:y:2017:i:c:p:27-39
    DOI: 10.1016/j.csda.2016.11.003
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    References listed on IDEAS

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    1. Seo, Byungtae & Lindsay, Bruce G., 2010. "A computational strategy for doubly smoothed MLE exemplified in the normal mixture model," Computational Statistics & Data Analysis, Elsevier, vol. 54(8), pages 1930-1941, August.
    2. Bordes, Laurent & Chauveau, Didier & Vandekerkhove, Pierre, 2007. "A stochastic EM algorithm for a semiparametric mixture model," Computational Statistics & Data Analysis, Elsevier, vol. 51(11), pages 5429-5443, July.
    3. Yong Wang, 2007. "On fast computation of the non‐parametric maximum likelihood estimate of a mixing distribution," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(2), pages 185-198, April.
    4. Laurent Bordes & Céline Delmas & Pierre Vandekerkhove, 2006. "Semiparametric Estimation of a Two‐component Mixture Model where One Component is known," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 33(4), pages 733-752, December.
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    Cited by:

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    2. Chee, Chew-Seng & Seo, Byungtae, 2020. "Semiparametric estimation for linear regression with symmetric errors," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).

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