GEE Estimators in Mixture Model with Varying Concentrations

Oleksii Doronin; Rostislav Maiboroda

doi:10.18778/0208-6018.314.03

Authors

Oleksii Doronin Taras Shevchenko National University of Kyiv
Rostislav Maiboroda Taras Shevchenko National University of Kyiv

DOI:

https://doi.org/10.18778/0208-6018.314.03

Keywords:

mixture model, semiparametric estimation, GEE

Abstract

We discuss semiparametric mixture model where some components are parametrized with common Euclidean parameter and others are fully unknown. We introduce GEE approach and adaptive GEE-based approach for parameter estimation. Proposed estimators are tested on simulated sample.

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Author Biographies

Oleksii Doronin, Taras Shevchenko National University of Kyiv

Faculty of Mechanics and Mathematics, Ph. D. student.
Rostislav Maiboroda, Taras Shevchenko National University of Kyiv

Faculty of Mechanics and Mathematics, Professor, Ph. D.

References

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Doronin O. (2014b), Adaptive estimation in semiparametric model of mixture with varying concentrations. "Theory of Probability and Mathematical Statistics", no. 91, p. 27−38.

Doronin O. (2012), Robust Estimates for Mixtures with Gaussian Component. "Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics & Mathematics" (in Ukrainian), vol. 1, p. 18-23.

Maiboroda R., Sugakova O. (2008), Estimation and classification by observations from mixtures. Kyiv University Publishers, Kyiv (in Ukrainian).

Maiboroda R., Kubaichuk O. (2005), Improved estimators for moments constructed from observations of a mixture. "Theory of Probability and Mathematical Statistics", no. 70, p. 83−92.

Maiboroda R., Sugakova O., Doronin A. (2013), Generalized estimating equations for mixtures with varying concentrations. "The Canadian Journal of Statistics", no. 41, vol. 2, p. 217−236.