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Minimum Hellinger distance estimation for finite mixtures of Poisson regression models and its applications.

作者信息

Lu Zudi, Hui Yer Van, Lee Andy H

机构信息

Institute of Systems Science, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing, China.

出版信息

Biometrics. 2003 Dec;59(4):1016-26. doi: 10.1111/j.0006-341x.2003.00117.x.

DOI:10.1111/j.0006-341x.2003.00117.x
PMID:14969481
Abstract

Minimum Hellinger distance estimation (MHDE) has been shown to discount anomalous data points in a smooth manner with first-order efficiency for a correctly specified model. An estimation approach is proposed for finite mixtures of Poisson regression models based on MHDE. Evidence from Monte Carlo simulations suggests that MHDE is a viable alternative to the maximum likelihood estimator when the mixture components are not well separated or the model parameters are near zero. Biometrical applications also illustrate the practical usefulness of the MHDE method.

摘要

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