Regularized empirical likelihood estimators in mixture models with unknown symmetric components

来源 :泛华统计学会(icsa)2015年学术会议 | 被引量 : 0次 | 上传用户：kyl1n

【摘要】

：

Modeling heterogeneity for multivariate data is an important research topic.In this paper,we give a sufficient condition to establish the identifiability for se

【作者】

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Xueqin Wang

【机构】

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DepartmentofStatistics,SunYat-senUniversity,Guangzhou,China

【出处】

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泛华统计学会(icsa)2015年学术会议

【发表日期】

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2015年7期

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Modeling heterogeneity for multivariate data is an important research topic.In this paper,we give a sufficient condition to establish the identifiability for semiparametric multivariate mixture models with unknown location-shifted symmetric components,and propose a novel minimum distance method to estimate the location and proportion parameters.

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Regularized empirical likelihood estimators in mixture models with unknown symmetric components

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