Asymptotic distribution and local power of the log-likelihood ratio test for mixtures:: bounded and unbounded cases

被引:20
作者
Azais, Jean-Marc
Gassiat, Elisabeth
Mercadier, Cecile
机构
[1] Univ Toulouse 3, Lab Stat & Probabil, UMR C55830, CNRS, F-31062 Toulouse 4, France
[2] Equipe Probabil Stat & Modelisat, Math Lab, F-91405 Orsay, France
关键词
contiguity; extreme values; local power; log-likelihood ratio test; mixture models; number of components;
D O I
10.3150/bj/1161614946
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
We consider the log-likelihood ratio test (LRT) for testing the number of components in a mixture of populations in a parametric family. We provide the asymptotic distribution of the LRT statistic under the null hypothesis as well as under contiguous alternatives when the parameter set is bounded. Moreover, for the simple contamination model we prove, under general assumptions, that the asymptotic local power under contiguous hypotheses may be arbitrarily close to the asymptotic level when the set of parameters is large enough. In the particular problem of normal distributions, we prove that, when the unknown mean is not a priori bounded, the asymptotic local power under contiguous hypotheses is equal to the asymptotic level.
引用
收藏
页码:775 / 799
页数:25
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