ROBUST ESTIMATION FOR SEMIPARAMETRIC EXPONENTIAL MIXTURE-MODELS

被引:0
|
作者
SHEN, LZQ [1 ]
机构
[1] PROCTER & GAMBLE CO,BIOMETR & STAT SCI,CINCINNATI,OH 45242
关键词
B-OPTIMAL; BOUNDED INFLUENCE FUNCTION; EXPONENTIAL MIXTURE MODEL; HAMPELS PROBLEM; MOST ROBUST ESTIMATE;
D O I
暂无
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
B-optimal robust estimates are considered for semiparametric exponential mixture models, under the perception that the data may have been contaminated. The B-optimal robust influence functions are defined by Hampel's variational problem: minimizing the asymptotic variances over the class of influence functions bounded by a constant. Explicit B-optimal influence functions are calculated for the semiparametric exponential mixture models. The one-step procedure is used to construct the B-optimal robust estimates from the B-optimal influence functions. A small Monte-Carlo study is conducted for the semiparametric two-sample exponential mixture model to confirm the theory.
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页码:333 / 349
页数:17
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