Bounds for robust maximum likelihood and posterior consistency in compound mixture state experiments

被引:4
|
作者
Majumdar, S
Gilliland, D
Hannan, J
机构
[1] Univ Connecticut, Dept Stat, Stamford, CT 06901 USA
[2] Michigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USA
关键词
asymptotic regret; compound; consistency; maximum likelihood; posterior;
D O I
10.1016/S0167-7152(98)00158-8
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
Uniform bounds on rates of L-1-consistency for the empiric mean of state sequences in a family of probability models (compound with finite-mixture-state component) are obtained for MLEs (Section 2) and posterior means for quasi-uniform hyperpriors (Section 3), both determined in the lid mixture (empirical Bayes) sub-models. Qualitative aspects of results of this type were described by Robbins (1951). Application to the Gilliland and Hannan (1974/86) restricted-risk-finite-state-component compound decision problem (Section 4) yields uniform bounds on rates of asymptotic regret of Bayes solutions therein (with extension to mixture-state by expectation), giving strong affirmation to an asymptotic form of a Robbins (1951) conjecture. The general extension to mixture-state components (Remark 4.1) strengthens much of the existing compound literature. (C) 1999 Published by Elsevier Science B.V. All rights reserved.
引用
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页码:215 / 227
页数:13
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