A PARADOX IN DECISION-THEORETIC INTERVAL ESTIMATION

被引：0

作者：

CASELLA, G

HWANG, JTG

ROBERT, C

机构：

[1] UNIV PARIS 06,LSTA,F-75252 PARIS 05,FRANCE

[2] CORNELL UNIV,CTR STAT,ITHACA,NY 14853

来源：

STATISTICA SINICA | 1993年 / 3卷 / 01期

关键词：

CONFIDENCE SETS; DECISION THEORY; BAYES ESTIMATION; FOUNDATIONS;

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：

Decision-theoretic interval estimation usually employs a loss function that is a linear combination of volume and coverage probability. Such loss functions, however, may result iu paradoxical behavior of Bayes rules. We investigate this paradox in the case of Student's t, and suggest ways of avoiding it using a different loss function. Some properties of the resulting Bayes rules are also examined. This alternative approach may also be generalized.

引用

页码：141 / 155

页数：15

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