The Behrens-Fisher problem revisited: a Bayes-frequentist synthesis

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초록

The Behrens-Fisher problem concerns the inference for the difference between the means of two normal populations whose ratio of variances is unknown. In this situation, Fisher's fiducial interval differs markedly from the Neyman-Pearson confidence interval. A prior proposed by Jeffreys leads to a credible interval that is equivalent to Fisher's solution but it carries a different interpretation. The authors propose an alternative prior leading to a credible interval whose asymptotic coverage probability matches the frequentist coverage probability more accurately than the interval of Jeffreys. Their simulation results indicate excellent matching even in small samples.

키워드

Fisher's fiducial interval; Jeffreys independent prior; matching priors; parametric orthogonality; reference priors; NONINFORMATIVE PRIORS; BARTLETT CORRECTIONS; POSTERIOR QUANTILES; INFERENCE; VALIDITY; PARAMETER; DISTRIBUTIONS; INTERVALS; TESTS
제목
The Behrens-Fisher problem revisited: a Bayes-frequentist synthesis
저자
Ghosh, M.; Kim, Yeong-Hwa
DOI
10.2307/3316047
발행일
2001-03
유형
Article
저널명
Canadian Journal of Statistics
권
29
호
1
페이지
5 ~ 17