상세 보기
The Behrens-Fisher problem revisited: a Bayes-frequentist synthesis
- Ghosh, M.;
- Kim, Yeong-Hwa
Citations
WEB OF SCIENCE
27Citations
SCOPUS
24초록
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
- 권
- 29
- 호
- 1
- 페이지
- 5 ~ 17
- 언어
- ENG
- 출판사
- CANADIAN JOURNAL STATISTICS
- 발행국가
- 캐나다
- 분량
- 13 페이지
- ISSN
- E 1708-945X
P 0319-5724