LOCAL ANCILLARITY
成果类型：
Article
署名作者：
COX, DR
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
发表日期：
1980
页码：
279286
关键词：
摘要：
Non-Bayesian inference is considered for a scalar unknown parameter. When the minimal sufficient statistic is of dimension > 1 and no suitable exactly ancillary statistic is available, a statistic with a certain property of local ancillarity is calculated and the conditional distribution given that statistic is evaluated by Edgeworth expansion. The resulting distribution is used to calculate significance tests and confidence intervals which have desired probability levels to O(1/n), where n is the sample size, and which are appropriately conditional. The resulting confidence intervals are simply related to likelihood inference in the parameterization in which Fisher''s information is constant, thus generalizing Fisher''s (1934) result for location parameters.