Plausibility Functions and Exact Frequentist Inference

• 成果类型: Article
• 署名作者: Martin, Ryan
• 署名单位: University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2014.983232
• 发表日期: 2015
• 页码: 1552-1561
• 关键词: generalized fiducial-inference; likelihood ratio; confidence-intervals; correlation-coefficient; nuisance parameters; binomial proportion; profile likelihood; gamma-distribution; tests; asymptotics

摘要

In the frequentist program, inferential methods with exact control on error rates are a primary focus. The standard approach, however, is to rely on asymptotic approximations, which may not be suitable. This article presents a general framework for the construction of exact frequentist procedures based on plausibility functions. It is shown that the plausibility function-based tests and confidence regions have the desired frequentist properties in finite samples-no large-sample justification needed. An extension of the proposed method is also given for problems involving nuisance parameters. Examples demonstrate that the plausibility function-based method is both exact and efficient in a wide variety of problems.