Introducing nonparametric predictive inference methods for reproducibility of likelihood ratio tests

Marques, F.J.; Coolen, F.P.A.; Coolen-Maturi, T.

Abstract

This paper introduces the nonparametric predictive inference approach for reproducibility of likelihood ratio tests. The general idea of this approach is outlined for tests between two simple hypotheses, followed by an investigation of reproducibility for tests between two beta distributions. The paper reports on the first steps of a wider research programme towards tests involving composite hypotheses and substantial computational challenges.

Citation

Marques, F., Coolen, F., & Coolen-Maturi, T. (2019). Introducing nonparametric predictive inference methods for reproducibility of likelihood ratio tests. Journal of statistical theory and practice, 13, Article 15. https://doi.org/10.1007/s42519-018-0020-9

• Journal Article Type: Article
• Acceptance Date: Oct 13, 2018
• Online Publication Date: Oct 31, 2018
• Publication Date: Mar 31, 2019
• Deposit Date: Oct 15, 2018
• Publicly Available Date: Oct 31, 2019
• Journal: Journal of Statistical Theory and Practice
• Electronic ISSN: 1559-8616
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 13
• Article Number: 15
• DOI: https://doi.org/10.1007/s42519-018-0020-9
• Public URL: https://durham-repository.worktribe.com/output/1311706