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Introducing nonparametric predictive inference methods for reproducibility of likelihood ratio tests.

Marques, F.J. and Coolen, F.P.A. and Coolen-Maturi, T. (2019) 'Introducing nonparametric predictive inference methods for reproducibility of likelihood ratio tests.', Journal of statistical theory and practice., 13 . p. 15.

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.

Item Type:Article
Full text:Publisher-imposed embargo until 31 October 2019.
(AM) Accepted Manuscript
First Live Deposit - 16 October 2018
File format - PDF
(344Kb)
Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1007/s42519-018-0020-9
Publisher statement:This is a post-peer-review, pre-copyedit version of an article published in Journal of statistical theory and practice. The final authenticated version is available online at: https://doi.org/10.1007/s42519-018-0020-9
Record Created:16 Oct 2018 09:58
Last Modified:13 Feb 2019 10:42

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