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Inference for an exponentiated Pareto record values based on the pivotal quantity
Journal of the Korean Data & Information Science Society 2019;30:885-93
Published online July 31, 2019;  https://doi.org/10.7465/jkdi.2019.30.4.885
© 2019 Korean Data and Information Science Society.

Jung-In Seo1

1Department of Big Data, Daejeon University
Correspondence to: Assistant professor, Department of Big Data, Daejeon University, Daejeon 34520, Korea. E-mail: leehoo1928@gmail.com

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (Ministry of Science, ICT & Future Planning) (No. NRF-2017R1C1B1006792).
Received May 10, 2019; Revised June 9, 2019; Accepted June 14, 2019.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This article provides estimation methods based on the pivotal quantity to construct exact confidence intervals with the equal-tails and shortest-length for unknown parameters of an exponentiated Pareto distribution based on lower record values and extends the method to prediction for the future lower record values, which not only entails no computational complexity like the maximum likelihood method, but also leads to valid confidence intervals even if the sample size is not large enough. The provided method is evaluated through Monte Carlo simulations and a real data set is analyzed for illustrative purposes.
Keywords : Exponentiated Pareto distribution, lower record value, pivotal quantity, prediction.