A Laplace Transform-Based Test for Exponentiality Against the EBUCL Class with Applications to Censored and Uncensored Data

Walid B. H. Etman, Mahmoud E. Bakr (), Arwa M. Alshangiti, Oluwafemi Samson Balogun and Rashad M. EL-Sagheer
Additional contact information
Walid B. H. Etman: Faculty of Computer and Artificial Intelligence, Modern University for Technology and Information, Cairo 11585, Egypt
Mahmoud E. Bakr: Department of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
Arwa M. Alshangiti: Department of Statistics and Operations Research, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
Oluwafemi Samson Balogun: Department of Computing, University of Eastern Finland, FI-70211, Finland
Rashad M. EL-Sagheer: Mathematics Department, Faculty of Science, Al-Azhar University, Naser City 11884, Cairo, Egypt

Mathematics, 2025, vol. 13, issue 21, 1-33

Abstract: This paper proposes a novel statistical test for evaluating exponentiality against the recently introduced EBUCL (Exponential Better than Used in Convex Laplace transform order) class of life distributions. The EBUCL class generalizes classical aging concepts and provides a flexible framework for modeling various non-exponential aging behaviors. The test is constructed using Laplace transform ordering and is shown to be effective in distinguishing exponential distributions from EBUCL alternatives. We derive the test statistic, establish its asymptotic properties, and assess its performance using Pitman’s asymptotic efficiency under standard alternatives, including Weibull, Makeham, and linear failure rate distributions. Critical values are obtained through extensive Monte Carlo simulations, and the power of the proposed test is evaluated and compared with existing methods. Furthermore, the test is extended to handle right-censored data, demonstrating its robustness and practical applicability. The effectiveness of the procedure is illustrated through several real-world datasets involving both censored and uncensored observations. The results confirm that the proposed test is a powerful and versatile tool for reliability and survival analysis.

Keywords: EBUCL class; exponentiality test; laplace transform order; life distributions; reliability analysis; Monte Carlo simulation; Pitman asymptotic efficiency; nonparametric testing; survival analysis; censored data (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/13/21/3379/pdf (application/pdf)
https://www.mdpi.com/2227-7390/13/21/3379/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:13:y:2025:i:21:p:3379-:d:1778135

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().