Title: A new heavy-tailed generalised exponentiated half logistic-G distribution with actuarial measures and applications

Authors: Thatayaone Moakofi; Agolame Puoetsile; Broderick Oluyede

Addresses: Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Palapye, BW, Botswana ' Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Palapye, BW, Botswana ' Department of Mathematics and Statistical Sciences, Botswana International University of Science and Technology, Palapye, BW, Botswana

Abstract: This work introduces and investigates the new heavy-tailed generalised exponentiated half logistic-G (HT-GEN-EHL-G) family of distributions. The study involves the derivation and analysis of statistical properties associated with HT-GEN-EHL-G distribution. Employing the maximum likelihood estimation technique, we estimate model parameters and evaluate the consistency of these estimators through simulation studies. Additionally, we develop actuarial metrics (risk measures) tailored to this distribution. The practical utility of the HT-GEN-EHL-G family of distributions is demonstrated through the analysis of four real-life datasets from diverse fields. These applications emphasise the significance and versatility of the newly introduced HT-GEN-EHL-G family of distributions.

Keywords: heavy-tailed distribution; exponentiated half-logistic-G distribution; estimation; applicability.

DOI: 10.1504/IJMOR.2025.146356

International Journal of Mathematics in Operational Research, 2025 Vol.30 No.4, pp.501 - 538

Received: 20 Aug 2023
Accepted: 29 Aug 2023
Published online: 27 May 2025 *

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