Data from Taif University Broaden Understanding of Mathematics (The Extended Log-Logistic Distribution: Inference and Actuarial Applications)

Math Daily News

2021 JUL 21 (NewsRx) -- By a News Reporter-Staff News Editor at Math Daily News -- Investigators publish new report on mathematics. According to news reporting originating from Taif University by NewsRx correspondents, research stated, “Actuaries are interested in modeling actuarial data using loss models that can be adopted to describe risk exposure.”

The news reporters obtained a quote from the research from Taif University: “This paper introduces a new flexible extension of the log-logistic distribution, called the extended log-logistic (Ex-LL) distribution, to model heavy-tailed insurance losses data. The Ex-LL hazard function exhibits an upside-down bathtub shape, an increasing shape, a J shape, a decreasing shape, and a reversed-J shape. We derived five important risk measures based on the Ex-LL distribution. The Ex-LL parameters were estimated using different estimation methods, and their performances were assessed using simulation results. Finally, the performance of the Ex-LL distribution was explored using two types of real data from the engineering and insurance sciences.”

According to the news editors, the research concluded: “The analyzed data illustrated that the Ex-LL distribution provided an adequate fit compared to other competing distributions such as the log-logistic, alpha-power log-logistic, transmuted log-logistic, generalized log-logistic, Marshall-Olkin log-logistic, inverse log-logistic, and Weibull generalized log-logistic distributions.”

For more information on this research see: The Extended Log-Logistic Distribution: Inference and Actuarial Applications. Mathematics, 2021,9(1386):1386. (Mathematics - http://www.mdpi.com/journal/mathematics). The publisher for Mathematics is MDPI AG.

A free version of this journal article is available at https://doi.org/10.3390/math9121386.

Our news journalists report that more information may be obtained by contacting Nada M. Alfaer, Department of Mathematics and Statistics, College of Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia. Additional authors for this research include Ahmed M. Gemeay, Hassan M. Aljohani, Ahmed Z. Afify.