A new Maxwell-Log logistic distribution and its applications for mortality rate data
Issued Date
2025-05-01
Resource Type
ISSN
27142817
eISSN
27144704
Scopus ID
2-s2.0-85218867506
Journal Title
Journal of the Nigerian Society of Physical Sciences
Volume
7
Issue
2
Rights Holder(s)
SCOPUS
Bibliographic Citation
Journal of the Nigerian Society of Physical Sciences Vol.7 No.2 (2025)
Suggested Citation
Panitanarak U., Ishaq A.I., Abiodun A.A., Daud H., Suleiman A.A. A new Maxwell-Log logistic distribution and its applications for mortality rate data. Journal of the Nigerian Society of Physical Sciences Vol.7 No.2 (2025). doi:10.46481/jnsps.2025.1976 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/105553
Title
A new Maxwell-Log logistic distribution and its applications for mortality rate data
Author(s)
Corresponding Author(s)
Other Contributor(s)
Abstract
In this research, we extended the Log-Logistic distribution by incorporating it into the Maxwell generalized class, resulting in the Maxwell-Log Logistic (Max-LL) distribution. The probability density function and cumulative distribution function of the proposed distribution have been defined. The proposed distribution’s density shapes can be left or right-skewed and symmetric. The failure function of this distribution might be increasing, decreasing, or inverted bathtub forms. We discussed some essential properties of the Max-LL distribution, including moments, moment generating function, probability weighted moments, stress-strength, and order statistics. The efficiency of the model parameters has been evaluated through a simulation study utilizing a quantile function. To assess the proposed distribution’s adaptability, we applied it to two lifetime datasets: global COVID-19 mortality rates (for nations with more than 100,000 cases) and Canadian COVID-19 mortality rates. The Maxwell-Log Logistic distribution outperformed other distributions on both datasets, as evidenced by several accuracy measures. This shows that the proposed distribution is the best fit for COVID-19 mortality rate data in Canada and around the world.