A new asymmetric extended family: Properties and estimation methods with actuarial applications.

Autor: Aljohani HM; Department of Mathematics & Statistics, College of Science, Taif University, Taif, Saudi Arabia., Bandar SA; Department of Mathematics, College of Education, Misan University, Amarah, Iraq., Al-Mofleh H; Department of Mathematics, Tafila Technical University, Tafila, Jordan., Ahmad Z; Department of Statistics, Yazd University, Yazd, Iran., El-Morshedy M; Department of Mathematics, College of Science and Humanities in Al-Kharj, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia.; Department of Statistics, Faculty of Science, Mansoura University, Mansoura, Egypt., Afify AZ; Department of Statistics, Mathematics and Insurance, Benha University, Benha, Egypt.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2022 Oct 06; Vol. 17 (10), pp. e0275001. Date of Electronic Publication: 2022 Oct 06 (Print Publication: 2022).
DOI: 10.1371/journal.pone.0275001
Abstrakt: In the present work, a class of distributions, called new extended family of heavy-tailed distributions is introduced. The special sub-models of the introduced family provide unimodal, bimodal, symmetric, and asymmetric density shapes. A special sub-model of the new family, called the new extended heavy-tailed Weibull (NEHTW) distribution, is studied in more detail. The NEHTW parameters have been estimated via eight classical estimation procedures. The performance of these methods have been explored using detailed simulation results which have been ordered, using partial and overall ranks, to determine the best estimation method. Two important risk measures are derived for the NEHTW distribution. To prove the usefulness of the two actuarial measures in financial sciences, a simulation study is conducted. Finally, the flexibility and importance of the NEHTW model are illustrated empirically using two real-life insurance data sets. Based on our study, we observe that the NEHTW distribution may be a good candidate for modeling financial and actuarial sciences data.
Competing Interests: The authors have declared that no competing interests exist.
Databáze: MEDLINE
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