TY  - JOUR
T1  - The Weighted Flexible Weibull Model
T2  - Properties, Applications, and Analysis for Extreme Events
AU  - Ramaki, Ziaurrahman
AU  - Alizadeh, Morad
AU  - Tahmasebi, Saeid
AU  - Afshari, Mahmoud
AU  - Contreras-Reyes, Javier E.
AU  - Yousof, Haitham M.
N1  - Publisher Copyright:
© 2025 by the authors.
PY  - 2025/4
Y1  - 2025/4
N2  - The weighted flexible Weibull distribution focuses on its unique point of flaunting a bathtub-shaped hazard rate, characterized by an initial increase followed by a drop over time. This property plays a major role in reliability analysis. In this paper, this distribution and its main properties are examined, and the parameters are estimated using several estimation methods. In addition, a simulation study is done for different sample sizes. The performance of the proposed model is illustrated through two real-world applications: component failure times and COVID-19 mortality. Moreover, the value-at-risk (VaR), tail value-at-risk (TVaR), peaks over a random threshold VaR (PORT-VaR), the mean of order P ((Formula presented.)) analysis, and optimal order of P due to the true mean value can help identify and characterize critical events or outliers in failure events and COVID-19 death data across different counties. Finally, the PORT-VaR estimators are provided under a risk analysis for both applications.
AB  - The weighted flexible Weibull distribution focuses on its unique point of flaunting a bathtub-shaped hazard rate, characterized by an initial increase followed by a drop over time. This property plays a major role in reliability analysis. In this paper, this distribution and its main properties are examined, and the parameters are estimated using several estimation methods. In addition, a simulation study is done for different sample sizes. The performance of the proposed model is illustrated through two real-world applications: component failure times and COVID-19 mortality. Moreover, the value-at-risk (VaR), tail value-at-risk (TVaR), peaks over a random threshold VaR (PORT-VaR), the mean of order P ((Formula presented.)) analysis, and optimal order of P due to the true mean value can help identify and characterize critical events or outliers in failure events and COVID-19 death data across different counties. Finally, the PORT-VaR estimators are provided under a risk analysis for both applications.
KW  - COVID-19
KW  - flexible Weibull
KW  - mean of order P
KW  - peaks over a random threshold for value-at-risk estimation
KW  - risk analysis
KW  - true mean value
UR  - http://www.scopus.com/inward/record.url?scp=105003693959&partnerID=8YFLogxK
U2  - 10.3390/mca30020042
DO  - 10.3390/mca30020042
M3  - Article
AN  - SCOPUS:105003693959
SN  - 1300-686X
VL  - 30
JO  - Mathematical and Computational Applications
JF  - Mathematical and Computational Applications
IS  - 2
M1  - 42
ER  -