TY - JOUR
T1 - Power unit Burr-XII distribution
T2 - Statistical inference with applications
AU - Yıldırım, Elif
AU - Ilıkkan, Eda Selin
AU - Gemeay, Ahmed M.
AU - Makumi, Nicholas
AU - Bakr, M. E.
AU - Balogun, Oluwafemi Samson
N1 - Publisher Copyright:
© 2023 Author(s).
PY - 2023/10/1
Y1 - 2023/10/1
N2 - This article introduces a new statistical distribution called the power unit Burr-XII distribution, which is an extension of the Burr XII distribution obtained through a power transform. This paper investigates several statistical properties of this new model, including mode, moments, moment generating and characteristic functions, entropy, and Bonferroni and Lorenz curves. In addition, various classical estimators for the parameters of the power unit Burr-XII distribution are evaluated, including maximum likelihood estimates, ordinary least squares estimates, maximum product of interval estimates, Anderson-Darling, right and left tail Anderson-Darling, and Cramer-von Mises estimators. This study provides tables and graphs to illustrate the performance of these methods under different scenarios and sample sizes. The results of the proposed distribution in different fields of application are shown using the mortality rates of COVID-19 patients in Spain and flood data from 20 observations. As a result of both applications, it was observed that the proposed distribution gave better results compared to other well-known distributions, such as the beta distribution, transformed gamma distribution, log-weighted power distribution, transmuted power distribution, Kumaraswamy distribution, Topp-Leone distribution, exponentiated reduce Kies distribution, and exponentiated Topp-Leone distribution.
AB - This article introduces a new statistical distribution called the power unit Burr-XII distribution, which is an extension of the Burr XII distribution obtained through a power transform. This paper investigates several statistical properties of this new model, including mode, moments, moment generating and characteristic functions, entropy, and Bonferroni and Lorenz curves. In addition, various classical estimators for the parameters of the power unit Burr-XII distribution are evaluated, including maximum likelihood estimates, ordinary least squares estimates, maximum product of interval estimates, Anderson-Darling, right and left tail Anderson-Darling, and Cramer-von Mises estimators. This study provides tables and graphs to illustrate the performance of these methods under different scenarios and sample sizes. The results of the proposed distribution in different fields of application are shown using the mortality rates of COVID-19 patients in Spain and flood data from 20 observations. As a result of both applications, it was observed that the proposed distribution gave better results compared to other well-known distributions, such as the beta distribution, transformed gamma distribution, log-weighted power distribution, transmuted power distribution, Kumaraswamy distribution, Topp-Leone distribution, exponentiated reduce Kies distribution, and exponentiated Topp-Leone distribution.
UR - http://www.scopus.com/inward/record.url?scp=85174302130&partnerID=8YFLogxK
U2 - 10.1063/5.0171077
DO - 10.1063/5.0171077
M3 - Article
AN - SCOPUS:85174302130
SN - 2158-3226
VL - 13
JO - AIP Advances
JF - AIP Advances
IS - 10
M1 - 105107
ER -