Classical and Bayesian estimation for the truncated inverse power Ailamujia distribution with applications

Autor: Ahmed Mohamed El Gazar, Mohammed ElGarhy, Beih S. El-Desouky
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: AIP Advances, Vol 13, Iss 12, Pp 125122-125122-19 (2023)
Druh dokumentu: article
ISSN: 2158-3226
DOI: 10.1063/5.0174794
Popis: In this study, we suggest the truncated version of the inverse power Ailamujia distribution, which is more flexible than other well-known distributions. Statistical properties of the new distribution are considered, such as moments, moment generating function, incomplete moments, quantile function, order statistics, and entropy. We discuss various methods of estimation, such as the method of maximum likelihood, methods of least squares and weighted least squares, the method of the maximum product of spacings, the method of Cramer and Von-Mises, methods of Anderson and Darling and right-tail Anderson and Darling, the method of percentiles, and the Bayesian method. Simulation is implemented to study the performance of estimates. We introduce two real data applications, showing that the new distribution can provide better fits than some other corresponding distributions.
Databáze: Directory of Open Access Journals