The Odd Log-Logistic Transmuted-G Family of Distributions: Properties, Characterization, Applications and Different Methods of Estimation

Autor:	Morad Alizadeh, Mahdi Rasekhi, Haitham M. Yousof, G.G. Hamedani, Alireza Ataei
Rok vydání:	2022
Předmět:	Statistics and Probability Control and Optimization Artificial Intelligence Signal Processing Computer Vision and Pattern Recognition Statistics Probability and Uncertainty Information Systems
Zdroj:	Statistics, Optimization & Information Computing. 10:904-924
ISSN:	2310-5070 2311-004X
Popis:	In this work, we propose a new class of lifetime distributions called the odd log-logistic transmuted-G family. The proposed family of distributions is constructed by compounding the odd log-logistic distribution with the transmuted distribution. It can provide better fits than some of the known lifetime models and this fact represents a good characterization of this new family. Some characterizations for the new family are presented as well as some of its mathematical properties including. The maximum likelihood, Least squares and weighted least squares, Cram\'{e}r--von--Mises, Anderson-Darling and right-tailed Anderson-Darlingare and maximum product of spacings methods are used for estimating the model parameters. The importance and flexibility of the new family are illustrated by means of an application to a real data set.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a09869b7c88b5f4550ce9d2a787e08f0 https://doi.org/10.19139/soic-2310-5070-1182 Zobrazit plný text záznamu