November 16, 2024
Morad Alizadeh

Morad Alizadeh

Academic Rank: Assistant professor
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Degree: Ph.D in Statistics
Phone: 0
Faculty: Faculty of Intelligent Systems and Data Science

Research

Title The Odd Log-Logistic Transmuted-G family of distributions: Properties, Characterizations, Applications and Different Methods of Estimation
Type Article
Keywords
Odd log-logistic-G family; Transmuted-G family; Estimation; Characterization
Journal Statistics, Optimization and Information Computing
DOI 10.19139/soic-2310-5070-1182
Researchers Morad Alizadeh (First researcher) , Mahdi Rasekhi (Second researcher) , Haitham Yousof (Third researcher) , G.G Hamedani (Fourth researcher) , Alireza Ataei (Fifth researcher)

Abstract

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, Cramr–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.