An Alternative to the Marshall-Olkin Family of Distributions:Bootstrap,Regression and Applications

作     者：Christophe Chesneau Kadir Karakaya Hassan S.Bakouch Coskun Kus Christophe Chesneau;Kadir Karakaya;Hassan S.Bakouch;Co?kun Ku?

作者机构：LMNOUniversité de CaenCampus ⅡScience 314032 CaenFrance Department of StatisticsFaculty of ScienceSelcuk University42250 KonyaTurkey Department of MathematicsFaculty of ScienceTanta UniversityTantaEgypt 

出 版 物：《Communications on Applied Mathematics and Computation》 (应用数学与计算数学学报（英文）)

年 卷 期：2022年第4卷第4期

页      面：1229-1257页

核心收录：

学科分类：07[理学] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 070101[理学-基础数学] 

基　　金：We would like to express our gratitude to the reviewers for their time and work in helping us to improve our manuscript 

主　　题：Marshall-Olkin family of distributions Estimation Confidence intervals Bootstrap Data analysis 

摘      要：This paper introduces a new rich family of distributions based on mixtures and the so-called Marshall-Olkin family of *** includes a wide variety of well-established mixture distributions,ensuring a high ability for data *** distributional properties are derived for the general *** Weibull distribution is then considered as the base-line,exhibiting a pliant four-parameter lifetime *** estimation methods for the related parameters are *** confidence intervals are also considered for these *** distribution is reparametrized with location-scale parameters and it is used for a lifetime regression *** extensive simulation is carried out on the esti-mation methods for distribution parameters and regression model *** are given to two practical data sets to illustrate the applicability of the new family.