{"title":"Marshall–Olkin Power Generalized Weibull Distribution with Applications in Engineering and Medicine","authors":"A. Afify, D. Kumar, I. Elbatal","doi":"10.2991/jsta.d.200507.004","DOIUrl":null,"url":null,"abstract":"This paper proposes a new flexible four-parameter model called Marshall – Olkin power generalized Weibull (MOPGW) distribution which provides symmetrical, reversed-J shaped, left-skewed and right-skewed densities, and bathtub, unimodal, increas-ing,constant,decreasing,Jshaped,andreversed-Jshapedhazardrates.SomeoftheMOPGWstructuralpropertiesarediscussed.ThemaximumlikelihoodisutilizedtoestimatetheMOPGWunknownparameters.Simulationresultsareprovidedtoassesstheperformanceofthemaximumlikelihoodmethod.Finally,weillustratetheimportanceoftheMOPGWmodel,comparedwithsomerivalmodels,viatworealdataapplicationsfromtheengineeringandmedicinefields.","PeriodicalId":45080,"journal":{"name":"Journal of Statistical Theory and Applications","volume":"33 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistical Theory and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2991/jsta.d.200507.004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 12
Abstract
This paper proposes a new flexible four-parameter model called Marshall – Olkin power generalized Weibull (MOPGW) distribution which provides symmetrical, reversed-J shaped, left-skewed and right-skewed densities, and bathtub, unimodal, increas-ing,constant,decreasing,Jshaped,andreversed-Jshapedhazardrates.SomeoftheMOPGWstructuralpropertiesarediscussed.ThemaximumlikelihoodisutilizedtoestimatetheMOPGWunknownparameters.Simulationresultsareprovidedtoassesstheperformanceofthemaximumlikelihoodmethod.Finally,weillustratetheimportanceoftheMOPGWmodel,comparedwithsomerivalmodels,viatworealdataapplicationsfromtheengineeringandmedicinefields.
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