{"title":"Discrete Odd Inverse Pareto Exponential Distribution: Properties, Estimation and Applications","authors":"Pornpop Saengthong, Palakorn Seenoi","doi":"10.60101/past.2023.250004","DOIUrl":null,"url":null,"abstract":"In this paper, a new discrete distribution named as the discrete odd inverse Pareto exponential (DOIPEx) distribution is introduced for modeling count data. The proposed distribution can be viewed as a generalization of the discrete Marshall-Olkin exponential, discrete exponentiate exponential, and discrete exponential distributions. Some basic distributional properties, quantile function, hazard and reversed hazard functions, and order statistics are derived. Estimation of the parameters is illustrated using the maximum likelihood method (MLE), and three real data sets are discussed to demonstrate the usefulness and applicability of the DOIPEx distribution.","PeriodicalId":500872,"journal":{"name":"Progress in Applied Science and Technology","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Progress in Applied Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.60101/past.2023.250004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a new discrete distribution named as the discrete odd inverse Pareto exponential (DOIPEx) distribution is introduced for modeling count data. The proposed distribution can be viewed as a generalization of the discrete Marshall-Olkin exponential, discrete exponentiate exponential, and discrete exponential distributions. Some basic distributional properties, quantile function, hazard and reversed hazard functions, and order statistics are derived. Estimation of the parameters is illustrated using the maximum likelihood method (MLE), and three real data sets are discussed to demonstrate the usefulness and applicability of the DOIPEx distribution.