{"title":"Poisson Gompertz Distribution with Properties and Applications","authors":"A. Chaudhary, L. Sapkota, Vijay Kumar","doi":"10.37622/IJAER/16.1.2021.75-84","DOIUrl":null,"url":null,"abstract":"Here, a new distribution using the Poisson generating family with Gompertz distribution as baseline distribution have been generated called Poisson Gompertz (PGZ) distribution. Some distributional features of the PGZ distribution are presented. For the parameter estimates of the presented model, Maximum likelihood Estimation (MLE) is applied along with Cramer-Von-Mises estimation (CVME) and least-square estimation (LSE) methods. We have constructed the asymptotic confidence intervals based on maximum likelihood estimates. R software platform was used to perform the computations. The application of the proposed model has been illustrated by considering the data set obtained from real life and investigated the goodness of fit attained by the observed model via different test statistics and graphical methods. We have found that the distribution that is introduced provides better fit to the dataset taken with more flexibility as compared to other models in consideration","PeriodicalId":36710,"journal":{"name":"International Journal of Applied Engineering Research (Netherlands)","volume":"62 10 1","pages":"75-84"},"PeriodicalIF":0.0000,"publicationDate":"2021-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Applied Engineering Research (Netherlands)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37622/IJAER/16.1.2021.75-84","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 1
Abstract
Here, a new distribution using the Poisson generating family with Gompertz distribution as baseline distribution have been generated called Poisson Gompertz (PGZ) distribution. Some distributional features of the PGZ distribution are presented. For the parameter estimates of the presented model, Maximum likelihood Estimation (MLE) is applied along with Cramer-Von-Mises estimation (CVME) and least-square estimation (LSE) methods. We have constructed the asymptotic confidence intervals based on maximum likelihood estimates. R software platform was used to perform the computations. The application of the proposed model has been illustrated by considering the data set obtained from real life and investigated the goodness of fit attained by the observed model via different test statistics and graphical methods. We have found that the distribution that is introduced provides better fit to the dataset taken with more flexibility as compared to other models in consideration