{"title":"过分散计数数据林德利泊松分布的β变换","authors":"C. G. Louzayadio, M. K. Diafouka, R. O. Malouata","doi":"10.37418/amsj.12.3.3","DOIUrl":null,"url":null,"abstract":"A new distribution for over-dispersed count data is proposed, and its properties are studied. This is a two-parameter distribution which is obtained by introducing an additional parameter beta into the Poisson-Lindley distribution. The goodness-of-fit of this distribution is compared with other distributions that have been proposed to model overdispersion. Two illustrative examples are presented to show the flexibility of the model.","PeriodicalId":231117,"journal":{"name":"Advances in Mathematics: Scientific Journal","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"BETA TRANSFORMATION OF THE LINDLEY POISSON DISTRIBUTION FOR OVER-DISPERSED COUNT DATA\",\"authors\":\"C. G. Louzayadio, M. K. Diafouka, R. O. Malouata\",\"doi\":\"10.37418/amsj.12.3.3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new distribution for over-dispersed count data is proposed, and its properties are studied. This is a two-parameter distribution which is obtained by introducing an additional parameter beta into the Poisson-Lindley distribution. The goodness-of-fit of this distribution is compared with other distributions that have been proposed to model overdispersion. Two illustrative examples are presented to show the flexibility of the model.\",\"PeriodicalId\":231117,\"journal\":{\"name\":\"Advances in Mathematics: Scientific Journal\",\"volume\":\"16 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Mathematics: Scientific Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37418/amsj.12.3.3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Mathematics: Scientific Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37418/amsj.12.3.3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
BETA TRANSFORMATION OF THE LINDLEY POISSON DISTRIBUTION FOR OVER-DISPERSED COUNT DATA
A new distribution for over-dispersed count data is proposed, and its properties are studied. This is a two-parameter distribution which is obtained by introducing an additional parameter beta into the Poisson-Lindley distribution. The goodness-of-fit of this distribution is compared with other distributions that have been proposed to model overdispersion. Two illustrative examples are presented to show the flexibility of the model.
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