{"title":"具有统计性质的Lomax分布的新扩展及其在故障和服务时间数据集上的应用","authors":"Mohamed K. A. Refaie","doi":"10.3844/JMSSP.2019.1.11","DOIUrl":null,"url":null,"abstract":"In this work, we introduce and study a new alternative Lomax model. The maximum likelihood method is used to estimate the unknown model parameters. We show empirically the importance and wide flexibility of the new model in modeling two types of failure times data sets. The new model is much better than the gamma Lomax, exponentiated Lomax, beta Lomax and Lomax models so the new model is a good alternative to these models.","PeriodicalId":41981,"journal":{"name":"Jordan Journal of Mathematics and Statistics","volume":"16 1","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A New Extension of the Lomax Distribution with Statistical Properties and Applications to Failure and Service Times Data Sets\",\"authors\":\"Mohamed K. A. Refaie\",\"doi\":\"10.3844/JMSSP.2019.1.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, we introduce and study a new alternative Lomax model. The maximum likelihood method is used to estimate the unknown model parameters. We show empirically the importance and wide flexibility of the new model in modeling two types of failure times data sets. The new model is much better than the gamma Lomax, exponentiated Lomax, beta Lomax and Lomax models so the new model is a good alternative to these models.\",\"PeriodicalId\":41981,\"journal\":{\"name\":\"Jordan Journal of Mathematics and Statistics\",\"volume\":\"16 1\",\"pages\":\"\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Jordan Journal of Mathematics and Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3844/JMSSP.2019.1.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"MATHEMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jordan Journal of Mathematics and Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3844/JMSSP.2019.1.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS","Score":null,"Total":0}
A New Extension of the Lomax Distribution with Statistical Properties and Applications to Failure and Service Times Data Sets
In this work, we introduce and study a new alternative Lomax model. The maximum likelihood method is used to estimate the unknown model parameters. We show empirically the importance and wide flexibility of the new model in modeling two types of failure times data sets. The new model is much better than the gamma Lomax, exponentiated Lomax, beta Lomax and Lomax models so the new model is a good alternative to these models.
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