{"title":"双变量分布的Cambanis族:性质和应用","authors":"N. Nair, Johny Scaria, Sithara Mohan.","doi":"10.6092/ISSN.1973-2201/6159","DOIUrl":null,"url":null,"abstract":"The Cambanis family of bivariate distributions was introduced as a generalization of the Farlie-Gumbel-Morgenstern system. The present work is an attempt to investigate the distributional characteristics and applications of the family. We derive various coecients of association, dependence concepts and time-dependent measures. Bivariate reliability functions such as hazard rates and mean residual life functions are analysed. The application of the family as a model for bivariate lifetime data is also demonstrated.","PeriodicalId":45117,"journal":{"name":"Statistica","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2016-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"The Cambanis family of bivariate distributions: Properties and applications\",\"authors\":\"N. Nair, Johny Scaria, Sithara Mohan.\",\"doi\":\"10.6092/ISSN.1973-2201/6159\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Cambanis family of bivariate distributions was introduced as a generalization of the Farlie-Gumbel-Morgenstern system. The present work is an attempt to investigate the distributional characteristics and applications of the family. We derive various coecients of association, dependence concepts and time-dependent measures. Bivariate reliability functions such as hazard rates and mean residual life functions are analysed. The application of the family as a model for bivariate lifetime data is also demonstrated.\",\"PeriodicalId\":45117,\"journal\":{\"name\":\"Statistica\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2016-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.6092/ISSN.1973-2201/6159\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.6092/ISSN.1973-2201/6159","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
The Cambanis family of bivariate distributions: Properties and applications
The Cambanis family of bivariate distributions was introduced as a generalization of the Farlie-Gumbel-Morgenstern system. The present work is an attempt to investigate the distributional characteristics and applications of the family. We derive various coecients of association, dependence concepts and time-dependent measures. Bivariate reliability functions such as hazard rates and mean residual life functions are analysed. The application of the family as a model for bivariate lifetime data is also demonstrated.
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