{"title":"指数分布的一个新版本:Copula,性质及其在救援和生存时代的应用","authors":"Hanaa Elgohari","doi":"10.19139/SOIC-2310-5070-1093","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce a new generalization of the Exponentiated Exponential distribution. Various structural mathematical properties are derived. Numerical analysis for mean, variance, skewness and kurtosis and the dispersion index is performed. The new density can be right skewed and symmetric with “unimodal” and “bimodal” shapes. The new hazard function can be “constant”, “decreasing”, “increasing”, “increasing-constant”, “upsidedown-constant”, “decreasingconstant”. Many bivariate and multivariate type model have been also derived. We assess the performance of the maximum likelihood method graphically via the biases and mean squared errors. The usefulness and flexibility of the new distribution is illustrated by means of two real data sets.","PeriodicalId":93376,"journal":{"name":"Statistics, optimization & information computing","volume":"9 1","pages":"311-333"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A New Version of the Exponentiated Exponential Distribution: Copula, Properties and Application to Relief and Survival Times\",\"authors\":\"Hanaa Elgohari\",\"doi\":\"10.19139/SOIC-2310-5070-1093\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduce a new generalization of the Exponentiated Exponential distribution. Various structural mathematical properties are derived. Numerical analysis for mean, variance, skewness and kurtosis and the dispersion index is performed. The new density can be right skewed and symmetric with “unimodal” and “bimodal” shapes. The new hazard function can be “constant”, “decreasing”, “increasing”, “increasing-constant”, “upsidedown-constant”, “decreasingconstant”. Many bivariate and multivariate type model have been also derived. We assess the performance of the maximum likelihood method graphically via the biases and mean squared errors. The usefulness and flexibility of the new distribution is illustrated by means of two real data sets.\",\"PeriodicalId\":93376,\"journal\":{\"name\":\"Statistics, optimization & information computing\",\"volume\":\"9 1\",\"pages\":\"311-333\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Statistics, optimization & information computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.19139/SOIC-2310-5070-1093\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Statistics, optimization & information computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.19139/SOIC-2310-5070-1093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A New Version of the Exponentiated Exponential Distribution: Copula, Properties and Application to Relief and Survival Times
In this paper, we introduce a new generalization of the Exponentiated Exponential distribution. Various structural mathematical properties are derived. Numerical analysis for mean, variance, skewness and kurtosis and the dispersion index is performed. The new density can be right skewed and symmetric with “unimodal” and “bimodal” shapes. The new hazard function can be “constant”, “decreasing”, “increasing”, “increasing-constant”, “upsidedown-constant”, “decreasingconstant”. Many bivariate and multivariate type model have been also derived. We assess the performance of the maximum likelihood method graphically via the biases and mean squared errors. The usefulness and flexibility of the new distribution is illustrated by means of two real data sets.