{"title":"广义伽玛分布的位置尺度混合:估计和病例影响诊断","authors":"Z. Rahnamaei","doi":"10.18869/acadpub.jsri.12.2.163","DOIUrl":null,"url":null,"abstract":"One of the most interesting problems in distribution theory is constructing the distributions, which are appropriate for fitting skewed and heavy-tailed data sets. In this paper, we introduce a skew-slash distribution by using the scale mixture of the generalized gamma distribution. Some properties of this distribution are obtained. An EM-type algorithm is presented to estimate the parameters. Finally, we provide a simulation study and an application to real data to illustrate the modeling strength of the proposed distribution.","PeriodicalId":422124,"journal":{"name":"Journal of Statistical Research of Iran","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Location-Scale Mixture of Generalized Gamma Distribution: Estimation and Case Influence Diagnostics\",\"authors\":\"Z. Rahnamaei\",\"doi\":\"10.18869/acadpub.jsri.12.2.163\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the most interesting problems in distribution theory is constructing the distributions, which are appropriate for fitting skewed and heavy-tailed data sets. In this paper, we introduce a skew-slash distribution by using the scale mixture of the generalized gamma distribution. Some properties of this distribution are obtained. An EM-type algorithm is presented to estimate the parameters. Finally, we provide a simulation study and an application to real data to illustrate the modeling strength of the proposed distribution.\",\"PeriodicalId\":422124,\"journal\":{\"name\":\"Journal of Statistical Research of Iran\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Statistical Research of Iran\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18869/acadpub.jsri.12.2.163\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Statistical Research of Iran","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18869/acadpub.jsri.12.2.163","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Location-Scale Mixture of Generalized Gamma Distribution: Estimation and Case Influence Diagnostics
One of the most interesting problems in distribution theory is constructing the distributions, which are appropriate for fitting skewed and heavy-tailed data sets. In this paper, we introduce a skew-slash distribution by using the scale mixture of the generalized gamma distribution. Some properties of this distribution are obtained. An EM-type algorithm is presented to estimate the parameters. Finally, we provide a simulation study and an application to real data to illustrate the modeling strength of the proposed distribution.