{"title":"信息先验条件下用贝叶斯分析估计形状已知的Frechet分布","authors":"Wajiha Nasir","doi":"10.14419/ijsw.v5i2.8371","DOIUrl":null,"url":null,"abstract":"In this study, Frechet distribution has been studied by using Bayesian analysis. Posterior distribution has been derived by using gamma and exponential. Bayes estimators and their posterior risks has been derived using five different loss functions. Elicitation of hyperparameters has been done by using prior predictive distributions. Simulation study is carried out to study the behavior of posterior distribution. Quasi quadratic loss function and exponential prior are found better among all.","PeriodicalId":119953,"journal":{"name":"International Journal of Advances in Scientific Research","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On estimation of Frechet distribution with known shape using Bayesian analysis under informative priors\",\"authors\":\"Wajiha Nasir\",\"doi\":\"10.14419/ijsw.v5i2.8371\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, Frechet distribution has been studied by using Bayesian analysis. Posterior distribution has been derived by using gamma and exponential. Bayes estimators and their posterior risks has been derived using five different loss functions. Elicitation of hyperparameters has been done by using prior predictive distributions. Simulation study is carried out to study the behavior of posterior distribution. Quasi quadratic loss function and exponential prior are found better among all.\",\"PeriodicalId\":119953,\"journal\":{\"name\":\"International Journal of Advances in Scientific Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Advances in Scientific Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14419/ijsw.v5i2.8371\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Advances in Scientific Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14419/ijsw.v5i2.8371","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On estimation of Frechet distribution with known shape using Bayesian analysis under informative priors
In this study, Frechet distribution has been studied by using Bayesian analysis. Posterior distribution has been derived by using gamma and exponential. Bayes estimators and their posterior risks has been derived using five different loss functions. Elicitation of hyperparameters has been done by using prior predictive distributions. Simulation study is carried out to study the behavior of posterior distribution. Quasi quadratic loss function and exponential prior are found better among all.