{"title":"用标准贝叶斯法和分层贝叶斯法估算具有第二类观测数据的反洛马克斯分布的可靠性函数的比较","authors":"Aklaa Jasim, Wafa Jafaar","doi":"10.29124/kjeas.1650.16","DOIUrl":null,"url":null,"abstract":"In this paper, the shape and size parameters (without imposing either parameter) and the survival function of the inverse Lomax distribution in the presence of observational data of the second type are estimated using different Bayesian methods, which included the standard Bayesian method and the hierarchical Bayesian method under a symmetric loss function, which is the quadratic loss function, and in order to compare The two methods used Monte Carlo simulation, where different sample sizes and three models of default values for distribution parameters (Ѳ,λ) , were used and the statistical measure, mean integral square error (IMSE), was used. Simulation experiments showed the superiority of the hierarchical Bayesian method because it has the least mean square integral error (IMSE)","PeriodicalId":181022,"journal":{"name":"Al Kut Journal of Economics and Administrative Sciences","volume":"48 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison between the standard Bayesian method and the hierarchical Bayesian method for estimating the reliability function of the inverse Lomax distribution with type II observational dat\",\"authors\":\"Aklaa Jasim, Wafa Jafaar\",\"doi\":\"10.29124/kjeas.1650.16\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the shape and size parameters (without imposing either parameter) and the survival function of the inverse Lomax distribution in the presence of observational data of the second type are estimated using different Bayesian methods, which included the standard Bayesian method and the hierarchical Bayesian method under a symmetric loss function, which is the quadratic loss function, and in order to compare The two methods used Monte Carlo simulation, where different sample sizes and three models of default values for distribution parameters (Ѳ,λ) , were used and the statistical measure, mean integral square error (IMSE), was used. Simulation experiments showed the superiority of the hierarchical Bayesian method because it has the least mean square integral error (IMSE)\",\"PeriodicalId\":181022,\"journal\":{\"name\":\"Al Kut Journal of Economics and Administrative Sciences\",\"volume\":\"48 3\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Al Kut Journal of Economics and Administrative Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29124/kjeas.1650.16\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Al Kut Journal of Economics and Administrative Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29124/kjeas.1650.16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison between the standard Bayesian method and the hierarchical Bayesian method for estimating the reliability function of the inverse Lomax distribution with type II observational dat
In this paper, the shape and size parameters (without imposing either parameter) and the survival function of the inverse Lomax distribution in the presence of observational data of the second type are estimated using different Bayesian methods, which included the standard Bayesian method and the hierarchical Bayesian method under a symmetric loss function, which is the quadratic loss function, and in order to compare The two methods used Monte Carlo simulation, where different sample sizes and three models of default values for distribution parameters (Ѳ,λ) , were used and the statistical measure, mean integral square error (IMSE), was used. Simulation experiments showed the superiority of the hierarchical Bayesian method because it has the least mean square integral error (IMSE)