{"title":"二项分布的极大极小估计","authors":"Zul . Amry, Sisti Nadia Amalia","doi":"10.54647/mathematics11340","DOIUrl":null,"url":null,"abstract":"This paper discusses the minimax estimator of parameter for binomial distribution. The likelihood function is constructed based on the probability function of the Binomial distribution. The posterior distribution is obtained from the joint of the likelihood function and prior distribution. Furthermore, the Bayes estimator is obtained based on the posterior mean and provide the constancy of the risk of Bayes the minimax estimator can be concluded.","PeriodicalId":380124,"journal":{"name":"SCIREA Journal of Mathematics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Minimax Estimator on Binomial Distribution\",\"authors\":\"Zul . Amry, Sisti Nadia Amalia\",\"doi\":\"10.54647/mathematics11340\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper discusses the minimax estimator of parameter for binomial distribution. The likelihood function is constructed based on the probability function of the Binomial distribution. The posterior distribution is obtained from the joint of the likelihood function and prior distribution. Furthermore, the Bayes estimator is obtained based on the posterior mean and provide the constancy of the risk of Bayes the minimax estimator can be concluded.\",\"PeriodicalId\":380124,\"journal\":{\"name\":\"SCIREA Journal of Mathematics\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-07-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SCIREA Journal of Mathematics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.54647/mathematics11340\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SCIREA Journal of Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54647/mathematics11340","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper discusses the minimax estimator of parameter for binomial distribution. The likelihood function is constructed based on the probability function of the Binomial distribution. The posterior distribution is obtained from the joint of the likelihood function and prior distribution. Furthermore, the Bayes estimator is obtained based on the posterior mean and provide the constancy of the risk of Bayes the minimax estimator can be concluded.
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