{"title":"不精确先验分布的贝叶斯模糊假设检验","authors":"G. Hesamian","doi":"10.18869/ACADPUB.JIRSS.15.2.105","DOIUrl":null,"url":null,"abstract":"This paper considers the classical (normal) Bayesian method for testing fuzzy hypotheses. For this purpose, using a notion of prior distribution with interval-valued or fuzzy-valued parameters, a concept of posterior probability of a fuzzy hypothesis is proposed and its main properties are also verified. The feasibility and effectiveness of the proposed methods are also clarified by some numerical examples.","PeriodicalId":42965,"journal":{"name":"JIRSS-Journal of the Iranian Statistical Society","volume":"15 1","pages":"105-119"},"PeriodicalIF":0.1000,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Bayesian Fuzzy Hypothesis Testing with Imprecise Prior Distribution\",\"authors\":\"G. Hesamian\",\"doi\":\"10.18869/ACADPUB.JIRSS.15.2.105\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper considers the classical (normal) Bayesian method for testing fuzzy hypotheses. For this purpose, using a notion of prior distribution with interval-valued or fuzzy-valued parameters, a concept of posterior probability of a fuzzy hypothesis is proposed and its main properties are also verified. The feasibility and effectiveness of the proposed methods are also clarified by some numerical examples.\",\"PeriodicalId\":42965,\"journal\":{\"name\":\"JIRSS-Journal of the Iranian Statistical Society\",\"volume\":\"15 1\",\"pages\":\"105-119\"},\"PeriodicalIF\":0.1000,\"publicationDate\":\"2016-08-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JIRSS-Journal of the Iranian Statistical Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.18869/ACADPUB.JIRSS.15.2.105\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JIRSS-Journal of the Iranian Statistical Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18869/ACADPUB.JIRSS.15.2.105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
Bayesian Fuzzy Hypothesis Testing with Imprecise Prior Distribution
This paper considers the classical (normal) Bayesian method for testing fuzzy hypotheses. For this purpose, using a notion of prior distribution with interval-valued or fuzzy-valued parameters, a concept of posterior probability of a fuzzy hypothesis is proposed and its main properties are also verified. The feasibility and effectiveness of the proposed methods are also clarified by some numerical examples.
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