{"title":"随机序列定义的贝叶斯方法及其在统计推断中的应用","authors":"Hayato Takahashi","doi":"10.1109/ISIT.2006.261937","DOIUrl":null,"url":null,"abstract":"We introduce a universal Bayes test, which is a Bayesian version of Martin-Lof test. Then we define random sequences with respect to parametric models based on our universal Bayes test. We state some theorems related to Bayesian statistical inference in terms of random sequence","PeriodicalId":115298,"journal":{"name":"2006 IEEE International Symposium on Information Theory","volume":"21 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Bayesian approach to a definition of random sequences and its applications to statistical inference\",\"authors\":\"Hayato Takahashi\",\"doi\":\"10.1109/ISIT.2006.261937\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce a universal Bayes test, which is a Bayesian version of Martin-Lof test. Then we define random sequences with respect to parametric models based on our universal Bayes test. We state some theorems related to Bayesian statistical inference in terms of random sequence\",\"PeriodicalId\":115298,\"journal\":{\"name\":\"2006 IEEE International Symposium on Information Theory\",\"volume\":\"21 3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE International Symposium on Information Theory\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIT.2006.261937\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE International Symposium on Information Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIT.2006.261937","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Bayesian approach to a definition of random sequences and its applications to statistical inference
We introduce a universal Bayes test, which is a Bayesian version of Martin-Lof test. Then we define random sequences with respect to parametric models based on our universal Bayes test. We state some theorems related to Bayesian statistical inference in terms of random sequence