{"title":"概率定理和单调性","authors":"F. Bruss","doi":"10.14708/MA.V47I1.6481","DOIUrl":null,"url":null,"abstract":"Given a finite sequence of events and a well-defined notion of events being interesting, the Odds-theorem (Bruss (2000)) gives an online strategy to stop on the last interesting event. It is optimal for independent events. Here we study questions in how far optimal win probabilities mirror monotonicity properties of the underlying sequence of probabilities of events. We make these questions precise, motivate them, and then give complete answers. This note, concentrating on the original Odds-theorem, is elementary, and the answers are hoped to be of interest. We include several applications.","PeriodicalId":36622,"journal":{"name":"Mathematica Applicanda","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Odds -theorem and monotonicity\",\"authors\":\"F. Bruss\",\"doi\":\"10.14708/MA.V47I1.6481\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Given a finite sequence of events and a well-defined notion of events being interesting, the Odds-theorem (Bruss (2000)) gives an online strategy to stop on the last interesting event. It is optimal for independent events. Here we study questions in how far optimal win probabilities mirror monotonicity properties of the underlying sequence of probabilities of events. We make these questions precise, motivate them, and then give complete answers. This note, concentrating on the original Odds-theorem, is elementary, and the answers are hoped to be of interest. We include several applications.\",\"PeriodicalId\":36622,\"journal\":{\"name\":\"Mathematica Applicanda\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mathematica Applicanda\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14708/MA.V47I1.6481\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Decision Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematica Applicanda","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14708/MA.V47I1.6481","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Decision Sciences","Score":null,"Total":0}
Given a finite sequence of events and a well-defined notion of events being interesting, the Odds-theorem (Bruss (2000)) gives an online strategy to stop on the last interesting event. It is optimal for independent events. Here we study questions in how far optimal win probabilities mirror monotonicity properties of the underlying sequence of probabilities of events. We make these questions precise, motivate them, and then give complete answers. This note, concentrating on the original Odds-theorem, is elementary, and the answers are hoped to be of interest. We include several applications.