{"title":"具有指数故障时间数据的系统的贝叶斯先验分布","authors":"K. Fertig","doi":"10.1214/AOMS/1177692376","DOIUrl":null,"url":null,"abstract":"In this paper, confidence bounds on the reliability of a serial system composed of exponential subsystems are considered. Both the classical and the Bayesian analyses are discussed. The main result is that for the case in which there are no previous data, then there are no prior distributions on the subsystem reliabilities that are independent of current data and that yield the uniformly most accurate unbiased confidence bounds available through classical techniques.","PeriodicalId":50764,"journal":{"name":"Annals of Mathematical Statistics","volume":"1 1","pages":"1441-1448"},"PeriodicalIF":0.0000,"publicationDate":"1972-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Bayesian Prior Distributions for Systems with Exponential Failure-time Data\",\"authors\":\"K. Fertig\",\"doi\":\"10.1214/AOMS/1177692376\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, confidence bounds on the reliability of a serial system composed of exponential subsystems are considered. Both the classical and the Bayesian analyses are discussed. The main result is that for the case in which there are no previous data, then there are no prior distributions on the subsystem reliabilities that are independent of current data and that yield the uniformly most accurate unbiased confidence bounds available through classical techniques.\",\"PeriodicalId\":50764,\"journal\":{\"name\":\"Annals of Mathematical Statistics\",\"volume\":\"1 1\",\"pages\":\"1441-1448\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1972-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals of Mathematical Statistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1214/AOMS/1177692376\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Mathematical Statistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1214/AOMS/1177692376","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Bayesian Prior Distributions for Systems with Exponential Failure-time Data
In this paper, confidence bounds on the reliability of a serial system composed of exponential subsystems are considered. Both the classical and the Bayesian analyses are discussed. The main result is that for the case in which there are no previous data, then there are no prior distributions on the subsystem reliabilities that are independent of current data and that yield the uniformly most accurate unbiased confidence bounds available through classical techniques.