{"title":"正态分布方差的测量程序","authors":"E. Collani, D. Monica, Panaite Victorina","doi":"10.1515/EQC.2002.155","DOIUrl":null,"url":null,"abstract":"Neyman prediction and measurement procedures have been discussed by E.v. Collani, M. Dumitrescu and their co-workers since 1999. These procedures offer optimal, however, computational rather intensive ways for predicting with respect to the future outcome of a random variable and measuring with respect to the actual value of a deterministic variable under the realistic condition that the range of variability of any involved variable is bounded.","PeriodicalId":360039,"journal":{"name":"Economic Quality Control","volume":"30 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Measurement Procedures for the Variance of a Normal Distribution\",\"authors\":\"E. Collani, D. Monica, Panaite Victorina\",\"doi\":\"10.1515/EQC.2002.155\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Neyman prediction and measurement procedures have been discussed by E.v. Collani, M. Dumitrescu and their co-workers since 1999. These procedures offer optimal, however, computational rather intensive ways for predicting with respect to the future outcome of a random variable and measuring with respect to the actual value of a deterministic variable under the realistic condition that the range of variability of any involved variable is bounded.\",\"PeriodicalId\":360039,\"journal\":{\"name\":\"Economic Quality Control\",\"volume\":\"30 6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Economic Quality Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1515/EQC.2002.155\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Economic Quality Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/EQC.2002.155","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
自1999年以来,e.v. Collani, M. Dumitrescu及其同事一直在讨论内曼预测和测量程序。然而,这些程序为预测随机变量的未来结果和在任何相关变量的可变性范围有限的现实条件下测量确定性变量的实际值提供了最佳的、计算上相当密集的方法。
Measurement Procedures for the Variance of a Normal Distribution
Neyman prediction and measurement procedures have been discussed by E.v. Collani, M. Dumitrescu and their co-workers since 1999. These procedures offer optimal, however, computational rather intensive ways for predicting with respect to the future outcome of a random variable and measuring with respect to the actual value of a deterministic variable under the realistic condition that the range of variability of any involved variable is bounded.