{"title":"获得与蒙特卡罗方法估计相容的不确定性估计","authors":"I. Zakharov, O. Botsiura, P. Neyezhmakov","doi":"10.23919/MEASUREMENT47340.2019.8779925","DOIUrl":null,"url":null,"abstract":"The proposed approaches to the implementation of the algorithm for processing the results and the measurement uncertainty evaluation based on the Bayesian method are considered. Expressions to obtain unbiased estimates of the measurand, its standard and expanded uncertainties are given. It is shown that to obtain standard and expanded uncertainty, it is necessary to take into account the kurtosis of the input quantities distributions.","PeriodicalId":129350,"journal":{"name":"2019 12th International Conference on Measurement","volume":"103 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Obtaining Uncertainty Estimates Compatible with Estimates of Monte Carlo Method\",\"authors\":\"I. Zakharov, O. Botsiura, P. Neyezhmakov\",\"doi\":\"10.23919/MEASUREMENT47340.2019.8779925\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The proposed approaches to the implementation of the algorithm for processing the results and the measurement uncertainty evaluation based on the Bayesian method are considered. Expressions to obtain unbiased estimates of the measurand, its standard and expanded uncertainties are given. It is shown that to obtain standard and expanded uncertainty, it is necessary to take into account the kurtosis of the input quantities distributions.\",\"PeriodicalId\":129350,\"journal\":{\"name\":\"2019 12th International Conference on Measurement\",\"volume\":\"103 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 12th International Conference on Measurement\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/MEASUREMENT47340.2019.8779925\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 12th International Conference on Measurement","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/MEASUREMENT47340.2019.8779925","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Obtaining Uncertainty Estimates Compatible with Estimates of Monte Carlo Method
The proposed approaches to the implementation of the algorithm for processing the results and the measurement uncertainty evaluation based on the Bayesian method are considered. Expressions to obtain unbiased estimates of the measurand, its standard and expanded uncertainties are given. It is shown that to obtain standard and expanded uncertainty, it is necessary to take into account the kurtosis of the input quantities distributions.
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