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dc.contributor.authorChen, Hung-Chiaen_US
dc.contributor.authorWu, Pei-Chenen_US
dc.contributor.authorHuang, Jing-Yeen_US
dc.contributor.authorChen, Lin-Anen_US
dc.date.accessioned2014-12-08T15:47:57Z-
dc.date.available2014-12-08T15:47:57Z-
dc.date.issued2010-11-01en_US
dc.identifier.issn0263-2241en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.measurement.2010.07.001en_US
dc.identifier.urihttp://hdl.handle.net/11536/32014-
dc.description.abstractFor measuring the true value of a measurand, vague statistical concept of measurand results in inefficient uncertainty analysis of measurement. The vagueness is caused by the fact that true value of the measurand is an unknown parameter such as population mean or median and the measurement of this true value is a random variable. Generally a parameter may be estimated remarkably more efficiently than the prediction of the random variable. The classical uncertainty analysis in the literature has been developed based on the structure that a measurand is a random variable. This misspecification of statistical concept costs serious price of sacrificing efficiency in terms of length of the uncertainty interval. The purpose of present study is to formally formulate a statistical model for the true value of measurand and provide an uncertainty analysis for the measurement of this true value. (C) 2010 Elsevier Ltd. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectMeasurement of measuranden_US
dc.subjectUncertainty analysisen_US
dc.subjectUncertainty intervalen_US
dc.titleUncertainty analysis for measurement of measuranden_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.measurement.2010.07.001en_US
dc.identifier.journalMEASUREMENTen_US
dc.citation.volume43en_US
dc.citation.issue9en_US
dc.citation.spage1250en_US
dc.citation.epage1254en_US
dc.contributor.department統計學研究所zh_TW
dc.contributor.departmentInstitute of Statisticsen_US
dc.identifier.wosnumberWOS:000282377000020-
dc.citation.woscount5-
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