期刊
TECHNOMETRICS
卷 43, 期 2, 页码 223-229出版社
TAYLOR & FRANCIS INC
DOI: 10.1198/004017001750386332
关键词
binary data; EM algorithm; go/no-go testing; inspection errors; mixture models; profile likelihood
Quantitative measurement is an accepted ideal, but pass-fail inspection remains a fact of life, even in high-technology industries. For pass-fail data variance components do not separate gauge and material variation. This article focuses on maximum likelihood estimation of conditional misclassification rates, with and without reference evaluations to anchor the analysis. Likelihood-based confidence intervals and testing for reproducibility effects an also discussed.
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