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dc.contributor.authorPearn, WLen_US
dc.contributor.authorLin, GHen_US
dc.date.accessioned2014-12-08T15:41:25Z-
dc.date.available2014-12-08T15:41:25Z-
dc.date.issued2003en_US
dc.identifier.issn0026-1335en_US
dc.identifier.urihttp://hdl.handle.net/11536/28174-
dc.description.abstractPearn et al. (1992) proposed the capability index C-pmk, and investigated the statistical properties of its natural estimator (C) over cap (pmk) for stable normal processes with constant mean mu. Chen and Hsu (1995) showed that under general conditions the asymptotic distribution of (C) over cap (pmk) is normal if munot equalm, and is a linear combination of the normal and the folded-normal distributions if mu=m, where m is the mid-point between the upper and the lower specification limits. In this paper, we consider a new estimator (C) over tilde (pmk) for stable processes under a different (more realistic) condition on process mean, namely, P (mugreater than or equal tom)=p, 0less than or equal topless than or equal to1. We obtain the exact distribution, the expected value, and the variance of (C) over tilde (pmk) under normality assumption. We show that for P (mugreater than or equal tom)=0, or 1, the new estimator (C) over tilde (pmk) is the MLE of C-pmk, which is asymptotically efficient. In addition, we show that under general conditions (C) over tilde (pmk) is consistent and is asymptotically unbiased. We also show that the asymptotic distribution of (C) over tilde (pmk) is a mixture of two normal distributions.en_US
dc.language.isoen_USen_US
dc.subjectprocess capability indexen_US
dc.subjectBayesian-like estimatoren_US
dc.subjectconsistenten_US
dc.subjectmixture distributionen_US
dc.titleA Bayesian-like estimator of the process capability index C-pmken_US
dc.typeArticleen_US
dc.identifier.journalMETRIKAen_US
dc.citation.volume57en_US
dc.citation.issue3en_US
dc.citation.spage303en_US
dc.citation.epage312en_US
dc.contributor.department工業工程與管理學系zh_TW
dc.contributor.departmentDepartment of Industrial Engineering and Managementen_US
dc.identifier.wosnumberWOS:000183532500005-
dc.citation.woscount5-
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