Comparisons of the Performance with Bayes Estimator and MLE for Control Charts Based on Geometric Distribution
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hong, Hwiju | - |
dc.contributor.author | Lee, Jaeheon | - |
dc.date.available | 2019-03-08T16:38:54Z | - |
dc.date.issued | 2015-10 | - |
dc.identifier.issn | 1225-066X | - |
dc.identifier.issn | 2383-5818 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/9027 | - |
dc.description.abstract | Charts based on geometric distribution are effective to monitor the proportion of nonconforming items in high-quality processes where the in-control proportion nonconforming is low. The implementation of this chart is often based on the assumption that in-control proportion nonconforming is known or accurately estimated. However, accurate parameter estimation is very difficult and may require a larger sample size than that available in practice for high-quality process where the proportion of nonconforming items is very small. An inaccurate estimate of the parameter can result in estimated control limits that cause unreliability in the monitoring process. The maximum likelihood estimator (MLE) is often used to estimate in-control proportion nonconforming. In this paper, we recommend a Bayes estimator for the in-control proportion nonconforming to incorporate practitioner knowledge and avoid estimation issues when no nonconforming items are observed in the Phase I sample. The effects of parameter estimation on the geometric chart and the geometric CUSUM chart are considered when the MLE and the Bayes estimator are used. The results show that chart performance with estimated control limits based on the Bayes estimator is generally better than that based on the MLE. | - |
dc.format.extent | 14 | - |
dc.language | 한국어 | - |
dc.language.iso | KOR | - |
dc.publisher | KOREAN STATISTICAL SOC | - |
dc.title | Comparisons of the Performance with Bayes Estimator and MLE for Control Charts Based on Geometric Distribution | - |
dc.type | Article | - |
dc.identifier.doi | 10.5351/KJAS.2015.28.5.907 | - |
dc.identifier.bibliographicCitation | KOREAN JOURNAL OF APPLIED STATISTICS, v.28, no.5, pp 907 - 920 | - |
dc.identifier.kciid | ART002044787 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.wosid | 000437602300006 | - |
dc.citation.endPage | 920 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 907 | - |
dc.citation.title | KOREAN JOURNAL OF APPLIED STATISTICS | - |
dc.citation.volume | 28 | - |
dc.type.docType | Article | - |
dc.publisher.location | 대한민국 | - |
dc.subject.keywordAuthor | ARL | - |
dc.subject.keywordAuthor | Bayes estimator | - |
dc.subject.keywordAuthor | geometric chart | - |
dc.subject.keywordAuthor | MLE | - |
dc.subject.keywordAuthor | Phase I sample | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.description.journalRegisteredClass | esci | - |
dc.description.journalRegisteredClass | kci | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
84, Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea (06974)02-820-6194
COPYRIGHT 2019 Chung-Ang University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.