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A note on GLR charts for monitoring count processes
Various generalized likelihood ratio (GLR) charts have been proposed to monitor count processes such as binomial, Bernoulli, Poisson, and multinomial processes. The advantages of GLR charts are that designing the chart is relatively easy, estimates of the process change‐point and shift size are avai...
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Published in: | Quality and reliability engineering international 2018-10, Vol.34 (6), p.1041-1044 |
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container_title | Quality and reliability engineering international |
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creator | Lee, Jaeheon Woodall, William H. |
description | Various generalized likelihood ratio (GLR) charts have been proposed to monitor count processes such as binomial, Bernoulli, Poisson, and multinomial processes. The advantages of GLR charts are that designing the chart is relatively easy, estimates of the process change‐point and shift size are available for post‐signal diagnosis, and they are effective in detecting a wide range of shifts in the process parameter. However, for some special cases of the observations, such as observing all defective items or all non‐defective items, the GLR chart statistic for monitoring a count process has been said to be undefined. We show that the GLR chart statistic is always well defined. |
doi_str_mv | 10.1002/qre.2306 |
format | article |
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We show that the GLR chart statistic is always well defined.</description><identifier>ISSN: 0748-8017</identifier><identifier>EISSN: 1099-1638</identifier><identifier>DOI: 10.1002/qre.2306</identifier><language>eng</language><publisher>Bognor Regis: Wiley Subscription Services, Inc</publisher><subject>Charts ; Control charts ; count process ; generalized likelihood ratio chart ; Likelihood ratio ; maximum likelihood estimator ; Monitoring ; Process parameters ; Signal processing ; statistical process control</subject><ispartof>Quality and reliability engineering international, 2018-10, Vol.34 (6), p.1041-1044</ispartof><rights>2018 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3366-2498572193b1cd8d367a0373b068c5ed734f40c9c016f48bc2e61d9973972313</citedby><cites>FETCH-LOGICAL-c3366-2498572193b1cd8d367a0373b068c5ed734f40c9c016f48bc2e61d9973972313</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Lee, Jaeheon</creatorcontrib><creatorcontrib>Woodall, William H.</creatorcontrib><title>A note on GLR charts for monitoring count processes</title><title>Quality and reliability engineering international</title><description>Various generalized likelihood ratio (GLR) charts have been proposed to monitor count processes such as binomial, Bernoulli, Poisson, and multinomial processes. 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We show that the GLR chart statistic is always well defined.</description><subject>Charts</subject><subject>Control charts</subject><subject>count process</subject><subject>generalized likelihood ratio chart</subject><subject>Likelihood ratio</subject><subject>maximum likelihood estimator</subject><subject>Monitoring</subject><subject>Process parameters</subject><subject>Signal processing</subject><subject>statistical process control</subject><issn>0748-8017</issn><issn>1099-1638</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp10E9LwzAYx_EgCtYp-BICXrx0PsnT5c9xjDmFgjh2D22aasfWbEmL7N3brV49PZcPzw--hDwymDIA_nIMbsoRxBVJGGidMoHqmiQgM5UqYPKW3MW4BRiwVgnBOW1956hv6SpfU_tdhC7S2ge6923T-dC0X9T6vu3oIXjrYnTxntzUxS66h787IZvX5WbxluYfq_fFPE8tohApz7SaSc40lsxWqkIhC0CJJQhlZ66SmNUZWG2BiTpTpeVOsEpriVpyZDghT-PbYfjYu9iZre9DOywazkApAMVxUM-jssHHGFxtDqHZF-FkGJhzETMUMeciA01H-tPs3OlfZz7Xy4v_BTEpXsk</recordid><startdate>201810</startdate><enddate>201810</enddate><creator>Lee, Jaeheon</creator><creator>Woodall, William H.</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope></search><sort><creationdate>201810</creationdate><title>A note on GLR charts for monitoring count processes</title><author>Lee, Jaeheon ; Woodall, William H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3366-2498572193b1cd8d367a0373b068c5ed734f40c9c016f48bc2e61d9973972313</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Charts</topic><topic>Control charts</topic><topic>count process</topic><topic>generalized likelihood ratio chart</topic><topic>Likelihood ratio</topic><topic>maximum likelihood estimator</topic><topic>Monitoring</topic><topic>Process parameters</topic><topic>Signal processing</topic><topic>statistical process control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Jaeheon</creatorcontrib><creatorcontrib>Woodall, William H.</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><jtitle>Quality and reliability engineering international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Jaeheon</au><au>Woodall, William H.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A note on GLR charts for monitoring count processes</atitle><jtitle>Quality and reliability engineering international</jtitle><date>2018-10</date><risdate>2018</risdate><volume>34</volume><issue>6</issue><spage>1041</spage><epage>1044</epage><pages>1041-1044</pages><issn>0748-8017</issn><eissn>1099-1638</eissn><abstract>Various generalized likelihood ratio (GLR) charts have been proposed to monitor count processes such as binomial, Bernoulli, Poisson, and multinomial processes. The advantages of GLR charts are that designing the chart is relatively easy, estimates of the process change‐point and shift size are available for post‐signal diagnosis, and they are effective in detecting a wide range of shifts in the process parameter. However, for some special cases of the observations, such as observing all defective items or all non‐defective items, the GLR chart statistic for monitoring a count process has been said to be undefined. We show that the GLR chart statistic is always well defined.</abstract><cop>Bognor Regis</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/qre.2306</doi><tpages>4</tpages></addata></record> |
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subjects | Charts Control charts count process generalized likelihood ratio chart Likelihood ratio maximum likelihood estimator Monitoring Process parameters Signal processing statistical process control |
title | A note on GLR charts for monitoring count processes |
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