Comparing the Efficiency of T2 Graphs for Hotelling and Classification by Ranking, Using Different Estimators of Location and Dispersion

Quality is defined simultaneously by a set of correlated variables for many products or services. To monitor a multivariate process, the classic control chart T2 (Hotelling (1947)) is often used. This chart is constructed under the assumption of normality of the observations and estimates of usual l...

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Article of journal
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2019
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Universidad Católica de Pereira
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Repositorio Institucional - RIBUC
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spa
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oai:repositorio.ucp.edu.co:10785/9878
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https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/690
http://hdl.handle.net/10785/9878
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Derechos de autor 2019 Entre Ciencia e Ingeniería
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repository_id_str
dc.title.eng.fl_str_mv Comparing the Efficiency of T2 Graphs for Hotelling and Classification by Ranking, Using Different Estimators of Location and Dispersion
dc.title.spa.fl_str_mv Comparando la Eficiencia de los Gráficos T2 de Hotelling y de Clasificación por Rangos, Utilizando Diversos Estimadores de Localización y Dispersión
title Comparing the Efficiency of T2 Graphs for Hotelling and Classification by Ranking, Using Different Estimators of Location and Dispersion
spellingShingle Comparing the Efficiency of T2 Graphs for Hotelling and Classification by Ranking, Using Different Estimators of Location and Dispersion
title_short Comparing the Efficiency of T2 Graphs for Hotelling and Classification by Ranking, Using Different Estimators of Location and Dispersion
title_full Comparing the Efficiency of T2 Graphs for Hotelling and Classification by Ranking, Using Different Estimators of Location and Dispersion
title_fullStr Comparing the Efficiency of T2 Graphs for Hotelling and Classification by Ranking, Using Different Estimators of Location and Dispersion
title_full_unstemmed Comparing the Efficiency of T2 Graphs for Hotelling and Classification by Ranking, Using Different Estimators of Location and Dispersion
title_sort Comparing the Efficiency of T2 Graphs for Hotelling and Classification by Ranking, Using Different Estimators of Location and Dispersion
description Quality is defined simultaneously by a set of correlated variables for many products or services. To monitor a multivariate process, the classic control chart T2 (Hotelling (1947)) is often used. This chart is constructed under the assumption of normality of the observations and estimates of usual location and dispersion. It is well known that this chart is very sensitive to the presence of outliers in the historical data set, causing the masking effect and therefore several proposals to construct charts T2 with alternative estimators that have become more powerful and robust charts in the presence of outliers or faster detection of change in the mean vector have been proposed. The normality of the observations is not always true in practice, then the nonparametric control charts are recommended in this case, one of them is the chart of a ranking method (Liu (1995)). Zertuchi and Cantu (2008), Velasquez and Moreno (2009), comparing the efficiency between the two charts above using conventional estimators under normal and devoid of it. This work, presents a comparative study about the efficiency of the two charts using various estimates of the mean vector and covariance matrix, in the presence of outliers in the construction phase. The efficiency of control charts is determined by the change in the early detection of mean vector. The efficiency of charts in this study is measured calculating the average run length (ARL) under control by statistical simulation through various environments encountered. We present the results obtained with their respective interpretations and conclusions.
publishDate 2019
dc.date.issued.none.fl_str_mv 2019-07-27
dc.date.accessioned.none.fl_str_mv 2022-06-01T19:08:45Z
dc.date.available.none.fl_str_mv 2022-06-01T19:08:45Z
dc.type.spa.fl_str_mv Artículo de revista
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.coar.none.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.coarversion.none.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
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dc.identifier.none.fl_str_mv https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/690
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10785/9878
url https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/690
http://hdl.handle.net/10785/9878
dc.language.none.fl_str_mv spa
language spa
dc.relation.none.fl_str_mv https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/690/693
dc.rights.spa.fl_str_mv Derechos de autor 2019 Entre Ciencia e Ingeniería
https://creativecommons.org/licenses/by-nc/4.0/deed.es_ES
dc.rights.uri.spa.fl_str_mv https://creativecommons.org/licenses/by-nc/4.0/deed.es_ES
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
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rights_invalid_str_mv Derechos de autor 2019 Entre Ciencia e Ingeniería
https://creativecommons.org/licenses/by-nc/4.0/deed.es_ES
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad Católica de Pereira
dc.source.eng.fl_str_mv Entre ciencia e ingeniería; Vol 6 No 11 (2012); 164-182
dc.source.spa.fl_str_mv Entre Ciencia e Ingeniería; Vol. 6 Núm. 11 (2012); 164-182
dc.source.por.fl_str_mv Entre ciencia e ingeniería; v. 6 n. 11 (2012); 164-182
dc.source.none.fl_str_mv 2539-4169
1909-8367
institution Universidad Católica de Pereira
repository.name.fl_str_mv Repositorio Institucional de la Universidad Católica de Pereira - RIBUC
repository.mail.fl_str_mv bdigital@metabiblioteca.com
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spelling 2022-06-01T19:08:45Z2022-06-01T19:08:45Z2019-07-27https://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/690http://hdl.handle.net/10785/9878Quality is defined simultaneously by a set of correlated variables for many products or services. To monitor a multivariate process, the classic control chart T2 (Hotelling (1947)) is often used. This chart is constructed under the assumption of normality of the observations and estimates of usual location and dispersion. It is well known that this chart is very sensitive to the presence of outliers in the historical data set, causing the masking effect and therefore several proposals to construct charts T2 with alternative estimators that have become more powerful and robust charts in the presence of outliers or faster detection of change in the mean vector have been proposed. The normality of the observations is not always true in practice, then the nonparametric control charts are recommended in this case, one of them is the chart of a ranking method (Liu (1995)). Zertuchi and Cantu (2008), Velasquez and Moreno (2009), comparing the efficiency between the two charts above using conventional estimators under normal and devoid of it. This work, presents a comparative study about the efficiency of the two charts using various estimates of the mean vector and covariance matrix, in the presence of outliers in the construction phase. The efficiency of control charts is determined by the change in the early detection of mean vector. The efficiency of charts in this study is measured calculating the average run length (ARL) under control by statistical simulation through various environments encountered. We present the results obtained with their respective interpretations and conclusions.Para muchos productos o servicios, su calidad es definida simultáneamente por un conjunto de variables correlacionadas. Para monitorear un proceso multivariado, el gráfico de control clásico (Hotelling (1947)) es frecuentemente usado. Este gráfico es construido bajo el supuesto de normalidad de las observaciones y con estimadores de localización y dispersión usuales. Es bien conocido, que este gráfico es muy sensible a la presencia de outliers en el conjunto de datos históricos provocando el efecto de enmascaramiento, por lo cual han surgido varias propuestas de construcción de gráficos con estimadores alternativos que los ha convertido en gráficos más potentes y robustos ante la presencia de datos atípicos o en la detección más rápida del cambio en el vector de medias. La normalidad de las observaciones no siempre se cumple en la práctica, luego los gráficos de control no paramétricos son los recomendados en este caso, uno de ellos es el gráfico de clasificación por rangos (Liu (1995)). Trabajos como el de Zertuchi y Cantú (2008), Velásquez y Moreno (2009), comparan la eficiencia de los dos gráficos mencionados usando estimadores usuales, bajo normalidad y carente de ella.  En este trabajo, se presenta un estudio comparativo de la eficiencia de los dos gráficos usando diversos estimadores del vector de medias y de la matriz de covarianzas, en presencia de datos atípicos en la fase de construcción. La eficiencia de los gráficos de control, es determinada por la pronta detección en el cambio del vector de medias. La eficiencia de los gráficos en este estudio, se mide a través del cálculo de la longitud promedio de corrida (ARL) bajo control, mediante simulación estadística ante diversos ambientes planteados. Se presentan los resultados obtenidos con sus respectivas interpretaciones y conclusiones.application/pdfspaUniversidad Católica de Pereirahttps://revistas.ucp.edu.co/index.php/entrecienciaeingenieria/article/view/690/693Derechos de autor 2019 Entre Ciencia e Ingenieríahttps://creativecommons.org/licenses/by-nc/4.0/deed.es_EShttps://creativecommons.org/licenses/by-nc/4.0/deed.es_ESinfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Entre ciencia e ingeniería; Vol 6 No 11 (2012); 164-182Entre Ciencia e Ingeniería; Vol. 6 Núm. 11 (2012); 164-182Entre ciencia e ingeniería; v. 6 n. 11 (2012); 164-1822539-41691909-8367Comparing the Efficiency of T2 Graphs for Hotelling and Classification by Ranking, Using Different Estimators of Location and DispersionComparando la Eficiencia de los Gráficos T2 de Hotelling y de Clasificación por Rangos, Utilizando Diversos Estimadores de Localización y DispersiónArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionGonzález Borja, JoaquínMontes Masmela, HaiderLugo Capera, Oscar AndrésPublication10785/9878oai:repositorio.ucp.edu.co:10785/98782025-01-27 18:59:54.56https://creativecommons.org/licenses/by-nc/4.0/deed.es_ESDerechos de autor 2019 Entre Ciencia e Ingenieríametadata.onlyhttps://repositorio.ucp.edu.coRepositorio Institucional de la Universidad Católica de Pereira - RIBUCbdigital@metabiblioteca.com