HOTELLING'S T² CONTROL CHARTS BASED ON ROBUST ESTIMATORS
Under the presence of multivariate outliers, in a Phase I analysis of historical set of data, the T² control chart based on the usual sample mean vector and sample variance - covariance matrix performs poorly. Several alternative estimators have been proposed. Among them, estimators based on the minimum volume ellipsoid (MVE) and the minimum covariance determinant (MCD) are powerful in detecting a reasonable number of outliers. In this paper we propose a T² control chart using the biweight S estimators for the location and dispersion parameters when monitoring multivariate individual observations. Simulation studies show that this method outperforms the T² control chart based on MVE estimators for a small number of observations.
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| Principais autores: | , , |
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| Formato: | Digital revista |
| Idioma: | English |
| Publicado em: |
Universidad Nacional de Colombia
2010
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| Acesso em linha: | http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S0012-73532010000300025 |
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| Resumo: | Under the presence of multivariate outliers, in a Phase I analysis of historical set of data, the T² control chart based on the usual sample mean vector and sample variance - covariance matrix performs poorly. Several alternative estimators have been proposed. Among them, estimators based on the minimum volume ellipsoid (MVE) and the minimum covariance determinant (MCD) are powerful in detecting a reasonable number of outliers. In this paper we propose a T² control chart using the biweight S estimators for the location and dispersion parameters when monitoring multivariate individual observations. Simulation studies show that this method outperforms the T² control chart based on MVE estimators for a small number of observations. |
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