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 minim...
- Autores:
-
Yáñez Canal, Sergio
González Alvarez, Nelfi Gertrudis
Vargas Navas, José Alberto
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2010
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/37603
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/37603
http://bdigital.unal.edu.co/27687/
- Palabra clave:
- Multivariate Control Charts
MVE Estimators
Outliers
S Estimators.
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
| Summary: | 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 T²control chart based on MVE estimators for a small number of observations. |
|---|