This paper studies the effects of multivariate measurement errors on multivariate capability indices computed using the principal components analysis. This study shows that measurement errors influence the results of a multivariate process capability analysis, resulting in either a decrease or an increase in the capability of the process. To avoid unreliable conclusions a method is proposed for overcoming the effects of measurement errors. Furthermore, a statistical test that allows one to determine whether measurement errors alter the process covariance structure is discussed.
On the Use of Principal Component Analysis for Assessing Multivariate Process Capability / Michele, Scagliarini; Stefania, Evangelisti. - STAMPA. - (2011), pp. 46-46. (Intervento presentato al convegno CLADAG 2011 8th Scientific Meeting of the CLAssification and Data Analysis Group of the Italian Statistical Society tenutosi a University of Pavia nel September 7-9, 2011).
On the Use of Principal Component Analysis for Assessing Multivariate Process Capability
SCAGLIARINI, MICHELE;EVANGELISTI, STEFANIA
2011
Abstract
This paper studies the effects of multivariate measurement errors on multivariate capability indices computed using the principal components analysis. This study shows that measurement errors influence the results of a multivariate process capability analysis, resulting in either a decrease or an increase in the capability of the process. To avoid unreliable conclusions a method is proposed for overcoming the effects of measurement errors. Furthermore, a statistical test that allows one to determine whether measurement errors alter the process covariance structure is discussed.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
