Jensen, Willis A.Birch, Jeffrey B.Woodall, William H.2019-05-082019-05-082005http://hdl.handle.net/10919/89427The goal of Phase I monitoring of multivariate data is to identify multivariate outliers and step changes so that the estimated control limits are sufficiently accurate for Phase II monitoring. High breakdown estimation methods based on the minimum volume ellipsoid (MVE) or the minimum covariance determinant (MCD) are well suited to detecting multivariate outliers in data. However, they are difficult to implement in practice due to the extensive computation required to obtain the estimates. Based on previous studies, it is not clear which of these two estimation methods is best for control chart applications. The comprehensive simulation study here gives guidance for when to use which estimator, and control limits are provided. High breakdown estimation methods such as MCD and MVE, can be applied to a wide variety of multivariate quality control data.45 pagesapplication/pdfenIn CopyrightAsymptotic PropertiesBreakdown PointMinimum Covariance DeterminantMinimum Volume EllipsoidMultivariate OutliersMultivariate Statistical Process ControlRobust EstimationTechnical reporthttps://www.stat.vt.edu/content/dam/stat_vt_edu/graphics-and-pdfs/research-papers/Technical_Reports/TechReport05-6.pdf