A Nearest In Control Neighbour Based Method to Estimate Variable Contributions to the Hotelling's Statistic

Hotelling’s statistic, also called T-statistic, is widely used in statistical process control as an extension of the univariate student’s chart to reliably detect out of control status in multivariate processes. Although it is a very efficient tool for detection purposes, by itself, it offers no assistance about the origin of the declared faulty status. Several different approaches have been proposed to estimate the variable values’ effect on the overall statistic’s value. Some of these strategies work in the original measurement space while others interpret the results coming from the analysis in latent variable spaces using for example principal component analysis (PCA) or independent component analysis (ICA). In this work we present a novel strategy based on finding the nearest “in-control” neighbour of the observation point.