Sensitivity Coefficient In Principal Component Analysis: Robust Case

摘要

In the classical principal component analysis (PCA), the empirical influence function for the sensitivity coefficient p is used to detect influential observations on the subspace spanned by the dominants principal components. In this article, we derive the influence function of p in the case where the reweighted minimum covariance determinant (MCD~1) is used as estimator of multivariate location and scatter. Our aim is to confirm the reliability in terms of robustness of the MCD~1 via the approach based on the influence function of the sensitivity coefficient.