Robust principal components regression as a detection tool for outliers

Robust principal components regression procedure based on the ellipsoidal multivariate trimming (MVT) and the least median of squares (LMS) methods is proposed as an outlier detection tool. The performance of this approach was evaluated using simulated data randomly contaminated.