Implicitly weighted multivariate methods for high-dimensional data

Abstract

This work deals with a robustification of classification analysis for data with a high dimension. We combine a robust principal component analysis and robust classification.

This method inherits the idea of down-weighting less reliable data points from the least weighted squares regression.

Keywords

• Robust statistics
• multivariate statistics
• least weighted squares
• computational aspects.