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Whilst influence functions for linear discriminant analysis (LDA) have beenfound for a single discriminant when dealing with two groups, until now thesehave not been derived in the setting of a general number of groups. In thispaper we explore the relationship between Sliced Inverse Regression (SIR) andLDA, and exploit this relationship to develop influence functions for LDA fromthose already derived for SIR. These influence functions can be used tounderstand robustness properties of LDA and also to detect influentialobservations in practice. We illustrate the usefulness of these via theirapplication to a real data set.

Influence functions for Linear Discriminant Analysis: Sensitivity analysis and efficient influence diagnostics