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Influence functions and outlier detection under the common principal components model: A robust approach

Boente, Graciela; Pires, Ana M.; Rodrigues, Isabel M.

Biometrika, 89 (2002), 861-875

The common principal components model for several groups of multivariate observations
assumes equal principal axes but different variances along these axes among the
groups. Influence functions for plug-in and projection-pursuit estimates under a common
principal component model are obtained. Asymptotic variances are derived from them.
Outlier detection is possible using partial influence functions.