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

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.