A note on sensitivity of principal component subspaces and the efficient detection of influential observations in high dimensions
arXiv:0803.0402 · doi:10.1214/08-EJS201
Abstract
In this paper we introduce an influence measure based on second order expansion of the RV and GCD measures for the comparison between unperturbed and perturbed eigenvectors of a symmetric matrix estimator. Example estimators are considered to highlight how this measure compliments recent influence analysis. Importantly, we also show how a sample based version of this measure can be used to accurately and efficiently detect influential observations in practice.
Published in at http://dx.doi.org/10.1214/08-EJS201 the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)