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2008 A note on sensitivity of principal component subspaces and the efficient detection of influential observations in high dimensions
Luke A. Prendergast
Electron. J. Statist. 2: 454-467 (2008). 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.

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Luke A. Prendergast. "A note on sensitivity of principal component subspaces and the efficient detection of influential observations in high dimensions." Electron. J. Statist. 2 454 - 467, 2008. https://doi.org/10.1214/08-EJS201

Information

Published: 2008
First available in Project Euclid: 26 June 2008

zbMATH: 1320.62140
MathSciNet: MR2417389
Digital Object Identifier: 10.1214/08-EJS201

Subjects:
Primary: 62F35
Secondary: 62H12

Rights: Copyright © 2008 The Institute of Mathematical Statistics and the Bernoulli Society

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