High breakdown estimators for principal components: the projection-pursuit approach revisited
- 1 July 2005
- journal article
- Published by Elsevier BV in Journal of Multivariate Analysis
- Vol. 95 (1), 206-226
- https://doi.org/10.1016/j.jmva.2004.08.002
Abstract
No abstract availableKeywords
This publication has 23 references indexed in Scilit:
- Asymptotic distributions of principal components based on robust dispersionsBiometrika, 2003
- Influence functions and outlier detection under the common principal components model: A robust approachBiometrika, 2002
- Principal component analysis based on robust estimators of the covariance or correlation matrix: influence functions and efficienciesBiometrika, 2000
- Robust principal component and factor analysis in the geostatistical treatment of environmental dataEnvironmetrics, 1999
- Generalized S-EstimatorsJournal of the American Statistical Association, 1994
- Efficient high-breakdown M-estimators of scaleStatistics & Probability Letters, 1994
- Robust Singular Value Decompositions: A New Approach to Projection PursuitJournal of the American Statistical Association, 1993
- Asymptotic Behaviour of $S$-Estimates of Multivariate Location Parameters and Dispersion MatricesThe Annals of Statistics, 1987
- Influence in principal components analysisBiometrika, 1985
- Robust Estimation of Dispersion Matrices and Principal ComponentsJournal of the American Statistical Association, 1981