The feasible solution algorithm for the minimum covariance determinant estimator in multivariate data

DOI10.1016/0167-9473(92)00071-XzbMath0937.62595OpenAlexW2012234124MaRDI QIDQ1361544

Douglas M. Hawkins

Publication date: 25 August 1997

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0167-9473(92)00071-x

zbMATH Keywords

outliersmultivariatehigh breakdown estimation

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12)

Related Items

Robust estimation of multivariate location and shape ⋮ Reweighting approximate GM estimators: Asymptotics and residual-based graphics ⋮ Robust covariance estimates based on resampling ⋮ An easy way to increase the finite-sample efficiency of the resampled minimum volume ellipsoid estimator ⋮ A comparison of robust alternatives to Hotelling’sT²control chart ⋮ Modified minimum covariance determinant estimator and its application to outlier detection of chemical process data ⋮ Influence function and efficiency of the minimum covariance determinant scatter matrix estimator ⋮ Convergence of the feasible solution algorithm for least median of squares regression ⋮ Experiments with, and on, algorithms for maximum likelihood clustering ⋮ RelaxMCD: smooth optimisation for the minimum covariance determinant estimator ⋮ Robust tools for the imperfect world ⋮ Robust Hotelling's T²control charts under non-normality: the case oft-Student distribution ⋮ Multiple outlier detection in multivariate data using self-organizing maps ⋮ The complexity of computing the MCD-estimator ⋮ Maximum trimmed likelihood estimator for multivariate mixed continuous and categorical data ⋮ A procedure for the detection of multivariate outliers. ⋮ Improved feasible solution algorithms for high breakdown estimation. ⋮ Applied regression analysis bibliography update 1994-97

Cites Work

• On the relation between S-estimators and M-estimators of multivariate location and covariance
• Asymptotic behaviour of S-estimates of multivariate location parameters and dispersion matrices
• Robust m-estimators of multivariate location and scatter
• Robustness and efficiency properties of scatter matrices
• Least Median of Squares Regression
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item