A resistant estimator of multivariate location and dispersion

DOI10.1016/S0167-9473(03)00119-1zbMath1429.62189MaRDI QIDQ956901

David J. Olive

Publication date: 26 November 2008

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

zbMATH Keywords

minimum covariance determinant estimatorDD plot

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (10)

The DetS and DetMM estimators for multivariate location and scatter ⋮ New Results on the Small-Sample Properties of Some Robust Univariate Estimators of Location ⋮ Comparing Measures of Location: Some Small-Sample Results When Distributions Differ in Skewness and Kurtosis Under Heterogeneity of Variances ⋮ Bootstrapping analogs of the two-sample hotelling’s T² test ⋮ Some small-sample properties of some recently proposed multivariate outlier detection techniques ⋮ OLS for 1D Regression Models ⋮ Robust Multivariate Regression When There is Heteroscedasticity ⋮ Separating a mixture of two normals with proportional covariances ⋮ A comparative study for robust canonical correlation methods ⋮ Discussion of: ``The power of monitoring: how to make the most of a contaminated multivariate sample

Uses Software

• covRobust

Cites Work

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• A local breakdown property of robust tests in linear regression
• Improved feasible solution algorithms for high breakdown estimation.
• Asymptotics of reweighted estimators of multivariate location and scatter
• Rate of convergence of depth contours: with application to a multivariate metrically trimmed mean.
• Asymptotic normality of multivariate trimmed means
• Robust Estimation of Dispersion Matrices and Principal Components
• Robust estimation and outlier detection with correlation coefficients
• Inconsistency of Resampling Algorithms for High-Breakdown Regression Estimators and a New Algorithm
• Nearest-Neighbor Variance Estimation (NNVE)
• Some quantitative relationships between two types of finite sample breakdown point

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