Many different robust estimation approaches for the covariance or shape matrix of multivariate data have been … established until today. Tyler's M-estimator has been recognized as the 'most robust' M-estimator for the shape matrix of … data. It is shown that the shape matrix estimator remains distribution-free under the class of generalized elliptical …

Many different robust estimation approaches for the covariance or shape matrix of multivariate data have been … established until today. Tyler's M-estimator has been recognized as the 'most robust' M-estimator for the shape matrix of … data. It is shown that the shape matrix estimator remains distribution-free under the class of generalized elliptical …

for ∑ or another matrix Γ ∝ ∑. In the present work, robust estimators for the shape matrix and the associated scale are … function. If it is non-normal (this holds for example if the estimators for the shape matrix and scale are based on the minimum …

for ∑ or another matrix Γ ∝ ∑. In the present work, robust estimators for the shape matrix and the associated scale are … function. If it is non-normal (this holds for example if the estimators for the shape matrix and scale are based on the minimum …