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Donoho D. L. (1982) Breakdown properties of multivariate location estimators 


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Donoho D. L. (1982) Breakdown properties of multivariate location estimators are crucial for robust estimation. Various high-breakdown-point estimators, such as the MM-estimator with smooth hard rejection and the Rocke S-estimator, are designed for efficiency at the Gaussian distribution but can lack efficiency in non-Gaussian scenarios. A new S-q estimator is proposed for symmetric elliptical distributions, offering higher maximum efficiency across common families like Gaussian, t-, Cauchy distributions while maintaining a high breakdown point. Additionally, the S-q estimator demonstrates robustness comparable to leading estimators and stability with initial conditions, making it broadly applicable for practitioners. This advancement in multivariate location estimation is exemplified in financial portfolio optimization, showcasing the practical utility of the S-q estimator.

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The paper discusses affine-equivariant multivariate location estimators under Lp loss functions, providing asymptotic properties and equivariance under affine transformations, but does not address Donoho's breakdown properties.
The paper introduces a new S-q estimator for multivariate scatter and location with high efficiency and breakdown point, surpassing existing estimators for elliptical distributions.
The paper introduces a new S-q estimator with high efficiency and maximum breakdown point for multivariate scatter and location estimation in elliptical distributions, surpassing existing estimators.
Not addressed in the paper.

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