Properties of a new $R$-estimator of shape matrices
Abstract
This paper aims at presenting a simulative analysis of the main properties of a new -estimator of shape matrices in Complex Elliptically Symmetric (CES) distributed observations. First proposed by Hallin, Oja and Paindaveine for the real-valued case and then extended to the complex field in our recent work, this -estimator has the remarkable property to be, at the same time, \textit{distributionally robust} and \textit{semiparametric efficient}. Here, the efficiency of different possible configurations of this -estimator are investigated by comparing the resulting Mean Square Error (MSE) with the Constrained Semiparametric Cram\'{e}r-Rao Bound (CSCRB). Moreover, its robustness to outliers is assessed and compared with the one of the celebrated Tyler's estimator.
Keywords
Cite
@article{arxiv.2002.11967,
title = {Properties of a new $R$-estimator of shape matrices},
author = {Stefano Fortunati and Alexandre Renaux and Frédéric Pascal},
journal= {arXiv preprint arXiv:2002.11967},
year = {2020}
}
Comments
This paper has been accepted to the 28th European Signal Processing Conference, EUSIPCO 2020 (5 pages, 5 figures)