R-NL: Covariance Matrix Estimation for Elliptical Distributions based on Nonlinear Shrinkage
We combine Tyler's robust estimator of the dispersion matrix with nonlinear shrinkage. This approach delivers a simple and fast estimator of the dispersion matrix in elliptical models that is robust against both heavy tails and high dimensions. We prove convergence of the iterative part of our...
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| Veröffentlicht in: | arXiv.org 2023-05 |
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| creator | Hediger, Simon Näf, Jeffrey Wolf, Michael |
| description | We combine Tyler's robust estimator of the dispersion matrix with nonlinear shrinkage. This approach delivers a simple and fast estimator of the dispersion matrix in elliptical models that is robust against both heavy tails and high dimensions. We prove convergence of the iterative part of our algorithm and demonstrate the favorable performance of the estimator in a wide range of simulation scenarios. Finally, an empirical application demonstrates its state-of-the-art performance on real data. |
| doi_str_mv | 10.48550/arxiv.2210.14854 |
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| subjects | Algorithms Dispersion Iterative methods Robustness Statistics - Methodology |
| title | R-NL: Covariance Matrix Estimation for Elliptical Distributions based on Nonlinear Shrinkage |
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