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Estimation of Large-Dimensional Covariance Matrices via Second-Order Stein-Type Regularization
This paper tackles the problem of estimating the covariance matrix in large-dimension and small-sample-size scenarios. Inspired by the well-known linear shrinkage estimation, we propose a novel second-order Stein-type regularization strategy to generate well-conditioned covariance matrix estimators....
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857414/ https://www.ncbi.nlm.nih.gov/pubmed/36673194 http://dx.doi.org/10.3390/e25010053 |