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An Orthogonally Equivariant Estimator of the Covariance Matrix in High Dimensions and for Small Sample Sizes
We introduce an estimation method of covariance matrices in a high-dimensional setting, i.e., when the dimension of the matrix, p, is larger than the sample size n. Specifically, we propose an orthogonally equivariant estimator. The eigenvectors of such estimator are the same as those of the sample...
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| Gepubliceerd in: | J Stat Plan Inference |
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| Hoofdauteurs: | , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
2020
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7709931/ https://ncbi.nlm.nih.gov/pubmed/33281277 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.jspi.2020.10.006 |
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