Eigenvector distributions and optimal shrinkage estimators for large covariance and precision matrices
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866913325271482368 |
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| author | Ding, Xiucai Li, Yun Yang, Fan |
| author_facet | Ding, Xiucai Li, Yun Yang, Fan |
| contents | This paper focuses on investigating Stein's invariant shrinkage estimators for large sample covariance matrices and precision matrices in high-dimensional settings. We consider models that have nearly arbitrary population covariance matrices, including those with potential spikes. By imposing mild technical assumptions, we establish the asymptotic limits of the shrinkers for a wide range of loss functions. A key contribution of this work, enabling the derivation of the limits of the shrinkers, is a novel result concerning the asymptotic distributions of the non-spiked eigenvectors of the sample covariance matrices, which can be of independent interest. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_14751 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Eigenvector distributions and optimal shrinkage estimators for large covariance and precision matrices Ding, Xiucai Li, Yun Yang, Fan Statistics Theory Probability 60K35 This paper focuses on investigating Stein's invariant shrinkage estimators for large sample covariance matrices and precision matrices in high-dimensional settings. We consider models that have nearly arbitrary population covariance matrices, including those with potential spikes. By imposing mild technical assumptions, we establish the asymptotic limits of the shrinkers for a wide range of loss functions. A key contribution of this work, enabling the derivation of the limits of the shrinkers, is a novel result concerning the asymptotic distributions of the non-spiked eigenvectors of the sample covariance matrices, which can be of independent interest. |
| title | Eigenvector distributions and optimal shrinkage estimators for large covariance and precision matrices |
| topic | Statistics Theory Probability 60K35 |
| url | https://arxiv.org/abs/2404.14751 |