Covariance Operator Estimation: Sparsity, Lengthscale, and Ensemble Kalman Filters
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2023
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| _version_ | 1866914727071842304 |
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| author | Al-Ghattas, Omar Chen, Jiaheng Sanz-Alonso, Daniel Waniorek, Nathan |
| author_facet | Al-Ghattas, Omar Chen, Jiaheng Sanz-Alonso, Daniel Waniorek, Nathan |
| contents | This paper investigates covariance operator estimation via thresholding. For Gaussian random fields with approximately sparse covariance operators, we establish non-asymptotic bounds on the estimation error in terms of the sparsity level of the covariance and the expected supremum of the field. We prove that thresholded estimators enjoy an exponential improvement in sample complexity compared with the standard sample covariance estimator if the field has a small correlation lengthscale. As an application of the theory, we study thresholded estimation of covariance operators within ensemble Kalman filters. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_16933 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Covariance Operator Estimation: Sparsity, Lengthscale, and Ensemble Kalman Filters Al-Ghattas, Omar Chen, Jiaheng Sanz-Alonso, Daniel Waniorek, Nathan Statistics Theory Probability This paper investigates covariance operator estimation via thresholding. For Gaussian random fields with approximately sparse covariance operators, we establish non-asymptotic bounds on the estimation error in terms of the sparsity level of the covariance and the expected supremum of the field. We prove that thresholded estimators enjoy an exponential improvement in sample complexity compared with the standard sample covariance estimator if the field has a small correlation lengthscale. As an application of the theory, we study thresholded estimation of covariance operators within ensemble Kalman filters. |
| title | Covariance Operator Estimation: Sparsity, Lengthscale, and Ensemble Kalman Filters |
| topic | Statistics Theory Probability |
| url | https://arxiv.org/abs/2310.16933 |