A note on condition numbers for generalized inverse C^‡_A and their statistical estimation
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arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866912820300349440 |
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| author | Samar, Mahvish Shahkoor, Abdual |
| author_facet | Samar, Mahvish Shahkoor, Abdual |
| contents | In this paper, we consider the condition number for the generalized inverse C^‡_A. We first present the explicit expression of normwise mixed and componentwise condition numbers. Then, we derive the explicit expression of normwise condition number without Kronecker product using the classical method for condition numbers. With the intermediate result, i.e., the derivative of C^‡_A, we can recover the explicit expressions of condition numbers for solution of Indefinite least squares problem with equality constraint. To estimate these condition numbers with high reliability, we choose the probabilistic spectral norm estimator and the small-sample statistical condition estimation method and devise three algorithms. Numerical experiments are provided to illustrate the obtained results |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_08553 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A note on condition numbers for generalized inverse C^‡_A and their statistical estimation Samar, Mahvish Shahkoor, Abdual Numerical Analysis In this paper, we consider the condition number for the generalized inverse C^‡_A. We first present the explicit expression of normwise mixed and componentwise condition numbers. Then, we derive the explicit expression of normwise condition number without Kronecker product using the classical method for condition numbers. With the intermediate result, i.e., the derivative of C^‡_A, we can recover the explicit expressions of condition numbers for solution of Indefinite least squares problem with equality constraint. To estimate these condition numbers with high reliability, we choose the probabilistic spectral norm estimator and the small-sample statistical condition estimation method and devise three algorithms. Numerical experiments are provided to illustrate the obtained results |
| title | A note on condition numbers for generalized inverse C^‡_A and their statistical estimation |
| topic | Numerical Analysis |
| url | https://arxiv.org/abs/2601.08553 |