Asymptotic expected sensitivity function and its applications to nonparametric correlation estimators
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arXiv
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866913191563362304 |
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| author | Zhang, Qingyang |
| author_facet | Zhang, Qingyang |
| contents | We introduce a new type of influence function, the asymptotic expected sensitivity function, which is often equivalent to but mathematically more tractable than the traditional one based on the Gateaux derivative. To illustrate, we study the robustness of some important rank correlations, including Spearman's and Kendall's correlations, and the recently developed Chatterjee's correlation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_05281 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Asymptotic expected sensitivity function and its applications to nonparametric correlation estimators Zhang, Qingyang Methodology We introduce a new type of influence function, the asymptotic expected sensitivity function, which is often equivalent to but mathematically more tractable than the traditional one based on the Gateaux derivative. To illustrate, we study the robustness of some important rank correlations, including Spearman's and Kendall's correlations, and the recently developed Chatterjee's correlation. |
| title | Asymptotic expected sensitivity function and its applications to nonparametric correlation estimators |
| topic | Methodology |
| url | https://arxiv.org/abs/2401.05281 |