Adaptive estimation for nonparametric circular regression with errors in variables
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912554826072064 |
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| author | Nguyen, Tien Dat Ngoc, Thanh Mai Pham |
| author_facet | Nguyen, Tien Dat Ngoc, Thanh Mai Pham |
| contents | This paper investigates the nonparametric estimation of a circular regression function in an errors-in-variables framework. Two settings are studied, depending on whether the covariates are circular or linear. Adaptive estimators are constructed and their theoretical performance is assessed through convergence rates over Sobolev and Hölder smoothness classes. Numerical experiments on simulated and real datasets illustrate the practical relevance of the methodology. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_18581 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Adaptive estimation for nonparametric circular regression with errors in variables Nguyen, Tien Dat Ngoc, Thanh Mai Pham Statistics Theory Primary 62G08, secondary 62H11 This paper investigates the nonparametric estimation of a circular regression function in an errors-in-variables framework. Two settings are studied, depending on whether the covariates are circular or linear. Adaptive estimators are constructed and their theoretical performance is assessed through convergence rates over Sobolev and Hölder smoothness classes. Numerical experiments on simulated and real datasets illustrate the practical relevance of the methodology. |
| title | Adaptive estimation for nonparametric circular regression with errors in variables |
| topic | Statistics Theory Primary 62G08, secondary 62H11 |
| url | https://arxiv.org/abs/2508.18581 |