A New Class of Asymptotically Distribution-Free Smooth Tests
Fuente:
arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866918534117851136 |
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| author | Zhang, Xiangyu Algeri, Sara |
| author_facet | Zhang, Xiangyu Algeri, Sara |
| contents | This article demonstrates how recent developments in the theory of empirical processes allow us to construct a new family of asymptotically distribution-free smooth tests. Their distribution-free property is preserved even when the parameters are estimated, model selection is performed, and the sample size is only moderately large. A computationally efficient alternative to the classical parametric bootstrap is also discussed. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_01973 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A New Class of Asymptotically Distribution-Free Smooth Tests Zhang, Xiangyu Algeri, Sara Statistics Theory Methodology This article demonstrates how recent developments in the theory of empirical processes allow us to construct a new family of asymptotically distribution-free smooth tests. Their distribution-free property is preserved even when the parameters are estimated, model selection is performed, and the sample size is only moderately large. A computationally efficient alternative to the classical parametric bootstrap is also discussed. |
| title | A New Class of Asymptotically Distribution-Free Smooth Tests |
| topic | Statistics Theory Methodology |
| url | https://arxiv.org/abs/2508.01973 |