A model-free Screening procedure
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915660917899264 |
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| author | Dedecker, J Taupin, M L Tocquet, A S |
| author_facet | Dedecker, J Taupin, M L Tocquet, A S |
| contents | In this article, we propose a generic screening method for selecting explanatory variables correlated with the response variable Y . We make no assumptions about the existence of a model that could link Y with a subset of explanatory variables, nor about the distribution of the variables. Our procedure can therefore be described as ''model-free'' and can be applied in a wide range of situations. In order to obtain precise theoretical guarantees (Sure Screening Property and control of the False Positive Rate), we establish a Berry-Esseen type inequality for the studentized statistic of the slope estimator. We illustrate our selection procedure using two simulated examples and a real data set. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_07423 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A model-free Screening procedure Dedecker, J Taupin, M L Tocquet, A S Statistics Theory In this article, we propose a generic screening method for selecting explanatory variables correlated with the response variable Y . We make no assumptions about the existence of a model that could link Y with a subset of explanatory variables, nor about the distribution of the variables. Our procedure can therefore be described as ''model-free'' and can be applied in a wide range of situations. In order to obtain precise theoretical guarantees (Sure Screening Property and control of the False Positive Rate), we establish a Berry-Esseen type inequality for the studentized statistic of the slope estimator. We illustrate our selection procedure using two simulated examples and a real data set. |
| title | A model-free Screening procedure |
| topic | Statistics Theory |
| url | https://arxiv.org/abs/2512.07423 |