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High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking
Penalized likelihood approaches are widely used for high-dimensional regression. Although many methods have been proposed and the associated theory is now well developed, the relative efficacy of different approaches in finite-sample settings, as encountered in practice, remains incompletely underst...
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| 出版年: | Stat Comput |
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| 主要な著者: | , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Springer US
2019
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7026376/ https://ncbi.nlm.nih.gov/pubmed/32132772 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s11222-019-09914-9 |
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