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Consistent group selection in high-dimensional linear regression
In regression problems where covariates can be naturally grouped, the group Lasso is an attractive method for variable selection since it respects the grouping structure in the data. We study the selection and estimation properties of the group Lasso in high-dimensional settings when the number of g...
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| 主要な著者: | , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2010
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3209717/ https://ncbi.nlm.nih.gov/pubmed/22072891 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3150/10-BEJ252 |
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