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ADAPTIVE ROBUST VARIABLE SELECTION
Heavy-tailed high-dimensional data are commonly encountered in various scientific fields and pose great challenges to modern statistical analysis. A natural procedure to address this problem is to use penalized quantile regression with weighted L(1)-penalty, called weighted robust Lasso (WR-Lasso),...
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| Pubblicato in: | Ann Stat |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2014
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4286898/ https://ncbi.nlm.nih.gov/pubmed/25580039 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1214/13-AOS1191 |
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