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False discovery control for penalized variable selections with high-dimensional covariates
Modern bio-technologies have produced a vast amount of high-throughput data with the number of predictors much exceeding the sample size. Penalized variable selection has emerged as a powerful and efficient dimension reduction tool. However, control of false discoveries (i.e. inclusion of irrelevant...
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| Опубликовано в: : | Stat Appl Genet Mol Biol |
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| Главные авторы: | , , , , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
2018
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6450074/ https://ncbi.nlm.nih.gov/pubmed/30864387 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1515/sagmb-2018-0038 |
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