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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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Bibliografische gegevens
Gepubliceerd in:Stat Appl Genet Mol Biol
Hoofdauteurs: He, Kevin, Zhou, Xiang, Jiang, Hui, Wen, Xiaoquan, Li, Yi
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: 2018
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Online toegang: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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