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Component-wise gradient boosting and false discovery control in survival analysis with high-dimensional covariates

Motivation: Technological advances that allow routine identification of high-dimensional risk factors have led to high demand for statistical techniques that enable full utilization of these rich sources of information for genetics studies. Variable selection for censored outcome data as well as con...

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Detalhes bibliográficos
Publicado no:Bioinformatics
Main Authors: He, Kevin, Li, Yanming, Zhu, Ji, Liu, Hongliang, Lee, Jeffrey E., Amos, Christopher I., Hyslop, Terry, Jin, Jiashun, Lin, Huazhen, Wei, Qinyi, Li, Yi
Formato: Artigo
Idioma:Inglês
Publicado em: Oxford University Press 2016
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC4757968/
https://ncbi.nlm.nih.gov/pubmed/26382192
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btv517
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