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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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Publicat a:Bioinformatics
Autors principals: He, Kevin, Li, Yanming, Zhu, Ji, Liu, Hongliang, Lee, Jeffrey E., Amos, Christopher I., Hyslop, Terry, Jin, Jiashun, Lin, Huazhen, Wei, Qinyi, Li, Yi
Format: Artigo
Idioma:Inglês
Publicat: Oxford University Press 2016
Matèries:
Accés en línia: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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