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Multivariate sparse group lasso for the multivariate multiple linear regression with an arbitrary group structure

We propose a multivariate sparse group lasso variable selection and estimation method for data with high-dimensional predictors as well as high-dimensional response variables. The method is carried out through a penalized multivariate multiple linear regression model with an arbitrary group structur...

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Bibliografische gegevens
Gepubliceerd in:Biometrics
Hoofdauteurs: Li, Yanming, Nan, Bin, Zhu, Ji
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: 2015
Onderwerpen:
Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC4479976/
https://ncbi.nlm.nih.gov/pubmed/25732839
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1111/biom.12292
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