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The use of vector bootstrapping to improve variable selection precision in Lasso models

The Lasso is a shrinkage regression method that is widely used for variable selection in statistical genetics. Commonly, K-fold cross-validation is used to fit a Lasso model. This is sometimes followed by using bootstrap confidence intervals to improve precision in the resulting variable selections....

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Bibliografske podrobnosti
izdano v:Stat Appl Genet Mol Biol
Main Authors: Laurin, Charles, Boomsma, Dorret, Lubke, Gitta
Format: Artigo
Jezik:Inglês
Izdano: 2016
Teme:
Online dostop:https://ncbi.nlm.nih.gov/pmc/articles/PMC5131926/
https://ncbi.nlm.nih.gov/pubmed/27248122
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1515/sagmb-2015-0043
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