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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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| I publikationen: | Stat Appl Genet Mol Biol |
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| Huvudupphovsmän: | , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
2016
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| Ämnen: | |
| Länkar: | 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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