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pcLasso: Principal Components Lasso
A method for fitting the entire regularization path of the principal components lasso for linear and logistic regression models. The algorithm uses cyclic coordinate descent in a path-wise fashion. See URL below for more information on the algorithm. See Tay, K., Friedman, J. ,Tibshirani, R., (2014) 'Principal component-guided sparse regression' <<a href="https://doi.org/10.48550/arXiv.1810.04651" target="_top">doi:10.48550/arXiv.1810.04651</a>>.
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pcLasso: Principal Components Lasso
A method for fitting the entire regularization path of the principal components lasso for linear and logistic regression models. The algorithm uses cyclic coordinate descent in a path-wise fashion. See URL below for more information on the algorithm. See Tay, K., Friedman, J. ,Tibshirani, R., (2014) 'Principal component-guided sparse regression' <<a href="https://doi.org/10.48550/arXiv.1810.04651" target="_top">doi:10.48550/arXiv.1810.04651</a>>.
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pcLasso: Principal Components Lasso
A method for fitting the entire regularization path of the principal components lasso for linear and logistic regression models. The algorithm uses cyclic coordinate descent in a path-wise fashion. See URL below for more information on the algorithm. See Tay, K., Friedman, J. ,Tibshirani, R., (2014) 'Principal component-guided sparse regression' <<a href="https://doi.org/10.48550/arXiv.1810.04651" target="_top">doi:10.48550/arXiv.1810.04651</a>>.
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5- titleCRAN: Package pcLasso
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- DC.publisherComprehensive R Archive Network (CRAN)
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5- og:titlepcLasso: Principal Components Lasso
- og:descriptionA method for fitting the entire regularization path of the principal components lasso for linear and logistic regression models. The algorithm uses cyclic coordinate descent in a path-wise fashion. See URL below for more information on the algorithm. See Tay, K., Friedman, J. ,Tibshirani, R., (2014) 'Principal component-guided sparse regression' <<a href="https://doi.org/10.48550/arXiv.1810.04651" target="_top">doi:10.48550/arXiv.1810.04651</a>>.
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5- https://CRAN.R-project.org/package=pcLasso
- https://CRAN.R-project.org/src/contrib/Archive/pcLasso
- https://arxiv.org/abs/1810.04651
- https://doi.org/10.32614/CRAN.package.pcLasso
- https://doi.org/10.48550/arXiv.1810.04651