Hejazi, Nima S
Coyle, Jeremy R
van der Laan, Mark J
2020-09-25
<p>A scalable implementation of the highly adaptive lasso algorithm,including routines for constructing sparse matrices of basis functions of the observed data, as well as a custom implementation of Lasso regression tailored to enhance efficiency when the matrix of predictors is composed exclusively of indicator basis functions. For ease of use and increased flexibility, the Lasso fitting routines may invoke code from the glmnet package optionally. This version of the R package corresponds to the software paper in the <em>Journal of Open Source Software</em>.</p>
https://doi.org/10.5281/zenodo.4050561
oai:zenodo.org:4050561
Zenodo
https://doi.org/10.5281/zenodo.3558313
info:eu-repo/semantics/openAccess
GNU General Public License v3.0 only
https://www.gnu.org/licenses/gpl-3.0-standalone.html
machine learning
semiparametric theory
nonparametric estimation
causal inference
hal9001: Scalable highly adaptive lasso regression in R
info:eu-repo/semantics/other