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hal9001  

The Scalable Highly Adaptive Lasso
View on CRAN: Click here


Download and install hal9001 package within the R console
Install from CRAN:
install.packages("hal9001")

Install from Github:
library("remotes")
install_github("cran/hal9001")

Install by package version:
library("remotes")
install_version("hal9001", "0.4.6")



Attach the package and use:
library("hal9001")
Maintained by
Jeremy Coyle
[Scholar Profile | Author Map]
First Published: 2020-03-05
Latest Update: 2022-02-09
Description:
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 functions. For ease of use and increased flexibility, the Lasso fitting routines invoke code from the 'glmnet' package by default. The highly adaptive lasso was first formulated and described by MJ van der Laan (2017) , with practical demonstrations of its performance given by Benkeser and van der Laan (2016) . This implementation of the highly adaptive lasso algorithm was described by Hejazi, Coyle, and van der Laan (2020) .
How to cite:
Jeremy Coyle (2020). hal9001: The Scalable Highly Adaptive Lasso. R package version 0.4.6, https://cran.r-project.org/web/packages/hal9001. Accessed 01 Apr. 2025.
Previous versions and publish date:
0.2.5 (2020-03-05 21:20), 0.2.6 (2020-06-27 06:50), 0.2.7 (2021-01-22 06:40), 0.4.1 (2021-09-28 16:00), 0.4.2 (2022-01-26 21:02), 0.4.3 (2022-02-09 23:50)
Other packages that cited hal9001 R package
View hal9001 citation profile
Other R packages that hal9001 depends, imports, suggests or enhances
Complete documentation for hal9001
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