Package: hal9001 0.4.6

Jeremy Coyle

hal9001: The Scalable Highly Adaptive Lasso

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) <doi:10.1515/ijb-2015-0097>, with practical demonstrations of its performance given by Benkeser and van der Laan (2016) <doi:10.1109/DSAA.2016.93>. This implementation of the highly adaptive lasso algorithm was described by Hejazi, Coyle, and van der Laan (2020) <doi:10.21105/joss.02526>.

Authors:Jeremy Coyle [aut, cre], Nima Hejazi [aut], Rachael Phillips [aut], Lars van der Laan [aut], David Benkeser [ctb], Oleg Sofrygin [ctb], Weixin Cai [ctb], Mark van der Laan [aut, cph, ths]

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NEWS

# Install 'hal9001' in R:
install.packages('hal9001', repos = c('https://tlverse.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tlverse/hal9001/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • hal_quotes - HAL9000 Quotes from "2001: A Space Odyssey"

On CRAN:

cross-validationlasso-regressionmachine-learning-algorithmsnonparametric-regression

10 exports 49 stars 3.52 score 28 dependencies 3 dependents 350 scripts 1.1k downloads

Last updated 10 months agofrom:92bd08de5e. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 18 2024
R-4.5-win-x86_64OKSep 18 2024
R-4.5-linux-x86_64OKSep 18 2024
R-4.4-win-x86_64OKSep 18 2024
R-4.4-mac-x86_64OKSep 18 2024
R-4.4-mac-aarch64OKSep 18 2024
R-4.3-win-x86_64OKSep 18 2024
R-4.3-mac-x86_64OKSep 18 2024
R-4.3-mac-aarch64OKSep 18 2024

Exports:apply_copy_mapenumerate_basisfit_halformula_halhmake_copy_mapmake_design_matrixmake_reduced_basis_mapSL.hal9001squash_hal_fit

Dependencies:abindassertthatclicodetoolsdata.tabledigestforeachfuturefuture.applyglmnetglobalsglueiteratorslatticelifecyclelistenvmagrittrMatrixorigamiparallellyRcppRcppEigenrlangshapestringistringrsurvivalvctrs

Fitting the Highly Adaptive Lasso with hal9001

Nima Hejazi, Jeremy Coyle, Rachael Phillips, Lars van der Laan

Rendered fromintro_hal9001.Rmdusingknitr::rmarkdownon Sep 18 2024.

Last update: 2023-11-08
Started: 2017-08-31