Package: LassoBacktracking 1.1

LassoBacktracking: Modelling Interactions in High-Dimensional Data with Backtracking

Implementation of the algorithm introduced in Shah, R. D. (2016) <https://www.jmlr.org/papers/volume17/13-515/13-515.pdf>. Data with thousands of predictors can be handled. The algorithm performs sequential Lasso fits on design matrices containing increasing sets of candidate interactions. Previous fits are used to greatly speed up subsequent fits, so the algorithm is very efficient.

Authors:Rajen Shah [aut, cre]

LassoBacktracking_1.1.tar.gz
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LassoBacktracking.pdf |LassoBacktracking.html✨
LassoBacktracking/json (API)

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

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

1.00 score 1 stars 3 scripts 217 downloads 2 exports 3 dependencies

Last updated 2 years agofrom:698fffffe4. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 25 2025
R-4.5-win-x86_64OKJan 25 2025
R-4.5-linux-x86_64OKJan 25 2025
R-4.4-win-x86_64OKJan 25 2025
R-4.4-mac-x86_64OKJan 25 2025
R-4.4-mac-aarch64OKJan 25 2025
R-4.3-win-x86_64OKJan 25 2025
R-4.3-mac-x86_64OKJan 25 2025
R-4.3-mac-aarch64OKJan 25 2025

Exports:cvLassoBTLassoBT

Dependencies:latticeMatrixRcpp