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rare

Linear Model with Tree-Based Lasso Regularization for Rare Features

Implementation of an alternating direction method of multipliers algorithm for fitting a linear model with tree-based lasso regularization, which is proposed in Algorithm 1 of Yan and Bien (2020) <doi:10.1080/01621459.2020.1796677>. The package allows efficient model fitting on the entire 2-dimensional regularization path for large datasets. The complete set of functions also makes the entire process of tuning regularization parameters and visualizing results hassle-free.

Versions across snapshots

VersionRepositoryFileSize
0.1.2 rolling linux/jammy R-4.5 rare_0.1.2.tar.gz 296.9 KiB
0.1.2 rolling linux/noble R-4.5 rare_0.1.2.tar.gz 300.5 KiB
0.1.2 rolling source/ R- rare_0.1.2.tar.gz 2.1 MiB
0.1.2 latest linux/jammy R-4.5 rare_0.1.2.tar.gz 296.9 KiB
0.1.2 latest linux/noble R-4.5 rare_0.1.2.tar.gz 300.5 KiB
0.1.2 latest source/ R- rare_0.1.2.tar.gz 2.1 MiB
0.1.2 2026-04-26 source/ R- rare_0.1.2.tar.gz 2.1 MiB
0.1.2 2026-04-23 source/ R- rare_0.1.2.tar.gz 2.1 MiB
0.1.2 2026-04-09 windows/windows R-4.5 rare_0.1.2.zip 614.9 KiB
0.1.1 2025-04-20 source/ R- rare_0.1.1.tar.gz 2.5 MiB

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