LorenzRegression: Lorenz and Penalized Lorenz Regressions

Inference for the Lorenz and penalized Lorenz regressions. More broadly, the package proposes functions to assess inequality and graphically represent it. The Lorenz Regression procedure is introduced in Heuchenne and Jacquemain (2022) <doi:10.1016/j.csda.2021.107347> and in Jacquemain, A., C. Heuchenne, and E. Pircalabelu (2024) <doi:10.1214/23-EJS2200>.

Version: 2.3.0
Depends: R (≥ 3.3.1)
Imports: stats, ggplot2, parsnip, boot, rsample, parallel, doParallel, foreach, MASS, GA, Rearrangement, progress, Rcpp (≥ 0.11.0)
LinkingTo: Rcpp, RcppArmadillo
Suggests: rmarkdown
Published: 2025年08月20日
Author: Alexandre Jacquemain ORCID iD [aut, cre], Xingjie Shi [ctb] (Author of an R implementation of the FABS algorithm available at https://github.com/shuanggema/Fabs, of which function Lorenz.FABS is derived)
Maintainer: Alexandre Jacquemain <aljacquemain at gmail.com>
License: GPL-3
NeedsCompilation: yes
Materials: README, NEWS

Documentation:

Downloads:

Windows binaries: r-devel: LorenzRegression_2.3.0.zip, r-release: LorenzRegression_2.3.0.zip, r-oldrel: LorenzRegression_2.3.0.zip
macOS binaries: r-release (arm64): LorenzRegression_2.3.0.tgz, r-oldrel (arm64): LorenzRegression_2.3.0.tgz, r-release (x86_64): LorenzRegression_2.3.0.tgz, r-oldrel (x86_64): LorenzRegression_2.3.0.tgz

Reverse dependencies:

Reverse imports: glorenz

Linking:

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