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: 2.2.0 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: 2025-06-27 DOI: 10.32614/CRAN.package.LorenzRegression Author: Alexandre Jacquemain [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> BugReports: https://github.com/AlJacq/LorenzRegression/issues License: GPL-3 URL: https://github.com/AlJacq/LorenzRegression NeedsCompilation: yes Materials: README NEWS CRAN checks: LorenzRegression results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=LorenzRegression to link to this page.
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