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:	2.1.0
Depends:	R (≥ 3.3.1)
Imports:	stats, ggplot2, scales, parsnip, boot, rsample, parallel, doParallel, foreach, MASS, GA, locpol, Rearrangement, Rcpp (≥ 0.11.0)
LinkingTo:	Rcpp, RcppArmadillo
Suggests:	rmarkdown
Published:	2024-10-11
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:

Reference manual:

LorenzRegression.pdf

Downloads:

Package source:	LorenzRegression_2.1.0.tar.gz
Windows binaries:	r-devel: LorenzRegression_2.1.0.zip, r-release: LorenzRegression_2.1.0.zip, r-oldrel: LorenzRegression_2.1.0.zip
macOS binaries:	r-release (arm64): LorenzRegression_2.1.0.tgz, r-oldrel (arm64): LorenzRegression_2.1.0.tgz, r-release (x86_64): LorenzRegression_2.1.0.tgz, r-oldrel (x86_64): LorenzRegression_2.1.0.tgz
Old sources:	LorenzRegression archive

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