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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>.

Version: 1.0.0
Depends: R (≥ 3.3.1)
Imports: stats, ggplot2, parallel, doParallel, foreach, MASS, GA, locpol, Rearrangement, Rcpp (≥ 0.11.0), knitr
LinkingTo: Rcpp, RcppArmadillo
Suggests: rmarkdown
Published: 2023-02-28
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
CRAN checks: LorenzRegression results

Documentation:

Reference manual: LorenzRegression.pdf

Downloads:

Package source: LorenzRegression_1.0.0.tar.gz
Windows binaries: r-devel: LorenzRegression_1.0.0.zip, r-release: LorenzRegression_1.0.0.zip, r-oldrel: LorenzRegression_1.0.0.zip
macOS binaries: r-release (arm64): LorenzRegression_1.0.0.tgz, r-oldrel (arm64): LorenzRegression_1.0.0.tgz, r-release (x86_64): LorenzRegression_1.0.0.tgz, r-oldrel (x86_64): LorenzRegression_1.0.0.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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