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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> 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:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=LorenzRegression
to link to this page.
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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