The LorenzRegression package proposes a toolbox to estimate, produce inference on and interpret Lorenz regressions. These regressions are used to determine the explanatory power of a set of covariates on the inequality of a response variable.
You can install the released version of LorenzRegression from CRAN with:
install.packages("LorenzRegression")
You can install the development version of this package from GitHub with:
# install.packages("devtools")
# devtools::install_github("AlJacq/LorenzRegression")
install.packages("LorenzRegression", repos = c('https://aljacq.r-universe.dev', 'https://cloud.r-project.org'))
Function Structure Overhaul: Lorenz.Reg now acts as a wrapper
for fitting functions Lorenz.GA, Lorenz.FABS, and
Lorenz.SCADFABS, returning objects of class "LR" or "PLR" with
designated methods.
Enhanced Bootstrap and CV: Lorenz.boot performs bootstrap
calculations and out-of-bag score computation, while PLR.CV handles
cross-validation for tuning parameter selection.
Methods: New methods fitted, explainedIneq, and autoplot for
"LR" and "PLR" objects. Method availability is documented in the
Lorenz.Reg help page with individual help pages for each method.