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LorenzRegression

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.

Installation

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")

What’s new

LorenzRegression 2.0.0

  • 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.

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Version

Install

install.packages('LorenzRegression')

Monthly Downloads

265

Version

2.2.0

License

GPL-3

Issues

Pull Requests

Stars

Forks

Maintainer

Alexandre Jacquemain

Last Published

June 27th, 2025

Functions in LorenzRegression (2.2.0)

Lorenz.curve

Concentration curve of y with respect to x
Lorenz.ga.call

Call to the genetic algorithm for the Lorenz regression
Rearrangement.estimation

Estimates a monotonic regression curve via Chernozhukov et al (2009)
PLR.fit

Penalized Lorenz Regression Fit Function
PLR.scores

Computes Gini scores for the Penalized Lorenz Regression
PLR.normalize

Re-normalizes the estimated coefficients of a penalized Lorenz regression
Lorenz.graphs

Graphs of concentration curves
LorenzRegression-package

LorenzRegression : A package to estimate and interpret Lorenz regressions
PLR.BIC

Determines the regularization parameter (lambda) in a PLR via optimization of an information criterion.
diagnostic.PLR

Diagnostic for the penalized Lorenz regression
.frac_rank_cpp

Computes fractional ranks
ineqExplained.LR

Explained inequality metrics for the Lorenz regression
.Fitness_cpp

Computes the fitness used in the GA
predict.LR

Prediction and fitted values for the Lorenz regression
predict.PLR

Prediction and fitted values for the penalized Lorenz regression
summary.LR

Summary for the Lorenz regression
ineqExplained.PLR

Explained inequality metrics for the penalized Lorenz regression
runif_seed

Generates a sample of uniform random variables with a specific seed
ineqExplained.lm

Explained inequality metrics for (generalized) linear models
confint.LR_boot

Confidence intervals for the Lorenz regression
confint.PLR_boot

Confidence intervals for the penalized Lorenz regression
ineqExplained

Retrieve a measure of explained inequality from a model
residuals.PLR

Residuals for the penalized Lorenz regression
residuals.LR

Residuals for the Lorenz regression
coef.LR

Estimated coefficients for the Lorenz regression
print.LR

Printing method for the Lorenz regression
PLR.CV

Cross-validation for penalized Lorenz regression
summary.PLR

Summary for the penalized Lorenz regression
model_matrix_PLR

Design matrix in the Penalized Lorenz Regression
print.summary.LR

Printing method for the summary of a Lorenz regression
coef.PLR

Estimated coefficients for the penalized Lorenz regression
print.PLR

Printing method for the penalized Lorenz regression
autoplot.LR

Plots for the Lorenz regression
autoplot.PLR

Plots for the penalized Lorenz regression
print.summary.PLR

Printing method for the summary of a penalized Lorenz regression
Lorenz.GA

Estimates the parameter vector in Lorenz regression using a genetic algorithm
Lorenz.boot

Bootstrap for the (penalized) Lorenz regression
Lorenz.Population

Defines the population used in the genetic algorithm
Data.Incomes

Simulated income data
Lorenz.SCADFABS

Estimates the parameter vector in a penalized Lorenz regression with SCAD penalty
Gini.coef

Concentration index of y with respect to x
Lorenz.FABS

Estimates the parameter vector in a penalized Lorenz regression with lasso penalty
Lorenz.Reg

Fits a Lorenz regression
Lorenz.boot.combine

Combines bootstrap Lorenz regressions
Lorenz.Suggestions

Defines the suggestions used in the genetic algorithm