Package: LorenzRegression 2.1.0

Alexandre Jacquemain

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>.

Authors:Alexandre Jacquemain [aut, cre], Xingjie Shi [ctb]

LorenzRegression_2.1.0.tar.gz
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LorenzRegression.pdf |LorenzRegression.html✨
LorenzRegression/json (API)
NEWS

# Install 'LorenzRegression' in R:
install.packages('LorenzRegression', repos = c('https://aljacq.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/aljacq/lorenzregression/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

3.81 score 306 downloads 13 exports 63 dependencies

Last updated 1 months agofrom:a4fe6c45d1. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 10 2024
R-4.5-win-x86_64OKNov 10 2024
R-4.5-linux-x86_64OKNov 10 2024
R-4.4-win-x86_64OKNov 10 2024
R-4.4-mac-x86_64OKNov 10 2024
R-4.4-mac-aarch64OKNov 10 2024
R-4.3-win-x86_64OKNov 10 2024
R-4.3-mac-x86_64OKNov 10 2024
R-4.3-mac-aarch64OKNov 10 2024

Exports:diagnostic.PLRGini.coefineqExplainedLorenz.bootLorenz.boot.combineLorenz.curveLorenz.FABSLorenz.GALorenz.graphsLorenz.RegLorenz.SCADFABSPLR.CVRearrangement.estimation

Dependencies:bootclicodetoolscolorspacecpp11crayondigestdoParalleldplyrfansifarverforeachfurrrfutureGAgenericsggplot2globalsgluegtablehardhatisobanditeratorslabelinglatticelifecyclelistenvlocpolmagrittrMASSMatrixMatrixModelsmgcvmunsellnlmeparallellyparsnippillarpkgconfigprettyunitspurrrquantregR6RColorBrewerRcppRcppArmadilloRearrangementrlangrsamplescalessliderSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewarpwithr

Readme and manuals

Help Manual

Help pageTopics
Plots for the Lorenz regressionautoplot.LR autoplot.LR_boot plot.LR plot.LR_boot
Plots for the penalized Lorenz regressionautoplot.PLR autoplot.PLR_boot autoplot.PLR_cv plot.PLR plot.PLR_boot plot.PLR_cv
Estimated coefficients for the Lorenz regressioncoef.LR coef.LR_boot
Estimated coefficients for the penalized Lorenz regressioncoef.PLR coef.PLR_boot coef.PLR_cv
Confidence intervals for the Lorenz regressionconfint.LR confint.LR_boot
Confidence intervals for the penalized Lorenz regressionconfint.PLR confint.PLR_boot confint.PLR_cv
Simulated income dataData.Incomes
Diagnostic for the penalized Lorenz regressiondiagnostic.PLR
Concentration index of _y_ with respect to _x_Gini.coef
Retrieve a measure of explained inequality from a modelineqExplained
Explained inequality metrics for the Lorenz regressionineqExplained.LR ineqExplained.LR_boot
Explained inequality metrics for the penalized Lorenz regressionineqExplained.PLR ineqExplained.PLR_boot ineqExplained.PLR_cv
Bootstrap for the (penalized) Lorenz regressionLorenz.boot
Combines bootstrap Lorenz regressionsLorenz.boot.combine
Concentration curve of _y_ with respect to _x_Lorenz.curve
Estimates the parameter vector in a penalized Lorenz regression with lasso penaltyLorenz.FABS
Estimates the parameter vector in Lorenz regression using a genetic algorithmLorenz.GA
Graphs of concentration curvesLorenz.graphs
Fits a Lorenz regressionLorenz.Reg
Estimates the parameter vector in a penalized Lorenz regression with SCAD penaltyLorenz.SCADFABS
Cross-validation for penalized Lorenz regressionPLR.CV
Prediction and fitted values for the Lorenz regressionfitted.LR fitted.LR_boot predict.LR predict.LR_boot
Prediction and fitted values for the penalized Lorenz regressionfitted.PLR fitted.PLR_boot fitted.PLR_cv predict.PLR predict.PLR_boot predict.PLR_cv
Printing method for the Lorenz regressionprint.LR print.LR_boot
Printing method for the penalized Lorenz regressionprint.PLR print.PLR_boot print.PLR_cv
Printing method for the summary of a Lorenz regressionprint.summary.LR print.summary.LR_boot
Printing method for the summary of a penalized Lorenz regressionprint.summary.PLR print.summary.PLR_boot print.summary.PLR_cv
Estimates a monotonic regression curve via Chernozhukov et al (2009)Rearrangement.estimation
Summary for the Lorenz regressionsummary.LR summary.LR_boot
Summary for the penalized Lorenz regressionsummary.PLR summary.PLR_boot summary.PLR_cv