| .Fitness_cpp | Computes the fitness used in the GA |
| boot.confint | Bootstrap confidence intervals |
| coef.LR | Estimated coefficients for the Lorenz Regression |
| coef.PLR | Estimated coefficients for the Penalized Lorenz Regression |
| confint.LR | Confidence intervals for the Lorenz Regression |
| confint.PLR | Confidence intervals for the Penalized Lorenz Regression |
| Data.Incomes | Simulated income data |
| Gini.coef | Concentration index of _y_ wrt _x_ |
| Lorenz.boot | Produces bootstrap-based inference for (penalized) Lorenz regression |
| Lorenz.curve | Concentration curve of _y_ with respect to _x_ |
| Lorenz.FABS | Solves the Penalized Lorenz Regression with Lasso penalty |
| Lorenz.GA | Estimates the parameter vector in Lorenz regression using a genetic algorithm |
| Lorenz.graphs | Graphs of concentration curves |
| Lorenz.Population | Defines the population used in the genetic algorithm |
| Lorenz.Reg | Undertakes a Lorenz regression |
| Lorenz.SCADFABS | Solves the Penalized Lorenz Regression with SCAD penalty |
| LorenzRegression | LorenzRegression : A package to estimate and interpret Lorenz regressions |
| plot.LR | Plots for the Unpenalized Lorenz Regression |
| plot.PLR | Plots for the Penalized Lorenz Regression |
| PLR.BIC | Determines the regularization parameter (lambda) in a PLR via optimization of an information criterion. |
| PLR.CV | Determines the regularization parameter (lambda) in a PLR via cross-validation |
| PLR.normalize | Re-normalizes the estimated coefficients of a penalized Lorenz regression |
| PLR.wrap | Wrapper for the 'Lorenz.SCADFABS' and 'Lorenz.FABS' functions |
| print.LR | Printing method for the Lorenz Regression |
| print.PLR | Printing method for the Penalized Lorenz Regression |
| Rearrangement.estimation | Estimates a monotonic regression curve via Chernozhukov et al (2009) |
| summary.LR | Summary for the Lorenz Regression |
| summary.PLR | Summary for the Penalized Lorenz Regression |