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rifexpectile  

Density-Free RIF Decompositions for Unconditional Expectiles
View on CRAN: Click here


Download and install rifexpectile package within the R console
Install from CRAN:
install.packages("rifexpectile")

Install from Github:
library("remotes")
install_github("cran/rifexpectile")

Install by package version:
library("remotes")
install_version("rifexpectile", "0.1.1")



Attach the package and use:
library("rifexpectile")
Maintained by
Abdoul Aziz Ndoye
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-08-31
Latest Update: 2026-08-31
Description:
Implements a density-free recentered influence function (RIF) regression framework for unconditional expectiles, and embeds it in a two-sample Oaxaca-Blinder decomposition indexed continuously by the expectile level. Unlike quantile-based RIF decompositions, which require estimating an inverse density term at each quantile, the expectile RIF depends only on primitive moments of the outcome distribution and requires no density estimation, no bandwidth selection, and no kernel smoothing. The package provides expectile estimation by iteratively reweighted least squares, closed-form RIF construction, two-sample composition/structure decomposition across a grid of expectile levels, bootstrap-based inference, and plotting methods. The underlying methodology is described in Ndoye (2025), "Semi-Nonparametric Expectile RIF Regression for Distributional Decomposition," presented at the 2025 World Congress of the Econometric Society, Seoul, Korea, <https://www.econometricsociety.org/regional-activities/conference-papers/view/282/943>.
How to cite:
Abdoul Aziz Ndoye (2026). rifexpectile: Density-Free RIF Decompositions for Unconditional Expectiles. R package version 0.1.1, https://cran.r-project.org/web/packages/rifexpectile. Accessed 03 Oct. 2026.
Previous versions and publish date:
(2026-09-01 00:01), 0.1.0 (2026-08-30 11:10)
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Maintainer: Lu Mao (view profile)

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