Density-Free RIF Decompositions for Unconditional Expectiles R package rifexpectile version 0.1.1 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>. Software Depends: R (>= 4.1.0) Imports: stats, graphics Suggests: testthat (>= 3.0.0), knitr, rmarkdown, wooldridge Abdoul Aziz Ndoye <abdoulaziz1.ndoye@gmail.com> Comprehensive R Archive Network (CRAN) Abdoul Aziz Ndoye [aut, cre] MIT + file LICENSE (https://CRAN.R-project.org/package=rifexpectile/LICENSE) 2026-08-31 application/tgz https://CRAN.R-project.org/package=rifexpectile doi:10.32614/CRAN.package.rifexpectile