qqkrls: Quantile-on-Quantile Kernel Regularized Least Squares

Implements Quantile-on-Quantile Kernel-Based Regularized Least Squares (QQKRLS) as in Adebayo, Ozkan and Eweade (2024) <doi:10.1016/j.jclepro.2024.140832>. Combines Kernel-Based Regularized Least Squares (KRLS) of Hainmueller and Hazlett (2014) <doi:10.1093/pan/mpt019> with the Quantile-on-Quantile regression of Sim and Zhou (2015) <doi:10.1016/j.jbankfin.2015.01.013>: for each quantile theta of the independent variable the response is fit by KRLS on the corresponding sub-sample and the tau-quantile of the resulting pointwise marginal effects yields beta(theta, tau). Standard errors come from a paired bootstrap. Visualisations use the 'MATLAB' 'Parula' colour map by default.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: KRLS (≥ 1.0-0), plotly (≥ 4.0.0), stats, utils, grDevices
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2026-06-01
DOI: 10.32614/CRAN.package.qqkrls (may not be active yet)
Author: Merwan Roudane [aut, cre, cph], Tomiwa Sunday Adebayo [ctb] (Original QQKRLS methodology), Jens Hainmueller [ctb] (Original KRLS methodology), Chad Hazlett [ctb] (Original KRLS methodology)
Maintainer: Merwan Roudane <merwanroudane920 at gmail.com>
BugReports: https://github.com/merwanroudane/qqkrlsr/issues
License: GPL-3
URL: https://github.com/merwanroudane/qqkrlsr
NeedsCompilation: no
Citation: qqkrls citation info
Materials: NEWS
CRAN checks: qqkrls results

Documentation:

Reference manual: qqkrls.html , qqkrls.pdf

Downloads:

Package source: qqkrls_1.0.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): qqkrls_1.0.0.tgz, r-oldrel (arm64): qqkrls_1.0.0.tgz, r-release (x86_64): qqkrls_1.0.0.tgz, r-oldrel (x86_64): qqkrls_1.0.0.tgz

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