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qqkrls  

Quantile-on-Quantile Kernel Regularized Least Squares
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("qqkrls", "1.0.0")



Attach the package and use:
library("qqkrls")
Maintained by
Merwan Roudane
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-01
Latest Update: 2026-06-01
Description:
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.
How to cite:
Merwan Roudane (2026). qqkrls: Quantile-on-Quantile Kernel Regularized Least Squares. R package version 1.0.0, https://cran.r-project.org/web/packages/qqkrls. Accessed 04 Oct. 2026.
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