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mqqr  

Multivariate Quantile-on-Quantile Regression
View on CRAN: Click here


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

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

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



Attach the package and use:
library("mqqr")
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 Multivariate Quantile-on-Quantile Regression (m-QQR) of Sinha, Ghosh, Hussain, Nguyen and Das (2023) <doi:10.1016/j.eneco.2023.107021>, extending the bivariate Quantile-on-Quantile regression of Sim and Zhou (2015) <doi:10.1016/j.jbankfin.2015.01.013> to include exogenous moderators and controls with optional interaction terms. For each pair of quantile levels (theta of the response and tau of the regressor) the package fits a locally-weighted quantile regression of y on the principal regressor x, a lagged dependent variable, moderators Z and the x*Z interaction terms, using Gaussian kernel weights on the empirical cumulative distribution function (CDF) distance. Bootstrap standard errors and Koenker-Machado pseudo R-squared are reported. Visualisations include 'MATLAB'-style 'Parula' and 'Jet' 3D surfaces, heatmaps and contour plots through 'plotly'.
How to cite:
Merwan Roudane (2026). mqqr: Multivariate Quantile-on-Quantile Regression. R package version 1.0.0, https://cran.r-project.org/web/packages/mqqr. Accessed 26 Jun. 2026.
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