qqkrls
1.0.0Quantile-on-Quantile Kernel Regularized Least Squares
Overview
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.
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Health
- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-06-027 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 81%
- Return-value docs
- 100%
- References docs
- 20%
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Checks run against github.com/merwanroudane/qqkrlsr on 2026-07-19.
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Code & Tests
People & History
1 release. R releases are shown for context.
- 1.0.0Latest2026-06-01 · current release
- RR 4.6.0 released · 2026-04-24
Package metadata
- First published
- 2026-06-01
- Total releases
- 1 / 1 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Download size
- not tracked yet
- Installed size
- not tracked yet
- With dependencies
- not tracked yet