# Quantile Regression
This repository is for Python implementations of basic Quantile Regression routines.
## References
### Articles, books
[RK1] Roger Koenker,
[Quantile Regression](https://books.google.com/books/about/Quantile_Regression.html?id=hdkt7V4NXsgC),
Cambridge University Press, 2005.
[RK2] Roger Koenker,
["Quantile Regression in R: a vignette"](https://cran.r-project.org/web/packages/quantreg/vignettes/rq.pdf),
(2006),
[CRAN](https://cran.r-project.org/).
[AA1] Anton Antonov,
["A monad for Quantile Regression workflows"](https://github.com/antononcube/MathematicaForPrediction/blob/master/MarkdownDocuments/A-monad-for-Quantile-Regression-workflows.md),
(2018),
[MathematicaForPrediction at GitHub](https://github.com/antononcube/MathematicaForPrediction).
### Packages, paclets
[RKp1] Roger Koenker,
[`quantreg`](https://cran.r-project.org/web/packages/quantreg/index.html),
[CRAN](https://cran.r-project.org/).
[AAp1] Anton Antonov,
[Quantile Regression WL paclet](https://github.com/antononcube/WL-QuantileRegression-paclet),
(2014-2023),
[GitHub/antononcube](https://github.com/antononcube).
[AAp2] Anton Antonov,
[Monadic Quantile Regression WL paclet](https://github.com/antononcube/WL-MonadicQuantileRegression-paclet),
(2018-2024),
[GitHub/antononcube](https://github.com/antononcube).
[AAp3] Anton Antonov,
[`QuantileRegression`](https://resources.wolframcloud.com/FunctionRepository/resources/QuantileRegression),
(2019),
[Wolfram Function Repository](https://resources.wolframcloud.com/FunctionRepository/resources/QuantileRegression).
### Repositories
[AAr1] Anton Antonov,
[DSL::English::QuantileRegressionWorkflows in Raku](https://github.com/antononcube/Raku-DSL-English-QuantileRegressionWorkflows),
(2020),
[GitHub/antononcube](https://github.com/antononcube/Raku-DSL-English-QuantileRegressionWorkflows).
### Videos
[AAv1] Anton Antonov,
["Boston useR! QuantileRegression Workflows 2019-04-18"](https://www.youtube.com/watch?v=a_Dk25xarvE),
(2019),
[Anton Antonov at YouTube](https://www.youtube.com/@AAA4Prediction).
[AAv2] Anton Antonov,
["useR! 2020: How to simplify Machine Learning workflows specifications"](https://www.youtube.com/watch?v=b9Uu7gRF5KY),
(2020),
[R Consortium at YouTube](https://www.youtube.com/channel/UC_R5smHVXRYGhZYDJsnXTwg).
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