{"id":23029759,"url":"https://github.com/antononcube/qrmon-r","last_synced_at":"2026-01-15T22:27:51.695Z","repository":{"id":71383425,"uuid":"166620234","full_name":"antononcube/QRMon-R","owner":"antononcube","description":"Quantile Regression workflows monad in R 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returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-12-15T14:17:01.009Z","updated_at":"2026-01-15T22:27:51.690Z","avatar_url":"https://github.com/antononcube.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Quantile Regression Monad in R \n\n\u003c!-- badges: start --\u003e\n[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)\n[![Codecov test coverage](https://codecov.io/gh/antononcube/QRMon-R/branch/master/graph/badge.svg)](https://codecov.io/gh/antononcube/QRMon-R?branch=master)\n[![R-CMD-check](https://github.com/antononcube/QRMon-R/workflows/R-CMD-check/badge.svg)](https://github.com/antononcube/QRMon-R/actions)\n\u003c!-- badges: end --\u003e\n  \nThis repository is for the R implementation of a software monad for Quantile Regression\nworkflows called **Q**uantile **R**egression **Mon**ad (QRMon).\n\nThe R-implementation follows the Mathematica `QRMon` package \n[\"MonadicQuantileRegression.m\"](https://github.com/antononcube/MathematicaForPrediction/blob/master/MonadicProgramming/MonadicQuantileRegression.m),\n[AAp1].\nThe Mathematica `QRMon` package is extensively documented with \n[\"A monad for Quantile Regression workflows\"](https://github.com/antononcube/MathematicaForPrediction/blob/master/MarkdownDocuments/A-monad-for-Quantile-Regression-workflows.md),\n[AA1].\n\nThe usage of this R implementation is explained in detail in the vignette \n[\"Rapid making of Quantile Regression workflows\"](https://htmlpreview.github.io/?https://github.com/antononcube/QRMon-R/blob/master/notebooks/rapid-making-of-qr-workflows.html).\n\nHere is how to install the package:\n\n    devtools::install_github(\"antononcube/QRMon-R\")\n\nHere is a workflow (pipeline) example:\n\n    qrmon \u003c-\n      QRMonUnit( dfTemperatureData ) %\u003e%\n      QRMonEchoDataSummary() %\u003e%\n      QRMonQuantileRegression( df = 16, degree = 3, probabilities = seq(0.1,0.9,0.2) ) %\u003e%\n      QRMonPlot( datePlotQ = TRUE, dateOrigin = \"1900-01-01\" )\n      \nThere is a Domain Specific Language (DSL) parser-interpreter implemented in [Raku](https://raku.org) \nthat can be used to generate `QRMon` code using natural language commands; see\n[AAr1].\n\n## References\n\n### Articles, books\n\n[RK1] Roger Koenker, \n[Quantile Regression](https://books.google.com/books/about/Quantile_Regression.html?id=hdkt7V4NXsgC), \nCambridge University Press, 2005.\n\n[RK2] Roger Koenker,\n[\"Quantile Regression in R: a vignette\"](https://cran.r-project.org/web/packages/quantreg/vignettes/rq.pdf),\n(2006),\n[CRAN](https://cran.r-project.org/).\n\n[AA1] Anton Antonov,\n[\"A monad for Quantile Regression workflows\"](https://github.com/antononcube/MathematicaForPrediction/blob/master/MarkdownDocuments/A-monad-for-Quantile-Regression-workflows.md),\n(2018),\n[MathematicaForPrediction at GitHub](https://github.com/antononcube/MathematicaForPrediction).\n\n### Packages\n\n[RKp1] Roger Koenker,\n[`quantreg`](https://cran.r-project.org/web/packages/quantreg/index.html),\n[CRAN](https://cran.r-project.org/).\n\n[AAp1] Anton Antonov,\n[Quantile Regression Mathematica package](https://github.com/antononcube/MathematicaForPrediction/blob/master/QuantileRegression.m),\n(2014),\n[MathematicaForPrediction at GitHub](https://github.com/antononcube/MathematicaForPrediction).\n\n[AAp2] Anton Antonov,\n[Monadic Quantile Regression Mathematica package](https://github.com/antononcube/MathematicaForPrediction/blob/master/MonadicProgramming/MonadicQuantileRegression.m),\n(2018),\n[MathematicaForPrediction at GitHub](https://github.com/antononcube/MathematicaForPrediction).\n\n[AAp3] Anton Antonov,\n[`QuantileRegression`](https://resources.wolframcloud.com/FunctionRepository/resources/QuantileRegression),\n(2019),\n[Wolfram Function Repository](https://resources.wolframcloud.com/FunctionRepository/resources/QuantileRegression).\n\n### Repositories\n\n[AAr1] Anton Antonov,\n[DSL::English::QuantileRegressionWorkflows in Raku](https://github.com/antononcube/Raku-DSL-English-QuantileRegressionWorkflows),\n(2020),\n[GitHub/antononcube](https://github.com/antononcube/Raku-DSL-English-QuantileRegressionWorkflows).\n\n### Videos\n\n[AAv1] Anton Antonov,\n[\"Boston useR! QuantileRegression Workflows 2019-04-18\"](https://www.youtube.com/watch?v=a_Dk25xarvE),\n(2019),\n[Anton Antonov at YouTube](https://www.youtube.com/channel/UC5qMPIsJeztfARXWdIw3Xzw).\n\n[AAv2] Anton Antonov,\n[\"useR! 2020: How to simplify Machine Learning workflows specifications\"](https://www.youtube.com/watch?v=b9Uu7gRF5KY),\n(2020),\n[R Consortium at YouTube](https://www.youtube.com/channel/UC_R5smHVXRYGhZYDJsnXTwg).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fantononcube%2Fqrmon-r","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fantononcube%2Fqrmon-r","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fantononcube%2Fqrmon-r/lists"}