https://github.com/antononcube/qrmon-r

Quantile Regression workflows monad in R
https://github.com/antononcube/qrmon-r

Last synced: 6 months ago
JSON representation

Quantile Regression workflows monad in R

• Host: GitHub
• URL: https://github.com/antononcube/qrmon-r
• Owner: antononcube
• License: gpl-3.0
• Created: 2019-01-20T03:46:26.000Z (over 7 years ago)
• Default Branch: master
• Last Pushed: 2021-07-25T13:10:49.000Z (almost 5 years ago)
• Last Synced: 2025-04-02T20:33:25.210Z (over 1 year ago)
• Language: HTML
• Size: 706 KB
• Stars: 1
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# Quantile Regression Monad in R 

[![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)

[![Codecov test coverage](https://codecov.io/gh/antononcube/QRMon-R/branch/master/graph/badge.svg)](https://codecov.io/gh/antononcube/QRMon-R?branch=master)

[![R-CMD-check](https://github.com/antononcube/QRMon-R/workflows/R-CMD-check/badge.svg)](https://github.com/antononcube/QRMon-R/actions)

  

This repository is for the R implementation of a software monad for Quantile Regression

workflows called **Q**uantile **R**egression **Mon**ad (QRMon).

The R-implementation follows the Mathematica `QRMon` package 

["MonadicQuantileRegression.m"](https://github.com/antononcube/MathematicaForPrediction/blob/master/MonadicProgramming/MonadicQuantileRegression.m),

[AAp1].

The Mathematica `QRMon` package is extensively documented with 

["A monad for Quantile Regression workflows"](https://github.com/antononcube/MathematicaForPrediction/blob/master/MarkdownDocuments/A-monad-for-Quantile-Regression-workflows.md),

[AA1].

The usage of this R implementation is explained in detail in the vignette 

["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).

Here is how to install the package:

    devtools::install_github("antononcube/QRMon-R")

Here is a workflow (pipeline) example:

    qrmon <-

      QRMonUnit( dfTemperatureData ) %>%

      QRMonEchoDataSummary() %>%

      QRMonQuantileRegression( df = 16, degree = 3, probabilities = seq(0.1,0.9,0.2) ) %>%

      QRMonPlot( datePlotQ = TRUE, dateOrigin = "1900-01-01" )

      

There is a Domain Specific Language (DSL) parser-interpreter implemented in [Raku](https://raku.org) 

that can be used to generate `QRMon` code using natural language commands; see

[AAr1].

## 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

[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 Mathematica package](https://github.com/antononcube/MathematicaForPrediction/blob/master/QuantileRegression.m),

(2014),

[MathematicaForPrediction at GitHub](https://github.com/antononcube/MathematicaForPrediction).

[AAp2] Anton Antonov,

[Monadic Quantile Regression Mathematica package](https://github.com/antononcube/MathematicaForPrediction/blob/master/MonadicProgramming/MonadicQuantileRegression.m),

(2018),

[MathematicaForPrediction at GitHub](https://github.com/antononcube/MathematicaForPrediction).

[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/channel/UC5qMPIsJeztfARXWdIw3Xzw).

[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).