https://github.com/ararslan/betaregression.jl

Regression models for beta distributed responses in Julia
https://github.com/ararslan/betaregression.jl

beta-distribution beta-regression julia regression-models statistics

Last synced: 10 days ago
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Regression models for beta distributed responses in Julia

• Host: GitHub
• URL: https://github.com/ararslan/betaregression.jl
• Owner: ararslan
• License: mit
• Created: 2022-05-31T16:13:02.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-05-07T16:08:13.000Z (6 months ago)
• Last Synced: 2024-10-15T18:32:54.543Z (22 days ago)
• Topics: beta-distribution, beta-regression, julia, regression-models, statistics
• Language: Julia
• Homepage:
• Size: 312 KB
• Stars: 7
• Watchers: 3
• Forks: 2
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# BetaRegression.jl

[![Build Status](https://github.com/ararslan/BetaRegression.jl/workflows/CI/badge.svg)](https://github.com/ararslan/BetaRegression.jl/actions?query=workflow%3ACI+branch%3Amain)

[![Code Coverage](http://codecov.io/github/ararslan/BetaRegression.jl/coverage.svg?branch=main)](http://codecov.io/github/ararslan/BetaRegression.jl?branch=main)

[![](https://img.shields.io/badge/docs-stable-blue.svg)](https://ararslan.github.io/BetaRegression.jl/stable)

This package provides regression modeling functionality for continuous,

[beta-distributed](https://en.wikipedia.org/wiki/Beta_distribution) responses with values

in the open interval (0, 1).

Models of this kind are particularly useful when modeling rates and proportions, which

naturally fall within the unit interval (or can be trivially transformed to do so).

In concept, beta regression models are quite similar to generalized linear models (GLMs),

though they are not actually GLMs due to the parameterization used for the beta

distribution.

However, users familiar with [GLM.jl](https://github.com/JuliaStats/GLM.jl) will likely

find that this package feels familiar in its interface and behavior.

See the package documentation for more information, including usage examples.

## References

Ferrari, S. & Cribari-Neto, F. (2004). Beta regression for modelling rates and proportions.

_Journal of Applied Statistics_, 31(7), 799–815.

https://doi.org/10.1080/0266476042000214501