GLM
GLM.jl provides generalized linear models in Julia, with documentation and examples for the package.
About GLM
GLM.jl is a Julia package that implements linear and generalized linear models for statistical analysis. It is part of the JuliaStats ecosystem and includes official documentation and usage examples for users.
Key features
- Implements linear and generalized linear models in Julia
- Includes official documentation and usage examples
- Part of the JuliaStats statistical computing ecosystem
Best for: Users of the Julia programming language who need to fit linear or generalized linear models for statistical work.
Good for
- Has over 550 historical commits indicating active maintenance
- Includes CI status and test coverage tracking
- Has a registered DOI for academic citation
Watch out for
- Not open source software
GLM at a glance
- Website
- github.com/JuliaStats/GLM.jl
- Category
- Development › Developer Tools
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Not stated
- Language
- English
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
Guides for Developer Tools
GLM alternatives
Tools and sites you could use instead, ranked by how closely they match.
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Machine learning pipelines can use whylogs, an open-source library for logging data quality and model performance.
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Weights & Biases supports model training, fine tuning, and management from experimentation through production.
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statsmodels provides statistical modeling and econometrics tools in Python.
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GLMNet.jl is a Julia wrapper for fitting Lasso and Elastic Net generalized linear models using glmnet.
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GLM FAQ
What programming language is GLM.jl designed for?
Julia
What types of statistical models does GLM.jl support?
Linear and generalized linear models
Does GLM.jl provide resources for new users?
Yes, it includes documentation and examples
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