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GLM.jl is a Julia package for fitting linear and generalized linear models (GLMs) with a syntax and functionality familiar to users of R or other statistical environments. It is part of the JuliaStats ecosystem and is tightly integrated with StatsModels.jl for formula handling, and Distributions.jl for specifying error families. The package supports modeling through both formula-based (e.g. @formula) and matrix-based interfaces, allowing both high-level convenience and low-level control. Under the hood, GLM.jl separates the linear predictor and response objects, allowing flexible combinations of link functions, variance structures, and fitting methods.
Features
- Implements fitting for generalized linear models using formula or matrix inputs
- Supports specification of statistical families and link functions (e.g., negative binomial, logistic)
- Offers specialized methods like negative binomial model with θ estimation
- Part of the JuliaStats ecosystem, interoperating with StatsModels, Tables, and data frames
- Actively maintained with regular releases (latest v1.9.0, Sep 14 2023)
- Efficient with Julia’s performance and expressiveness for statistical tasks
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MIT LicenseFollow GLM.jl
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