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
Categories
LibrariesLicense
MIT LicenseFollow GLM.jl
Other Useful Business Software
Enterprise-grade ITSM, for every business
Freshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of GLM.jl!