hendersontrent/GeneralizedAdditiveModels.jl
Fit, evaluate, and visualise generalised additive models (GAMs) in native Julia
This tool helps statisticians and data scientists build flexible regression models that can capture complex, non-linear relationships in their data. You provide your dataset and specify the relationships between variables using a formula, and it outputs a generalized additive model (GAM) that can be used for predictions and insights. It's designed for quantitative analysts working with Julia.
Use this if you need to model relationships that aren't strictly linear and want to understand how multiple factors influence an outcome without assuming a fixed parametric form.
Not ideal if you primarily work in R and are already deeply integrated with `mgcv`, or if you need the full, sophisticated functionality of established statistical packages.
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Language
Julia
License
MIT
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Last pushed
Nov 16, 2025
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