Gammy documentation

A Generalized additive model is a predictive mathematical model defined as a sum of terms that are calibrated (fitted) with observation data. This package provides a hopefully pleasant interface for configuring and fitting such models. Bayesian interpretation of model parameters and a minimalist set of features are promoted.

The main idea behind Gammy is to enable quick coding of the solution to most of the day-to-day lightweight linear model estimation problems.

Contents

• Installation
• Key features
  • Intuitive interface
  • Fitting and predicting
  • Formula collection
  • Bayesian statistics
  • Multivariate terms
  • Gaussian processes
  • Spline regression
  • Non-linear manifold regression
• Backlog ideas
• API Reference
  • gammy.arraymapper
  • gammy.formulae
  • gammy.models
  • gammy.plot
  • gammy.utils

Other Python projects with GAM functionalities

• PyGAM

• Statsmodels

• BlinPy