Welcome to lpspline Documentation!

Getting Started

lpspline is a specialized convex regression package enabling the generation of constrained additive spline models via robust convex optimization. The package will provide a user-friendly interface for the generation of constrained additive spline models. Optimizer is based on cvxpy

Installation

pip install lpspline

Dependencies

The package requires the following dependencies:

polars
cvxpy
pimpmyplot

They will be automatically installed when installing lpspline.

Contact

For questions or suggestions, please contact me at maioliandrea0@gmail.com

My GitHub: clarkmaio

My Page: https://clarkmaio.github.io/

Navigation:

• Quickstart
  • Installation
  • Basic Usage
  • LpRegressor
  • Fit and predict
  • Summary
  • Saving and Loading
  • Diagnostics
• Demo
  • Standard regression
  • by splines
  • Constraints
  • Link functions
• API reference
  • lpspline.spline
  • lpspline.constraints
  • lpspline.penalties
  • lpspline.optimizer
  • lpspline.viz
  • lpspline.datasets