Uniform Error Estimator (UEE): minimax / Chebyshev regression with diagnostics and bootstrap inference
Project description
Uniform Error Estimator
Uniform Error Estimator (UEE) is a Python implementation of minimax (Chebyshev / L∞) regression:
[ \min_eta \max_t |y_t - X_t eta| ]
- Pypi package: 'uee'
- Source repository: 'uniform-error-estimator'
The package provides:
- a clean estimator API (
UEE) - rich fit diagnostics (
UEEResults) - bootstrap inference
- optional intercept handling
- active-set and dual-weight diagnostics
Installation
pip install uee
Quick start
import numpy as np
from uee import UEE
X = np.array(\\\[\\\[1.0], \\\[2.0], \\\[3.0], \\\[4.0]])
y = np.array(\\\[2.1, 4.0, 5.9, 8.2])
model = UEE(fit\\\_intercept=True)
res = model.fit(X, y)
print(res.intercept\\\_)
print(res.coef\\\_)
print(res.max\\\_abs\\\_error)
print(res.active\\\_set)
Package status
This repository/package is the maintained, packaged version of UEE. If you previously exposed a raw script or notebook implementation, update that legacy location to point users here.
License
MIT. See LICENSE.
Project details
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