Scalable and user friendly neural 🧠 forecasting algorithms.

🎓 Tidy tools for academics

Flexible Statistics and Data Analysis (FSDA) extends MATLAB for a robust analysis of data sets affected by different sources of heterogeneity. It is open source software licensed under the European Union Public Licence (EUPL). FSDA is a joint project by the University of Parma and the Joint Research Centre of the European Commission.

Generalized Linear Regressions Models (penalized regressions, robust regressions, ...)

A Julia package for robust regressions using M-estimators and quantile regressions

Robust Regression for arbitrary non-linear functions

Robust locally weighted multiple regression in Python

a c++ library with statistical machine learning algorithms for linear and non-linear robust regression that can be used with python.

Robust regression algorithm that can be used for explaining black box models (Python implementation)

Robust regression algorithm that can be used for explaining black box models (R implementation)

Different type of solvers to solve systems of nonlinear equations

Classification of Alan Miller's Fortran codes for statistics and numerical methods

Weighted BACON algorithms

Unveiling the Art of Stock Market Prognostication through Regression Algorithms. Delve into our research exploring the power of machine learning in predicting market trends. Discover the secrets behind top regression models like Linear, Robust, Ridge, and Lasso Regression. Unravel the complexities of the market with data-driven precision.

Robust shape fitting

Simple 1d robust regression with huber loss in the case of anomalies / outliers

universal rank-order method to analyze noisy data

Random Sample Consensus (RANSAC) Python Implementation

DecoR: Deconfounding Time Series with Robust Regression

Fortran 90 library of John Burkardt for regression using least-squares and other criteria, based on Spaeth's codes