robust-statistics

Enhancing `{ggplot2}` plots with statistical analysis 📊🎨📣

📊 Computation and processing of models' parameters

Tidy Dataframes and Expressions with Statistical Details 📉 📜🔣✅

Robust freeform surface modeling from user 2d sketches.

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.

This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design for designing randomized paired geo experiments.

Python PyTorch (GPU) and NumPy (CPU)-based port of Févotte and Dobigeon's robust-NMF algorithm appearing in "Nonlinear hyperspectral unmixing with robust nonnegative matrix factorization."

Robustats is a Python library for high-performance computation of robust statistical estimators.

📦 Non-parametric Causal Effects of Feasible Interventions Based on Modified Treatment Policies 🔮

Solve many kinds of least-squares and matrix-recovery problems

Robust statistics in Python

Defending Against Backdoor Attacks Using Robust Covariance Estimation

Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning

Robust Gaussian Process with Iterative Trimming

Neural Networks package for R with a fast C++ back-end and special support for unsupervised anomaly detection using autoencoders

📦 🎲 R/txshift: Efficient Estimation of the Causal Effects of Stochastic Interventions, with Corrections for Outcome-Dependent Sampling

Doubly-Robust and Efficient Estimators for Survival and Ordinal Outcomes in RCTs Without Proportional Hazards or Odds Assumptions 💊

Robust particle filter based on dynamic averaging of multiple noise models

This project contains the code for the paper accepted at NeurIPS 2020 - Robust Meta-learning for Mixed Linear Regression with Small Batches.

This is an open source library that can help to autofocus telescopes. The library can analyze a small series of defocused images in fourier space, from which the correct focus point can be interpolated. The library uses various robust statistical outlier detection methods. It is currently used in Astro Photography tool (APT) https://www.astrophotography.app/

Official implementation of the paper: "REGroup: Rank-aggregating Ensemble of Generative Classifiers for Robust Predictions", IEEE WACV, 2022

robust optimization

Robust Chauvenet Rejection: RCR is advanced, but easy to use, outlier rejection.

MATLAB pipeline for easy-to-program automated pre-processing of electroencephalogram (EEG) data using independent component analysis and statistically-robust detection of artifacts.

Robust Sure Independence Screening using the Minimum Density Power Divergence Estimators

RStudio project utilizing various statistical methods to replicate and diagnose the findings of Appel and Loyle from their study on post-conflict justice and foreign direct investment.

R Package implementing the Penalized Elastic Net S- and MM-Estimator for Linear Regression

Various numerical routines in C and C++