FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.

FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.

Feature transformation is a technique in machine learning that changes the way features are represented in order to improve the performance of machine learning algorithms. This can be done by transforming the features to a different scale, removing outliers, or creating new features from existing

The ConfidenceEllipse package provides functions for computing the coordinate points of confidence ellipses and ellipsoids for a given bivariate and trivariate dataset, at user-defined confidence level.

Simple multiverse analysis simulations, visualizations and inference techniques.

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

Robust locally weighted multiple regression in Python

A robust deterministic affine-equivariant algorithm for multivariate location and scatter

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

This is an R package I developed to estimate the causal effect of an exposure on an outcome when there's invalid instruments and large proportions of contamination.

This is an open source library that can be used to autofocus telescopes. It uses a novel algorithm based on robust statistics. For a preprint, see https://arxiv.org/abs/2201.12466 .The library is currently used in Astro Photography tool (APT) https://www.astrophotography.app/

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.

Code of the paper The Robust Randomized Quasi Monte Carlo method, applications to integrating singular functions by E. Gobet M. Lerasle and D. Métivier

This repository provides a unified framework to perform Optimization experiments across Stochastic, Mini-Batch, Decentralized and Federated Setting.

An Econometric Analysis of North Carolina Crime Data from 1987

Clustering algorithms, validations and interpretations with some robust statistic advanced topics. Real case applications. My R scripts to solve some university exams ;) - Work in progress

Robust analysis of categorical data

Lévy's alpha-stable distribution for the Jax numerical framework

CRAN Task View: Robust Statistical Methods