📊 Computation and processing of models' parameters

Tidy data frames and expressions with statistical summaries 📜

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

Robust estimations from distribution structures: Mean.

Robust estimations from distribution structures: Invariant moments.

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

📦 🎲 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 estimations from distribution structures: Central moments.

Robust Sure Independence Screening using the Minimum Density Power Divergence Estimators

🌳 🎯 Cross Validated Decision Trees with Targeted Maximum Likelihood Estimation

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.

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

Simple multiverse analysis simulations, visualizations and inference techniques.

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

This is a fork of cran/MASS with a modified rlm function that can handle complex valued data.

An R package containing tools for linear fitting of complex variables. Includes ordinary least squares and M-estimator robust functions.

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.

Minimum Density Power Divergence Estimation for Multivariate Datasets