nonparametric-statistics

Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).

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

Hypothesis and statistical testing in Python

The Wasserstein Distance and Optimal Transport Map of Gaussian Processes

Multivariate kernel density estimation

A C++ library for physics-informed spatial and functional data analysis.

R package for random forests model selection, inference, evaluation and validation

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

The R wrapper to the fdaPDE library for physics-informed spatial and functional data analysis.

A MATLAB package for multivariate permutation testing and effect size measurement

Scalable, GPU-accelerated Python library for modern difference-in-differences.

Perform inference on algorithm-agnostic variable importance

Perform inference on algorithm-agnostic variable importance in Python

B-Spline Density Estimation Library - nonparametric density estimation using B-Spline density estimator from univariate sample.

Unsupervised anomaly detection in vibration signal using PyCaret vs BiLSTM

An R package for nonparametric covariance matrix estimation in high dimensions

Nonparametric kernel density estimation, bandwidth selection, and other utilities for analyzing directional data

Chinese Restaurant Process Models for Regression and Clustering. Master branch contains latest stable build.

My implementation of Symbolic Transfer Entropy (STE): a measure of asymmetric information flow between stochastic processes.

Robust estimations from distribution structures: Central moments.