pure-Python HistFactory implementation with tensors and autodiff

A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.

Ambrosia is a Python library for A/B tests design, split and result measurement

MCMC sample analysis, kernel densities, plotting, and GUI

HEP statistics tools and utilities.

Hypothesis and statistical testing in Python

Statistical inference on machine learning or general non-parametric models

Code and data for the KDD2020 paper "Learning Opinion Dynamics From Social Traces"

Perform inference on algorithm-agnostic variable importance in Python

Generalized Additive Models in Python.

Significance tests of feature relevance for a black-box learner

A Bayesian model of series convergence using Gaussian sums

Code and data for the CIKM2021 paper "Learning Ideological Embeddings From Information Cascades"

Cegpy (/segpaɪ/) is a Python package for working with Chain Event Graphs. It supports learning the graphical structure of a Chain Event Graph from data, encoding of parametric and structural priors, estimating its parameters, and performing inference.

A package for constructing confidence intervals for error rates in matching tasks such as 1:1 face and speaker verification.

Off-Policy Interval Estimation withConfounded Markov Decision Process

Reproduce analyses from "Efficient nonparametric statistical inference on population feature importance using Shapley values"

Statistical Digital Signal Processing and Modeling

My Personal Machine Learning and Data Science Training Repository

A little exploration of R's power for statistical inference