Statistical Inference Python Packages

getdist

MCMC sample analysis, kernel densities, plotting, and GUI

pyhf

pure-Python HistFactory implementation with tensors and autodiff

hepstats

HEP statistics tools and utilities.

gibbus

Flexible analytic log-concave distributions fitted by maximum likelihood, with support-aware modeling and optional mixtures for multimodal data.

ambrosia

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

cegpy

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.

geoestimate

Inference from data collected using the geo-sampling, allocator pipeline

pysie

Package provides python implementation of statistical inference engine

regression-inference

Python library for statistical inference in ML and Econometrics with GPU accelerated model training.

esa-2scm

ESA-2SCM for Causal Discovery: Causal Modeling with Elastic Segmentation-based Synthetic Instrumental Variable

scmopy

scmopy: Distribution-Agnostic Structural Causal Models Optimization in Python

generalized-additive-models

Generalized Additive Models in Python.

beta4dist

A Python Package for the Four-Parameter Beta Distribution and Likelihood-Based Estimation

isweep

Statistical inference of recent positive selection using IBD segments

delimiterfinder

Python package for probabilistic delimiter detection.

stattools

Statistical learning and inference algorithms implemented in Python 3

dnn-inference

Significance tests of feature relevance for a black-box learner

tfnbs

Unified Python framework for permutation-based statistical inference on brain connectivity networks (NBS, TFNBS, cNBS, NI-TFNBS, FBC-TFNBS, GLM, ComBat)

vimpy

Perform inference on algorithm-agnostic variable importance in Python

ambrozia

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

pytorch-inferno

PyTorch implementation of inference aware neural optimisation (de Castro and Dorigo, 2018 https://www.sciencedirect.com/science/article/pii/S0010465519301948)

memocell

Bayesian inference of stochastic cellular processes with and without memory in Python.

scikit-stats

HEP statistics tools and utilities.

ppi-aipw

Python and R package for semisupervised mean estimation and causal inference with AIPW, calibration, and practical uncertainty quantification.