Statistical Models Python Packages

conjugate-prior

Implementation of the conjugate prior table for Bayesian Statistics

pydtmc

A library for discrete-time Markov chains analysis.

generalized-additive-models

Generalized Additive Models in Python.

brmspy

Python-first access to R’s brms with proper parameter names, ArviZ support, and cmdstanr performance. The easiest way to run brms models from Python.

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.

appelpy

Applied Econometrics Library for Python

ci-methods-analyser

Analyse efficacy of your own confidence interval (CI) methods

goftests

Generic goodness of fit tests for random plain old data

flame-pytorch

This is a implementation of the 3D FLAME model in PyTorch

pydisagg

No description available

bareml

Machine learning & deep learning implementation from scratch, depending only on numpy.

levy-stable-jax

Implementation of the Lévy alpha-stable distributions for Jax.

buqeyemodel

A Bayesian model of series convergence using Gaussian sums

phyddle

Software for phylogenetic model exploration with deep learning

asalix

A comprehensive collection of mathematical tools and utilities designed to support Lean Six Sigma practitioners in their process improvement journey

python-synthetica

Generate synthetic time series data.

paratc

ParaTC: Python functions and classes for generating parametric tropical cyclone models.

tseuler

A library for Time-Series exploration, analysis & modelling.

stat-analysis

A Python library providing hands on implementation of a collection of common statistical methods for data analysis.

maxlike

Python package to model count data through maximum likelihood estimation.

gsum

A Bayesian model of series convergence using Gaussian sums