A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.

PyStan, the Python interface to Stan

BridgeStan provides efficient in-memory access through Python, Julia, and R to the methods of a Stan model.

STUN & TURN client demo and api with python and C

A surface language for programming Stan models using python syntax

bayesian model by r and stan『StanとRでベイズ統計モデリング』by Python

A simple library to run variational inference on Stan models.

A sklearn style interface to Stan regression models

Bayesian Inferential Regression for Differential Microbiome Analysis

Phylogenetic inference using Stan

Code for "Reconstruction of plant--pollinator networks from observational data"

Gaussian processes on graphs and lattices in Stan.

Bayesian models of football leagues

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.

Unofficial implementation of STAN paper published at ISBI 2020 by researchers from University of Idaho using Tensorflow Keras 2.0.

Source code and data for the EDM 2022 paper

A modern framework for time series analysis and forecasting, offering everything from simple automated fits to fine-grained parameter control, with native support for diverse data types.

Easy, minimal interface to the Stan samplers in several languages

Structural time series modeling and forecasting in Python

GRB triangulation via non-stationary time-series models