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

Phylogenetic inference using Stan

Bayesian Inferential Regression for Differential Microbiome Analysis

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

Bayesian models of football leagues

Gaussian processes on graphs and lattices in Stan.

Source code and data for the EDM 2022 paper

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

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.

Structural time series modeling and forecasting in Python

scikit-learn wrapper for generalized linear mixed model methods in R

GRB triangulation via non-stationary time-series models

Python implementations of r-stan bayesian model（RとStanではじめるベイズ統計モデリングによるデータサイエンス入門 by Python）