Highlights
- Pro
Stars
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.
GitHub action to run CRAN-style reverse dependency check
Estimate Parameters for Arbitrary R Functions using 'Stan'
Run Stan models in the browser
A batteries-included template for Bayesian data analysis projects
A Julia-native port of the R-based bayesplot package using gadfly
BridgeStan provides efficient in-memory access through Python, Julia, and R to the methods of a Stan model.
Code for utilising VAE as means of doing exact MCMC inference in complex high-dimensional space
A sklearn style interface to Stan regression models
A web app to visualize distributions in Stan. Uses Stan Math C++ compiled to Webassembly to evaluate the functions using actual Stan implementations. Uses d3.js for visualizations.
library of C++ functions that support applications of Stan in Pharmacometrics
Reproducible Bayesian data analysis pipelines with targets and cmdstanr
Uses Stan sampler and math library to semiparametrically fit linear and multilevel models with additive Bayesian Additive Regression Tree (BART) components.
Database with posteriors of interest for Bayesian inference
pivmet: an R package proposing pivotal methods for consensus clustering and mixture modeling
Probability and Statistics: a simulation-based introduction. An open-access book.
A lightweight, no-dependency, but full-featured package for unit testing in R
Case studies in applied and computational statistics.
My lightning talking on bayesplot for SatRdays Chicago, April, 27, 2019
Tools for automatically generating local sensitivity measures in Stan.
A surface language for programming Stan models using python syntax
Interactive Markov-chain Monte Carlo Javascript demos