Bayesian Workflow book code and case studies

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.

The best ChatGPT that $100 can buy.

GitHub action to run CRAN-style reverse dependency check

PolyChord nested sampling on Stan models

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.

Fast Normal-Normal models

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

A package to model elemental fluxes in fish

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

↙️ ↘️ An R package for working with causal directed acyclic graphs (DAGs)

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