Bayesian inference with probabilistic programming.

Julia package with selected functions in the R package `rethinking`. Used in the SR2... projects.

Types and utility functions for summarizing Markov chain Monte Carlo simulations

A Bayesian Analysis Toolkit in Julia

Stan.jl illustrates the usage of the 'single method' packages, e.g. StanSample, StanOptimize, etc.

Implementations of the models from the Statistical Rethinking book with Turing.jl

Robust implementation for random-walk Metropolis-Hastings algorithms

StatisticalRethinking notebook project using Turing and Pluto notebooks (derived from Max Lapan's Jupyter project)

Sampling from intractable distributions, with support for distributed and parallel methods

Simulated Method of Moments for Julia

Sequential Monte Carlo algorithm for approximation of posterior distributions.

Bayesian Generalized Linear models using `@formula` syntax.

Simulation, visualization, and inference of individual level infectious disease models with Julia

Markov chain Monte Carlo solver for lattice spin systems implemented in Julialang

A common framework for implementing and using log densities for inference.

Comparing performance and results of mcmc options using Julia

Implementations of parallel tempering algorithms to augment samplers with tempering capabilities

Affine Invariant Markov Chain Monte Carlo (MCMC) Ensemble sampler

CmdStan.jl v6 provides an alternative, older Julia wrapper to Stan's `cmdstan` executable. CmdStan will be deprecated in 2022.

MCMC Inference for a Hawkes process in Julia