Mamba
A Julia package for implementing and applying Markov chain Monte Carlo (MCMC) methods for Bayesian analysis.
What is Mamba?
Mamba is a Julia package for Markov chain Monte Carlo (MCMC) methods in Bayesian analysis. It provides a framework for specifying hierarchical models, updating parameters with various samplers, executing sampling schemes, and performing posterior inference. The package is designed to give users low-level access to MCMC tools for developing new methods.
Researchers, statisticians, and data scientists who are knowledgeable about MCMC methodologies and want to implement or extend Bayesian analysis methods in Julia. It is also suitable for those who need convergence diagnostics and posterior inference tools for MCMC output.
Mamba offers an extensible, Julia-native environment where all model specifications and samplers can be written in Julia, providing flexibility and performance on par with compiled MCMC software. It includes a wide range of samplers and diagnostics, making it a comprehensive tool for advanced Bayesian analysis.
Overview
Markov chain Monte Carlo (MCMC) for Bayesian analysis in julia
Use Cases
Best For
- Developing custom MCMC samplers in Julia
Related Projects
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