Ensemble Quadratic and Affine Invariant Markov Chain Monte Carlo
Overview
The Ensemble Quadratic and Affine Invariant Markov chain Monte Carlo algorithms provide an efficient way to perform Bayesian inference in difficult parameter space geometries. The Ensemble Quadratic Monte Carlo algorithm was developed by Militzer (2023) doi:10.3847/1538-4357/ace1f1. The Ensemble Affine Invariant algorithm was developed by Goodman and Weare (2010) doi:10.2140/camcos.2010.5.65 and it was implemented in Python by Foreman-Mackey et al (2013) doi:10.48550/arXiv.1202.3665. The Quadratic Monte Carlo method was shown to perform better than the Affine Invariant method in the paper by Militzer (2023) doi:10.3847/1538-4357/ace1f1 and the Quadratic Monte Carlo method is the default method used. The Chen-Shao Highest Posterior Density Estimation algorithm is used for obtaining credible intervals and the potential scale reduction factor diagnostic is used for checking the convergence of the chains.
- Initial CRAN submission.
From NEWS.md in the release
Install
Health
- OK13 OK2026-09-08
- ERROR12 OK, 1 ERROR2026-09-07
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 3
- Examples that run
- 100%3 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 100%
Downloads
Dependencies
Installing QAEnsemble adds no packages beyond those that come with R.
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 1.0.0Latest2025-01-09 · current release
- RR 4.4.0 released · 2024-04-24
Package metadata
- First published
- 2025-01-09
- Total releases
- 1 / 1 yrs
- License
- GPL (>= 2) OSI
- Download size
- 258 KB
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