Introduction¶
arianna 1 is a Python implementation of the Metropolis–Coupled Slice Sampling method that generates posterior samples from high-dimensional and strongly multimodal distributions. Apart from Bayesian parameter inference, arianna also provides unbiased and low-variance estimates of the model evidence (aka marginal likelihood) at no additional cost. The sampler is modular and does not require any hand-tuning from the user. Its parallel and black-box nature renders it ideal for computationally expensive models with high number of parameters often met in the physical sciences.
Documentation¶
Attribution¶
Please cite the following if you find this code useful in your research. The BibTeX entry for the paper is:
@article{arianna,
title={arianna: A Metropolis--Coupled Slice Sampler for Bayesian Inference and Model Selection},
author={Minas Karamanis and Florian Beutler},
year={2021},
note={in prep}
}
Authors & License¶
Copyright 2021 Minas Karamanis and contributors.
arianna
is free software made available under the GPL-3.0 License
.