10 citations · 34 across the 19 of their papers we have counts for
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stat.CO2022
BayesMix: Bayesian Mixture Models in C++
Mario Beraha, Bruno Guindani, Matteo Gianella +1
We describe BayesMix, a C++ library for MCMC posterior simulation for general Bayesian mixture models. The goal of BayesMix is to provide a self-contained ecosystem to perform infe…
stat.CO2021★ 10 cited
JAGS, NIMBLE, Stan: a detailed comparison among Bayesian MCMC software
Mario Beraha, Daniele Falco, Alessandra Guglielmi
The aim of this work is the comparison of the performance of the three popular software platforms JAGS, NIMBLE and Stan. These probabilistic programming languages are able to autom…