acerbilab/vbmc
Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference in MATLAB
This tool helps scientists and researchers efficiently fit and evaluate complex computational models, especially when your model's likelihood function is expensive to calculate or contains noise. You input your model's log posterior distribution and parameter bounds, and it outputs an approximate posterior distribution of your model's parameters and an estimate of the log model evidence for comparing different models. It's designed for quantitative researchers in fields like computational neuroscience, cognitive science, and other areas using complex simulations.
233 stars. No commits in the last 6 months.
Use this if you need to perform Bayesian inference for models with up to 10-20 continuous parameters where calculating the log-likelihood is time-consuming or produces noisy results.
Not ideal if your model can be expressed analytically or if you have a very large number of parameters (over 20).
Stars
233
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44
Language
MATLAB
License
BSD-3-Clause
Category
Last pushed
May 03, 2023
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