minaskar/pocomc
pocoMC: A Python implementation of Preconditioned Monte Carlo for accelerated Bayesian Computation
This tool helps scientists and researchers quickly estimate model parameters and compare different models, especially in fields like astronomy and cosmology. You provide your model's likelihood function and a prior distribution for its parameters, and it outputs efficient posterior samples and an estimate of the model evidence. This is useful for anyone working with complex, high-dimensional data where traditional Bayesian methods are too slow.
120 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to perform fast Bayesian inference for scientific problems involving expensive calculations, non-linear relationships, or multiple possible solutions.
Not ideal if your problems are simple enough for traditional MCMC or Nested Sampling to run quickly, or if you're not comfortable working with Python.
Stars
120
Forks
11
Language
Python
License
GPL-3.0
Category
Last pushed
Sep 11, 2025
Commits (30d)
0
Dependencies
7
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