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[ascl:1610.013] MC3: Multi-core Markov-chain Monte Carlo code

MC3 (Multi-core Markov-chain Monte Carlo) is a Bayesian statistics tool that can be executed from the shell prompt or interactively through the Python interpreter with single- or multiple-CPU parallel computing. It offers Markov-chain Monte Carlo (MCMC) posterior-distribution sampling for several algorithms, Levenberg-Marquardt least-squares optimization, and uniform non-informative, Jeffreys non-informative, or Gaussian-informative priors. MC3 can share the same value among multiple parameters and fix the value of parameters to constant values, and offers Gelman-Rubin convergence testing and correlated-noise estimation with time-averaging or wavelet-based likelihood estimation methods.

Code site:
https://github.com/pcubillos/MCcubed http://pcubillos.github.io/MCcubed/
Appears in:
http://adsabs.harvard.edu/abs/2016arXiv161001336C
Bibcode:
2016ascl.soft10013C

ascl:1610.013
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