MC3: Multi-core Markov-chain Monte Carlo code

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Ada Coda
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MC3: Multi-core Markov-chain Monte Carlo code

Post by Ada Coda » Mon Oct 31, 2016 12:16 am

MC3: Multi-core Markov-chain Monte Carlo code

Abstract: 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.

Credit: Cubillos, Patricio; Harrington, Joseph; Lust, Nate; Foster, AJ; Stemm, Madison; Loredo, Tom; Stevenson, Kevin; Campo, Chris; Hardin, Matt; Hardy, Ryan


Bibcode: 2016ascl.soft10013C

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ID: ascl:1610.013
Last edited by Ada Coda on Sun Aug 11, 2019 6:31 pm, edited 1 time in total.
Reason: Updated code entry.

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