Multi-Core Markov-Chain Monte Carlo (MC3)¶
Author: | Patricio Cubillos and collaborators (see Collaborators) |
---|---|
Contact: | patricio.cubillos[at]oeaw.ac.at |
Organizations: | University of Central Florida (UCF), Space Research Institute (IWF) |
Web Site: | https://github.com/pcubillos/MCcubed |
Date: | Aug 11, 2019 |
Features¶
MC3
is a powerful Bayesian-statistics tool that offers:
- Levenberg-Marquardt least-squares optimization.
- Markov-chain Monte Carlo (MCMC) posterior-distribution sampling following the:
- Metropolis-Hastings algorithm with Gaussian proposal distribution,
- Differential-Evolution MCMC (DEMC), or
- DEMCzs (Snooker).
The following features are available when running MC3
:
- Execution from the Shell prompt or interactively through the Python interpreter.
- Single- or multiple-CPU parallel computing.
- Uniform non-informative, Jeffreys non-informative, or Gaussian-informative priors.
- Gelman-Rubin convergence test.
- Share the same value among multiple parameters.
- Fix the value of parameters to constant values.
- Correlated-noise estimation with the Time-averaging or the Wavelet-based Likelihood estimation methods.
Note
MC3
works in both Python2.7 and Python3!
Collaborators¶
All of these people have made a direct or indirect contribution to
MCcubed
, and in many instances have been fundamental in the
development of this package.
- Patricio Cubillos (UCF, IWF) patricio.cubillos[at]oeaw.ac.at
- Joseph Harrington (UCF)
- Nate Lust (UCF)
- AJ Foster (UCF)
- Madison Stemm (UCF)
- Tom Loredo (Cornell)
- Kevin Stevenson (UCF)
- Chris Campo (UCF)
- Matt Hardin (UCF)
- Ryan Hardy (UCF)
- Monika Lendl (IWF)
- Ryan Challener (UCF)
- Michael Himes (UCF)
Documentation¶
Be Kind¶
- Please cite this paper if you found
MC3
useful for your research: - Cubillos et al. (2017): On the Correlated-noise Analyses Applied to Exoplanet Light Curves, AJ, 153, 3.
We welcome your feedback, but do not necessarily guarantee support. Please send feedback or inquiries to:
Patricio Cubillos (patricio.cubillos[at]oeaw.ac.at)
MC3
is open-source open-development software under the MIT
License.
Thank you for using MC3
!
Documentation for Previous Releases¶
If you have an older version, you can compile these docs, according to your version into a pdf with the following commands:
# cd into MCcubed/docs
make latexpdf
The output pdf docs will be located at .../MCcubed/docs/latex/MC3.pdf
.