Differential Evolution Monte Carlo sampling

easy Bayesian computation for real parameter spaces

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This code implements a Markov chain Monte Carlo algorithm which automatically and efficiently tunes the proposal distribution to the covariance structure of the target distribution. This is achieved while maintaining the target distribution as the stationary distribution of the Markov chain. The algorithm is described in:

Cajo F.T. Ter Braak, "A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces", Stat Comput (2006) 16:239–249

As of the date of submission, this paper is freely available at:

http://www.stat.columbia.edu/~gelman/stuff_for_blog/cajo.pdf

Citation pour cette source

Corey Yanofsky (2026). Differential Evolution Monte Carlo sampling (https://fr.mathworks.com/matlabcentral/fileexchange/18092-differential-evolution-monte-carlo-sampling), MATLAB Central File Exchange. Extrait(e) le .

Informations générales

Compatibilité avec les versions de MATLAB

  • Compatible avec toutes les versions

Plateformes compatibles

  • Windows
  • macOS
  • Linux
Version Publié le Notes de version Action
1.4.0.0

updated license

1.0.0.0

fix typos, fix M-Lint warnings, add acknowledgement of funding