Metropolis-Hastings Monte Carlo Markov chain algorithm

Algorithm to generate a Metropolis-Hastings Monte Carlo Markov chain, ready to generate cool MCMC video
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Mise à jour 11 juil. 2020

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Easy algorithm to generate a Metropolis-Hastings Monte Carlo Markov chain that, given a probability density function (pdf), generate a Markow chain. The function enables the user to select the pdf, using a function handler @(x), and it enables to choose a sampler between uniform and gaussian. The example code also shows how to plot the Markow process just generated and it enables to convert the process into a cool video where you can follow the behaviour of your MCMC.

Make sure to read the comments inside the functions.

Citation pour cette source

Eugenio Bertolini (2024). Metropolis-Hastings Monte Carlo Markov chain algorithm (https://www.mathworks.com/matlabcentral/fileexchange/78017-metropolis-hastings-monte-carlo-markov-chain-algorithm), MATLAB Central File Exchange. Récupéré le .

Compatibilité avec les versions de MATLAB
Créé avec R2019b
Compatible avec les versions R2019b et ultérieures
Plateformes compatibles
Windows macOS Linux

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MetropolisHastings_MCMC

Version Publié le Notes de version
1.0.1

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1.0.0