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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Updated 11 Jul 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.

Cite As

Eugenio Bertolini (2026). Metropolis-Hastings Monte Carlo Markov chain algorithm (https://se.mathworks.com/matlabcentral/fileexchange/78017-metropolis-hastings-monte-carlo-markov-chain-algorithm), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2019b
Compatible with R2019b and later releases
Platform Compatibility
Windows macOS Linux

MetropolisHastings_MCMC

Version Published Release Notes
1.0.1

Changed image preview

1.0.0