Metropolis-Hastings Monte Carlo Markov chain algorithm
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 .
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MetropolisHastings_MCMC
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1.0.1 | Changed image preview |
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