This program develops a very basic example, for the sampling of functions by means of Metropolis algorithm; showing the correlograms and the histogram of the generated samples. metropolis_hastings.m. This file contains four examples, for the sampling of complex functions by means of Metropolis-Hastings algorithm, showing the correlograms and the histograms of the generated samples. In this case the proposals PDF its no longer symmetric. Additionally, the burn-in period, the lag period and the Geweke test have been implemented.It needs the "MH_routine.m" function. metropolis_hastings2.m. This file contains one example, for the sampling of a bivariate Gaussian PDF by means of Metropolis-Hastings algorithm, showing the correlograms and the histograms of the generated samples, and the function with its contours and marginals PDF. Additionally, the burn-in period, the lag period and the Geweke test have been implemented.

metropolis_hastings
metropolis_hastings\metropolis.m
__MACOSX
__MACOSX\metropolis_hastings
__MACOSX\metropolis_hastings\._metropolis.m
metropolis_hastings\metropolis_hastings.m
__MACOSX\metropolis_hastings\._metropolis_hastings.m
metropolis_hastings\metropolis_hastings2.m
__MACOSX\metropolis_hastings\._metropolis_hastings2.m
metropolis_hastings\MH_routine.m
__MACOSX\metropolis_hastings\._MH_routine.m
metropolis_hastings\readme.txt
__MACOSX\metropolis_hastings\._readme.txt
__MACOSX\._metropolis_hastings

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