4. The MCMC module¶
This module is the original part of the program, although massively rewritten from version 1.0.4 to 1.1. Originally, EPIC could run with standard MCMC sampler or Parallel-Tempering MCMC. The former has been temporarily removed to give place to a new and cleaner implementation attempting to solve some bugs. Use version 1.0.4 in case you need it. The MCMC sampler comes with an experimental adaptive routine that adjusts the covariance of the proposal multivariate Gaussian probability density for optimal efficiency, aiming at an acceptance rate around \(0.234\). In the following sections I briefly introduce the MCMC method and show how to use this program to perform simulations, illustrating with examples.
- 4.1. Introduction to MCMC and the Bayesian method
- 4.2. Before starting
- 4.3. Running MCMC