MATLAB Source Code for Markov Chain Monte Carlo Simulation

This document presents MATLAB source code for Markov Chain Monte Carlo (MCMC) simulation. We provide detailed explanations on utilizing this source code for Monte Carlo simulations, accompanied by practical implementation examples. The content explores fundamental principles of Markov chains and demonstrates their application in solving various problems across statistics and physics domains. The implementation includes key algorithmic components such as proposal distribution handling, acceptance ratio calculation using the Metropolis-Hastings algorithm, and chain state management through iterative sampling. Code structure features modular functions for chain initialization, transition probability computation, and convergence diagnostics. Through this technical exposition, readers will gain comprehensive understanding of MCMC concepts and MATLAB implementation techniques, enabling effective application in practical scenarios involving probabilistic modeling and Bayesian inference.