Bayesian inference relies on the computation of posterior distributions to update beliefs about model parameters in the light of observed data. Markov Chain Monte Carlo (MCMC) methods form a flexible ...
Monte Carlo sampling methods form a cornerstone of contemporary statistical inference by enabling the approximation of complex integrals and posterior distributions that defy analytical solution. At ...