Encyclopedia of Statistics in Quality and Reliability

We survey possible strategies to improve the performance of Markov chain Monte Carlo methods either by reducing the asymptotic variance of the resulting estimators or by increasing the speed of convergence to stationarity. Recent advances in the direction of the pseudomarginal approach, Gradient-based algorithms and Approximate Bayesian Computation are also highlighted.