35 citations · 42 across the 4 of their papers we have counts for
4 papers
Couplings of the Random-Walk Metropolis algorithm
John O'Leary
Couplings play a central role in contemporary Markov chain Monte Carlo methods and in the analysis of their convergence to stationarity. In most cases, a coupling must induce relat…
Metropolis-Hastings transition kernel couplings
John O'Leary, Guanyang Wang
Couplings play a central role in the analysis of Markov chain convergence and in the construction of novel Markov chain Monte Carlo estimators, diagnostics, and variance reduction…
Maximal couplings of the Metropolis-Hastings algorithm
John O'Leary, Guanyang Wang, Pierre E. Jacob
Couplings play a central role in the analysis of Markov chain Monte Carlo algorithms and appear increasingly often in the algorithms themselves, e.g. in convergence diagnostics, pa…
Unbiased Markov chain Monte Carlo with couplings
Pierre E. Jacob, John O'Leary, Yves F. Atchadé
Markov chain Monte Carlo (MCMC) methods provide consistent of integrals as the number of iterations goes to infinity. MCMC estimators are generally biased after any fixed number of…