On random- and systematic-scan samplers

DOI10.1093/BIOMET/ASW019zbMath1506.62010OpenAlexW2511006079MaRDI QIDQ5384404

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Publication date: 24 June 2019

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://research-information.bris.ac.uk/ws/files/72476340/novice_final_supplemental.pdf

zbMATH Keywords

Markov chain Monte CarloMetropolis-within-Gibbs algorithmPeskun orderdeterministic-scan samplerrandom-scan sampler

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Computational methods for problems pertaining to statistics (62-08) Monte Carlo methods (65C05) Numerical analysis or methods applied to Markov chains (65C40)

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Markov Kernels Local Aggregation for Noise Vanishing Distribution Sampling ⋮ Convergence rates of two-component MCMC samplers ⋮ Non-reversible guided Metropolis kernel ⋮ Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance ⋮ Peskun-Tierney ordering for Markovian Monte Carlo: beyond the reversible scenario ⋮ A hybrid scan Gibbs sampler for Bayesian models with latent variables

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