On the rate of convergence of the Metropolis algorithm and Gibbs sampler by geometric bounds

DOI10.1214/aoap/1177005064zbMath0802.60061OpenAlexW1969238664MaRDI QIDQ1333379

Salvatore Ingrassia

Publication date: 12 December 1994

Published in: The Annals of Applied Probability (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aoap/1177005064

zbMATH Keywords

transition probability matrixboundsspectral gapGibbs samplerMetropolis algorithmrandom updating dynamicsrate of convergence at low temperatures

Mathematics Subject Classification ID

Sums of independent random variables; random walks (60G50) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Inequalities involving eigenvalues and eigenvectors (15A42)

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