Optimal scaling of random walk Metropolis algorithms with non-Gaussian proposals

DOI10.1007/s11009-010-9176-9zbMath1237.60060OpenAlexW2094770100MaRDI QIDQ655925

Gareth O. Roberts, Peter Neal

Publication date: 26 January 2012

Published in: Methodology and Computing in Applied Probability (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11009-010-9176-9

zbMATH Keywords

heavy-tailed distributionsMarkov Chain Monte CarloMCMCoptimal scalingCauchy distribution spherical distributionsRandom Walk MetropolisRWM

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Monte Carlo methods (65C05) Discrete-time Markov processes on general state spaces (60J05) Numerical analysis or methods applied to Markov chains (65C40)

Related Items

Complexity bounds for Markov chain Monte Carlo algorithms via diffusion limits, Conditional sequential Monte Carlo in high dimensions, Optimal scaling of random-walk Metropolis algorithms on general target distributions, Optimal scaling for the transient phase of Metropolis Hastings algorithms: the longtime behavior, Optimal scaling of random walk Metropolis algorithms with discontinuous target densities, Random walk Metropolis algorithm in high dimension with non-Gaussian target distributions, Optimal scaling for the transient phase of the random walk Metropolis algorithm: the mean-field limit

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