Optimal acceptance rates for Metropolis algorithms: Moving beyond 0.234
- 1 December 2008
- journal article
- Published by Elsevier in Stochastic Processes and their Applications
- Vol. 118 (12), 2198-2222
- https://doi.org/10.1016/j.spa.2007.12.005
Abstract
No abstract availableKeywords
This publication has 11 references indexed in Scilit:
- Weak convergence of Metropolis algorithms for non-i.i.d. target distributionsThe Annals of Applied Probability, 2007
- Optimal scaling for partially updating MCMC algorithmsThe Annals of Applied Probability, 2006
- Scaling Limits for the Transient Phase of Local Metropolis–Hastings AlgorithmsJournal of the Royal Statistical Society Series B: Statistical Methodology, 2005
- Optimal scaling for various Metropolis-Hastings algorithmsStatistical Science, 2001
- From metropolis to diffusions: Gibbs states and optimal scalingStochastic Processes and their Applications, 2000
- Weak convergence and optimal scaling of random walk Metropolis algorithmsThe Annals of Applied Probability, 1997
- Bayesian Computation and Stochastic SystemsStatistical Science, 1995
- Optimum Monte-Carlo sampling using Markov chainsBiometrika, 1973
- Monte Carlo sampling methods using Markov chains and their applicationsBiometrika, 1970
- Equation of State Calculations by Fast Computing MachinesThe Journal of Chemical Physics, 1953