On Metropolis-Hastings algorithms with delayed rejection
By Antonietta Mira. 2001
202 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/c7e3ab118463e532b0957bc66b58b490a693204e
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Citations in the corpus
- Survey of multifidelity methods in uncertainty propagation, inference, and optimization (2018, methodology): “Multistage MCMC methods based on delayed rejection, in contrast to delayed acceptance, have been proposed in [200, 144, 85].”
- Efficient MCMC for Climate Model Parameter Estimation: Parallel Adaptive Chains and Early Rejection (2012, methodology): “The delayed rejection (DR) method by Mira (2001) can be combined with AM, as done by Haario et al. (2006).”
- MCMC Bayesian Estimation of a Skew-GED Stochastic Volatility Model (2004, background): “Mira (2001) and Tierney and Mira (1999) prove that, in order to maintain the reversibil- ity of the chain, for each sub-step of the MH algorithm the acceptance probability 5See Cappuccio et al. (2001) for a similar stochastic volatility model with a different approach to sampling of the volatility…”
- Optimal scaling of Metropolis algorithms: Heading toward general target distributions (2008, methodology): “…algorithms; Bédard, Fort, and Moulines (2008) features a comparison of the asymptotic behaviour of the Multiple Try Metropolis algorithm and the Delayed Rejection Metropolis algorithm (for more information on these sampling methods, see Liu, Liang, and Wong (2000) and Mira (2001), respectively).”
- DRAM: Efficient adaptive MCMC (2006, background): “If qi denotes the proposal at the i-th stage, the acceptance probability at that stage is, following [12],:”
- Simulation-based optimal Bayesian experimental design for nonlinear systems (2011, methodology): “Two useful improvements to MH are the concepts of delayed rejection (DR) [77, 78] and adaptive Metropolis (AM) [79]; combining these lead to the DRAM algorithm of Haario et al.”