Modified Metropolis–Hastings algorithm with delayed rejection

Modified Metropolis-Hastings algorithm with Delayed Rejection

The development of an efficient MCMC strategy for sampling from complex distributions is a difficult task that needs to be solved for calculating small failure probabilities encountered in high-dimensional reliability analysis of engineering systems. Usually different variations of the Metropolis-Hastings algorithm (MH) are used. However, the standard MH algorithm does generally not work in hig...

Modified Metropolis-Hastings algorithm with Delayed Rejection for High-Dimensional Reliability Analysis

The development of an efficient MCMC strategy for sampling from complex distributions is a difficult task that needs to be solved for calculating small failure probabilities encountered in high-dimensional reliability analysis of engineering systems. Usually different variations of the Metropolis-Hastings algorithm (MH) are used. However, the standard MH algorithm does generally not work in hig...

On Metropolis-Hastings algorithms with delayed rejection

Delayed rejection variational Monte Carlo.

An acceleration algorithm to address the problem of multiple time scales in variational Monte Carlo simulations is presented. After a first attempted move has been rejected, the delayed rejection algorithm attempts a second move with a smaller time step, so that even moves of the core electrons can be accepted. Results on Be and Ne atoms as test cases are presented. Correlation time and both av...

Scaling analysis of delayed rejection MCMC methods

In this paper, we study the asymptotic efficiency of the delayed rejection strategy. In particular, the efficiency of the delayed rejection Metropolis-Hastings algorithm is compared to that of the regular Metropolis algorithm. To allow for a fair comparison, the study is carried under optimal mixing conditions for each of these algorithms. After introducing optimal scaling results for the delay...