Tuning Tempered Transitions

Details Tuning Tempered Transitions Tuning Tempered Transitions

2010-10-05

arxiv.org/abs/1010.0842v1

Statistics

Computation

To appear in Statistics and Computing

Scientific paper

The method of tempered transitions was proposed by Neal (1996) for tackling the difficulties arising when using Markov chain Monte Carlo to sample from multimodal distributions. In common with methods such as simulated tempering and Metropolis-coupled MCMC, the key idea is to utilise a series of successively easier to sample distributions to improve movement around the state space. Tempered transitions does this by incorporating moves through these less modal distributions into the MCMC proposals. Unfortunately the improved movement between modes comes at a high computational cost with a low acceptance rate of expensive proposals. We consider how the algorithm may be tuned to increase the acceptance rates for a given number of temperatures. We find that the commonly assumed geometric spacing of temperatures is reasonable in many but not all applications.

Affiliated with

Also associated with

No associations

Rating

Tuning Tempered Transitions does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Tuning Tempered Transitions, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Tuning Tempered Transitions will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-86519