Importance tempering

Simulated tempering (ST) is an established Markov Chain Monte Carlo (MCMC) methodology for sampling from a multimodal density π(θ). The technique involves introducing an auxiliary variable k taking values in a finite subset of [0, 1] and indexing a set of tempered distributions, say πk(θ) ∝ π(θ)k. Small values of k encourage better mixing, but samples from π are only obtained when the joint chain for (θ, k)

• Type: Journal
• Year: 2010
• Where: SAC
• Authors: Robert B. Gramacy, Richard Samworth, Ruth King
• Keywords: Applied Computing, Markov Chain Monte Carlo, Multimodal Density, SAC 2010, Tempered Distributions