Statistics and Computing

, Volume 23, Issue 3, pp 323–339 | Cite as

Parallel tempering with equi-energy moves

  • Meïli Baragatti
  • Agnès Grimaud
  • Denys PommeretEmail author


The Equi-Energy Sampler (EES) introduced by Kou et al. (in Ann. Stat. 34(4), 1581–1619, 2006) is based on a population of chains which are updated by local moves and global moves, also called equi-energy jumps. The state space is partitioned into energy rings, and the current state of a chain can jump to a past state of an adjacent chain that has an energy level close to its level. This algorithm has been developed to facilitate global moves between different chains, resulting in a good exploration of the state space by the target chain. This method seems to be more efficient than the classical Parallel Tempering (PT) algorithm. However it is difficult to use in combination with a Gibbs sampler and it necessitates increased storage. We propose an adaptation of this EES that combines PT with the principle of swapping between chains with the same level of energy. This adaptation, that we shall call Parallel Tempering with Equi-Energy Moves (PTEEM), keeps the original idea of the EES method while ensuring good theoretical properties, and practical implementation. Performances of the PTEEM algorithm are compared with those of the EES and of the standard PT algorithms in the context of mixture models, and in a problem of identification of transcription factor binding motifs.


Equi-energy sampler Parallel tempering Population-based Monte Carlo Markov chains Mixture models Binding sites for transcription factors 


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Meïli Baragatti
    • 1
    • 2
  • Agnès Grimaud
    • 2
  • Denys Pommeret
    • 2
    Email author
  1. 1.Ipsogen SALuminy Biotech EntreprisesMarseille Cedex 9France
  2. 2.Institute of Mathematics of Luminy (IML)CNRS MarseilleMarseille Cedex 9France

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