Parallel Tempering with Equi-Energy Moves

Autor: Agnès Grimaud, Denys Pommeret, Meili Baragatti
Přispěvatelé: Institut de mathématiques de Luminy (IML), Centre National de la Recherche Scientifique (CNRS)-Université de la Méditerranée - Aix-Marseille 2, Mathématiques, Informatique et STatistique pour l'Environnement et l'Agronomie (MISTEA), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA), Université de la Méditerranée - Aix-Marseille 2-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)
Jazyk: angličtina
Rok vydání: 2013
Předmět:
FOS: Computer and information sciences
Statistics and Probability
binding sites for transcription factors
Population
equi-energy sampler
Context (language use)
Topology
01 natural sciences
Theoretical Computer Science
Methodology (stat.ME)
010104 statistics & probability
03 medical and health sciences
symbols.namesake
Chain (algebraic topology)
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]
State space
population-based Monte Carlo Markov Chains
0101 mathematics
mixture models
education
Statistics - Methodology
Simulation
ComputingMilieux_MISCELLANEOUS
030304 developmental biology
Mathematics
0303 health sciences
education.field_of_study
State (functional analysis)
Mixture model
Statistics::Computation
parallel tempering
Computational Theory and Mathematics
algorithm convergence
symbols
Parallel tempering
Statistics
Probability and Uncertainty
[STAT.ME]Statistics [stat]/Methodology [stat.ME]
Gibbs sampling
Zdroj: Statistics and Computing
Statistics and Computing, Springer Verlag (Germany), 2013, 23 (3), pp.323-339. ⟨10.1007/s11222-012-9313-0⟩
Statistics and Computing, Springer Verlag (Germany), 2013
Statistics and Computing, 2013, 23 (3), pp.323-339. ⟨10.1007/s11222-012-9313-0⟩
ISSN: 0960-3174
1573-1375
Popis: The Equi-Energy Sampler (EES) introduced by Kou et al [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 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. In this paper we propose an adaptation of this EES that combines PT with the principle of swapping between chains with same levels 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 even if combined with a Gibbs sampler. 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 gene regulatory binding motifs.
Databáze: OpenAIRE
Externí odkaz: