Parallel Markov Chain Monte Carlo

Comparison of some ratio estimators

Tin, M · 1965

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Practical Markov chain Monte Carlo

Geyer, C. J · 1992

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Bayesian analysis of binary and polychotomous response data

Albert, J · 1993

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Marginal likelihood from the Gibbs output

Chib, S · 1995

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Simulating ratios of normalizing constants via a simple identity: A theoretical exploration

Meng, X.-L · 1996

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Simulating normalizing constants: From importance sampling to bridge sampling to path sampling

Gelman, A · 1998

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A hybrid Markov chain for the Bayesian analysis of the multinomial probit model

Nobile, A · 1998

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Parallel computing and Monte Carlo algorithms

Rosenthal · 2000

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Marginal likelihood from the Metropolis-Hastings output

Chib, S · 2001

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Warp bridge sampling

Meng, X.-L · 2002

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Parallel algorithms for Bayesian phylogeneitc inference

Feng, X · 2003

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A new mixture model approach to analyzing allelic-loss data using Bayes factors

Desai, M · 2004

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A Bayesian analysis of the multinomial probit model using marginal data augmentation

Imai, K · 2005

Cited alongside, same era.

Parallel processing in Markov chain Monte Carlo simulation by pre-fetching

Brockwell, A. E · 2006

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Learn from thy neighbor: Parallel-chain and regional adaptive MCMC

Craiu, R. V · 2009

Later among the works it cites.

Sufficient conditions for torpid mixing of parallel and simulated tempering

Original

Woodard, D · 2009

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On the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods

Lee, A · 2010

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Divide and conquer: A mixture-based approach to regional adaptation for MCMC

Bai, Y · 2011

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α \alpha -stable limit laws for harmonic mean estimators of marginal likelihoods

Wolpert, R. L · 2012

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Adaptive Markov chain Monte Carlo for Bayesian variable selection