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Pseudo-marginal Metropolis-Hastings (pmMH) is a powerful method for Bayesian inference in models where the posterior distribution is analytical intractable or computationally costly to evaluate directly.
Equation of state calculations by fast computing machines
N. Metropolis, A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller, and E. Teller · 1953
Earlier work this paper cites.
Monte Carlo sampling methods using Markov chains and their applications
W. K. Hastings · 1970
Earlier work this paper cites.
Optimum Monte-carlo sampling using Markov chains
P. H. Peskun · 1973
Earlier work this paper cites.
Finite Markov chains
J. G. Kemeny and J. L. Snell · 1976
Earlier work this paper cites.
Numerical solution of stochastic differential equations , volume 23
P. E. Kloeden and E. Platen · 1992
Earlier work this paper cites.
Markov chains for exploring posterior distributions
L. Tierney · 1994
Earlier work this paper cites.
Efficient Metropolis jumping rules
A. Gelman, G. Roberts, and W. Gilks · 1996
Earlier work this paper cites.
Metropolis light transport
E. Veach and L. J. Guibas · 1997
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Safe and effective importance sampling
A. Owen and Y. Zhou · 2000
Earlier work this paper cites.
A simple and robust mutation strategy for the Metropolis light transport algorithm
C. Kelemen, L. Szirmay-Kalos, G. Antal, and F. Csonka · 2002
Earlier work this paper cites.
Monte Carlo statistical methods
C. P. Robert and G. Casella · 2004
Earlier work this paper cites.
Sequential Monte Carlo samplers
P. Del Moral, A. Doucet, and A. Jasra · 2006
Earlier work this paper cites.
MCMC methods for diffusion bridges
A. Beskos, G. Roberts, A. Stuart, and J. Voss · 2008
Earlier work this paper cites.
Towards smooth particle filters for likelihood estimation with multivariate latent variables
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The pseudo-marginal approach for efficient Monte Carlo computations
C. Andrieu and G. O. Roberts · 2009
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Markov chains and stochastic stability
S. P. Meyn and R. L. Tweedie · 2009
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Particle Markov chain Monte Carlo methods
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A tutorial on particle filtering and smoothing: Fifteen years later
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Zero variance Markov chain Monte Carlo for Bayesian estimators
A. Mira, R. Solgi, and D. Imparato · 2013
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Searching for efficient Markov chain Monte Carlo proposal kernels
Z. Yang and Carlos E Rodríguez · 2013
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Multiplexed Metropolis light transport
T. Hachisuka, A. S. Kaplanyan, and C. Dachsbacher · 2014
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Spectral gaps for a Metropolis-Hastings algorithm in infinite dimensions
M. Hairer, A. M. Stuart, and S. J. Vollmer · 2014
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Robust auxiliary particle filters using multiple importance sampling
J. Kronander and T. B. Schön · 2014
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Importance Sampling Squared for Bayesian Inference in Latent Variable Models
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Discussion on constructing summary statistics for approximate Bayesian computation
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