Fetching the paper…
Reading the bibliography…
When an unbiased estimator of the likelihood is used within a Metropolis--Hastings chain, it is necessary to trade off the number of Monte Carlo samples used to construct this estimator against the asymptotic variances of averages computed under this chain.
Optimum Monte–Carlo sampling using Markov chains
Peskun, P. H · 1973
Earlier work this paper cites.
Central limit theorem for additive functionals of reversible Markov processes and applications to simple exclusions
Kipnis, C · 1986
Earlier work this paper cites.
Markov Chains and Stochastic Stability
Meyn, S · 1991
Earlier work this paper cites.
Functional Analysis
Rudin, W · 1991
Earlier work this paper cites.
Practical Markov chain Monte Carlo
Geyer, C. J · 1992
Earlier work this paper cites.
Markov chains for exploring posterior distributions (with discussion)
Tierney, L · 1994
Earlier work this paper cites.
Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms
Roberts, G · 1996
Earlier work this paper cites.
A note on Metropolis–Hastings kernels for general state spaces
Tierney, L · 1998
Earlier work this paper cites.
A noisy Monte Carlo algorithm
Lin, L · 2000
Cited alongside, same era.
Estimation of population growth or decline in genetically monitored populations
Beaumont, M · 2003
Cited alongside, same era.
Alternative models of stock price dynamics
Chernov, M · 2003
Cited alongside, same era.
Martingale approximations for sums of stationary processes
Wu, W · 2004
Cited alongside, same era.
Renewal theory and computable convergence rates for geometrically ergodic Markov chains
Baxendale, P · 2005
Cited alongside, same era.
The relative contribution of jumps to total price variation
Huang, X · 2005
Cited alongside, same era.
Particle Markov chain Monte Carlo methods
Andrieu, C · 2010
Later among the works it cites.
A vanilla Rao–Blackwellization of Metropolis–Hastings algorithms
Douc, R · 2011
Later among the works it cites.
Convergence properties of pseudo-marginal Markov Chain Monte Carlo algorithms
Andrieu, C · 2012
Closest in time.
On some properties of Markov chain Monte Carlo simulation methods based on the particle filter
Pitt, M. K · 2012
Closest in time.
Unbounded Self-adjoint Operators on Hilbert Space
Schmüdgen, K · 2012
Closest in time.
Positivity of hit-and-run and related algorithms
Rudolf, D · 2013
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Häggström, O · 2007
Cited alongside, same era.
The pseudo-marginal approach for efficient Monte Carlo computations
Andrieu, C · 2009
Cited alongside, same era.
Sherlock, C · 2013
Closest in time.
Establishing some order amongst exact approximations of MCMCs, arXiv:1404.6909
Andrieu, C · 2014
Closest in time.