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Pseudo-marginal Metropolis–Hastings sampling using averages of unbiased estimators

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  • Chris Sherlock
  • Alexandre H. Thiery
  • Anthony Lee

Abstract

SummaryWe consider a pseudo-marginal Metropolis–Hastings kernel ${\mathbb{P}}_m$ that is constructed using an average of $m$ exchangeable random variables, and an analogous kernel ${\mathbb{P}}_s$ that averages $s

Suggested Citation

  • Chris Sherlock & Alexandre H. Thiery & Anthony Lee, 2017. "Pseudo-marginal Metropolis–Hastings sampling using averages of unbiased estimators," Biometrika, Biometrika Trust, vol. 104(3), pages 727-734.
    • Handle: RePEc:oup:biomet:v:104:y:2017:i:3:p:727-734.
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    File URL: http://hdl.handle.net/10.1093/biomet/asx031
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    Cited by:

    1. Franks, Jordan & Vihola, Matti, 2020. "Importance sampling correction versus standard averages of reversible MCMCs in terms of the asymptotic variance," Stochastic Processes and their Applications, Elsevier, vol. 130(10), pages 6157-6183.
    2. Farmer, J. Doyne & Dyer, Joel & Cannon, Patrick & Schmon, Sebastian, 2022. "Black-box Bayesian inference for economic agent-based models," INET Oxford Working Papers 2022-05, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    3. Matti Vihola & Jouni Helske & Jordan Franks, 2020. "Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1339-1376, December.

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