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Adaptive Multiple Importance Sampling

Author

Listed:
  • JEAN-MARIE CORNUET
  • JEAN-MICHEL MARIN
  • ANTONIETTA MIRA
  • CHRISTIAN P. ROBERT

Abstract

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Suggested Citation

  • Jean-Marie Cornuet & Jean-Michel Marin & Antonietta Mira & Christian P. Robert, 2012. "Adaptive Multiple Importance Sampling," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 39(4), pages 798-812, December.
    • Handle: RePEc:bla:scjsta:v:39:y:2012:i:4:p:798-812
    DOI: j.1467-9469.2011.00756.x
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    Citations

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    Cited by:

    1. Chris J. Oates & Mark Girolami & Nicolas Chopin, 2017. "Control functionals for Monte Carlo integration," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(3), pages 695-718, June.
    2. Liseo, Brunero & Parisi, Antonio, 2013. "Bayesian inference for the multivariate skew-normal model: A population Monte Carlo approach," Computational Statistics & Data Analysis, Elsevier, vol. 63(C), pages 125-138.
    3. L. Martino & F. Louzada, 2017. "Issues in the Multiple Try Metropolis mixing," Computational Statistics, Springer, vol. 32(1), pages 239-252, March.
    4. Tatiana Dmitrieva & Kristin McCullough & Nader Ebrahimi, 2021. "Improved approximate Bayesian computation methods via empirical likelihood," Computational Statistics, Springer, vol. 36(2), pages 1533-1552, June.
    5. Chaudhuri, Anirban & Kramer, Boris & Willcox, Karen E., 2020. "Information Reuse for Importance Sampling in Reliability-Based Design Optimization," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    6. Qiyun Pan & Eunshin Byon & Young Myoung Ko & Henry Lam, 2020. "Adaptive importance sampling for extreme quantile estimation with stochastic black box computer models," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(7), pages 524-547, October.
    7. Filippi Sarah & Barnes Chris P. & Cornebise Julien & Stumpf Michael P.H., 2013. "On optimality of kernels for approximate Bayesian computation using sequential Monte Carlo," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(1), pages 87-107, March.
    8. Yalei Yang & Hao Gao & Colin Berry & David Carrick & Aleksandra Radjenovic & Dirk Husmeier, 2022. "Classification of myocardial blood flow based on dynamic contrast‐enhanced magnetic resonance imaging using hierarchical Bayesian models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1085-1115, November.
    9. Christian P. Robert & Gareth Roberts, 2021. "Rao–Blackwellisation in the Markov Chain Monte Carlo Era," International Statistical Review, International Statistical Institute, vol. 89(2), pages 237-249, August.
    10. Shields, Michael D., 2018. "Adaptive Monte Carlo analysis for strongly nonlinear stochastic systems," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 207-224.

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