Speeding up MCMC by Delayed Acceptance and Data Subsampling-Reference-Cited by-同舟云学术

Speeding up MCMC by Delayed Acceptance and Data Subsampling

Published:2017-07-28 Issue:1 Volume:27 Page:12-22
ISSN:1061-8600
Container-title:Journal of Computational and Graphical Statistics
language:en
Short-container-title:Journal of Computational and Graphical Statistics

Author:

Quiroz Matias¹²,Tran Minh-Ngoc³,Villani Mattias¹,Kohn Robert⁴

Affiliation:

1. Division of Statistics and Machine Learning, Linköping University, Linköping, Sweden

2. Research Division, Sveriges Riksbank, Stockholm, Sweden

3. Discipline of Business Analytics, University of Sydney, Camperdown NSW, Australia

4. Australian School of Business, University of New South Wales, Sydney NSW, Australia

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Discrete Mathematics and Combinatorics,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/10618600.2017.1307117

Reference43 articles.

1. The pseudo-marginal approach for efficient Monte Carlo computations

2. Banterle, M., Grazian, C., and Robert, C. P. (2014), “Accelerating Metropolis-Hastings Algorithms: Delayed Acceptance With Prefetching,” arXiv preprint arXiv:1406.2660.

3. ——— (2015), “On Markov Chain Monte Carlo Methods for Tall Data,” arXiv preprint arXiv:1505.02827.

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