Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations-Reference-Cited by-同舟云学术

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Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations

Published:2016-10-01 Issue:516 Volume:111 Page:1591-1607
ISSN:0162-1459
Container-title:Journal of the American Statistical Association
language:en
Short-container-title:Journal of the American Statistical Association

Author:

Conrad Patrick R.¹,Marzouk Youssef M.¹,Pillai Natesh S.²,Smith Aaron³

Affiliation:

1. Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, USA

2. Department of Statistics, Harvard University, Cambridge, MA, USA

3. Department of Mathematics and Statistics, University of Ottawa, Ottawa, Canada

Publisher

Informa UK Limited

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/01621459.2015.1096787

Reference50 articles.

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

2. Bayesian inverse problems with Monte Carlo forward models

3. Local Derivative-Free Approximation of Computationally Expensive Posterior Densities

4. Bayesian Calibration and Uncertainty Analysis for Computationally Expensive Models Using Optimization and Radial Basis Function Approximation

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