Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations

Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations

We construct a new framework for accelerating Markov chain Monte Carlo in posterior sampling problems where standard methods are limited by the computational cost of the likelihood, or of numerical models embedded therein. Our approach introduces local approximations of these models into the Metropo...

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Bibliographic Details
Main Authors: Conrad, Patrick R., Marzouk, Youssef M., Pillai, Natesh S., Smith, Aaron
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Format: Article
Language:en_US
Published: American Statistical Association 2015
Online Access:http://hdl.handle.net/1721.1/99937
https://orcid.org/0000-0001-8242-3290

Internet

http://hdl.handle.net/1721.1/99937
https://orcid.org/0000-0001-8242-3290

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