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Title: Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations

Abstract

Not provided.

Authors:
 [1];  [1];  [2];  [3]
  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
Publication Date:
Research Org.:
Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1535376
DOE Contract Number:  
SC0007099
Resource Type:
Journal Article
Journal Name:
Journal of the American Statistical Association
Additional Journal Information:
Journal Volume: 111; Journal Issue: 516; Journal ID: ISSN 0162-1459
Publisher:
Taylor & Francis
Country of Publication:
United States
Language:
English
Subject:
Mathematics

Citation Formats

Conrad, Patrick R., Marzouk, Youssef M., Pillai, Natesh S., and Smith, Aaron. Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations. United States: N. p., 2016. Web. doi:10.1080/01621459.2015.1096787.
Conrad, Patrick R., Marzouk, Youssef M., Pillai, Natesh S., & Smith, Aaron. Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations. United States. doi:10.1080/01621459.2015.1096787.
Conrad, Patrick R., Marzouk, Youssef M., Pillai, Natesh S., and Smith, Aaron. Sat . "Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations". United States. doi:10.1080/01621459.2015.1096787.
@article{osti_1535376,
title = {Accelerating Asymptotically Exact MCMC for Computationally Intensive Models via Local Approximations},
author = {Conrad, Patrick R. and Marzouk, Youssef M. and Pillai, Natesh S. and Smith, Aaron},
abstractNote = {Not provided.},
doi = {10.1080/01621459.2015.1096787},
journal = {Journal of the American Statistical Association},
issn = {0162-1459},
number = 516,
volume = 111,
place = {United States},
year = {2016},
month = {10}
}