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September 2015 Calibrating a large computer experiment simulating radiative shock hydrodynamics
Robert B. Gramacy, Derek Bingham, James Paul Holloway, Michael J. Grosskopf, Carolyn C. Kuranz, Erica Rutter, Matt Trantham, R. Paul Drake
Ann. Appl. Stat. 9(3): 1141-1168 (September 2015). DOI: 10.1214/15-AOAS850


We consider adapting a canonical computer model calibration apparatus, involving coupled Gaussian process (GP) emulators, to a computer experiment simulating radiative shock hydrodynamics that is orders of magnitude larger than what can typically be accommodated. The conventional approach calls for thousands of large matrix inverses to evaluate the likelihood in an MCMC scheme. Our approach replaces that costly ideal with a thrifty take on essential ingredients, synergizing three modern ideas in emulation, calibration and optimization: local approximate GP regression, modularization, and mesh adaptive direct search. The new methodology is motivated both by necessity—considering our particular application—and by recent trends in the supercomputer simulation literature. A synthetic data application allows us to explore the merits of several variations in a controlled environment and, together with results on our motivating real-data experiment, lead to noteworthy insights into the dynamics of radiative shocks as well as the limitations of the calibration enterprise generally.


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Robert B. Gramacy. Derek Bingham. James Paul Holloway. Michael J. Grosskopf. Carolyn C. Kuranz. Erica Rutter. Matt Trantham. R. Paul Drake. "Calibrating a large computer experiment simulating radiative shock hydrodynamics." Ann. Appl. Stat. 9 (3) 1141 - 1168, September 2015.


Received: 1 October 2014; Revised: 1 June 2015; Published: September 2015
First available in Project Euclid: 2 November 2015

zbMATH: 06525981
MathSciNet: MR3418718
Digital Object Identifier: 10.1214/15-AOAS850

Rights: Copyright © 2015 Institute of Mathematical Statistics


Vol.9 • No. 3 • September 2015
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