Composite grid designs for adaptive computer experiments with fast inference

Matthew Plumlee, C. B. Erickson, B. E. Ankenman, E. Lawrence

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Experiments are often used to produce emulators of deterministic computer code. This article introduces composite grid experimental designs and a sequential method for building the designs for accurate emulation. Computational methods are developed that enable fast and exact Gaussian process inference even with large sample sizes. We demonstrate that the proposed approach can produce emulators that are orders of magnitude more accurate than current approximations at a comparable computational cost.

Original languageEnglish (US)
Pages (from-to)749-755
Number of pages7
JournalBiometrika
Volume108
Issue number3
DOIs
StatePublished - Sep 1 2021

Keywords

  • Emulation
  • Gaussian process
  • Kriging
  • Sequential experiment
  • Sparse grid

ASJC Scopus subject areas

  • Statistics and Probability
  • General Mathematics
  • Agricultural and Biological Sciences (miscellaneous)
  • General Agricultural and Biological Sciences
  • Statistics, Probability and Uncertainty
  • Applied Mathematics

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