Exclusive Content & Downloads from ASQ

Calibration of Stochastic Computer Simulators Using Likelihood Emulation

Summary: [This abstract is based on the authors' abstract.] We calibrate a stochastic computer simulation model of “moderate” computational expense. The simulator is an imperfect representation of reality, and we recognize this discrepancy to ensure a reliable calibration. The calibration model combines a Gaussian process emulator of the likelihood surface with importance sampling. Changing the discrepancy specification changes only the importance weights, which lets us investigate sensitivity to different discrepancy specifications at little computational cost. We present a case study of a natural history model that has been used to characterize UK bowel cancer incidence. Datasets and computer code are provided as supplementary material.

Please sign-in or register to download this information. Registration is FREE and gives you access to ASQ's articles, case studies and general information.

Other Ways to Access content:

Join ASQ

Join ASQ as a Full member. Enjoy all the ASQ member benefits including access to many online articles.

  • Topics: Design of Experiments, Software and Technology (for statistics, measurement, analysis), Statistics
  • Keywords: Experiments, Simulations, Calibration, Stochastic models, Sampling, Computers
  • Author: Oakley, Jeremy E.; Youngman, Benjamin D.
  • Journal: Technometrics