Tuning Complex Computer Code to Data,

Abstract

The problem of estimating parameters in a complex computer simulator of a nuclear fusion reactor from an experimental database is treated. Practical limitations do not permit a standard statistical analysis using nonlinear regression methodology. The assumption that the function giving the true theoretical predictions is a realization of a Gaussian stochastic process provides a statistical method for combining information from relatively few computer runs with information from the experimental database and making inferences on the parameters.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1992
Accession Number
ADP007148

Entities

People

  • Clifford Singer
  • Dennis Cox
  • Jeong S. Park
  • Jerome Sacks

Organizations

  • University of Illinois Urbana–Champaign

Tags

DTIC Thesaurus Topics

  • Computer Science
  • Computers
  • Data Science
  • Databases
  • Information Science
  • Nuclear Fusion
  • Simulators
  • Statistical Analysis
  • Statistics
  • Stochastic Processes
  • Theoretical Computer Science

Readers

  • Computational Modeling and Simulation
  • Regression Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference