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Simultaneous Determination of Tuning and Calibration Parameters for Computer Experiments.
Han, Gang; Santner, Thomas J; Rawlinson, Jeremy J.
Afiliación
  • Han G; H. Lee Moffitt Cancer Center & Research Institute, MRC/BIOSTAT, 12902 Magnolia Drive, Tampa, FL 33612, ( gang.han@moffitt.org ).
Technometrics ; 51(4): 464-474, 2009 Nov 01.
Article en En | MEDLINE | ID: mdl-20523754
Tuning and calibration are processes for improving the representativeness of a computer simulation code to a physical phenomenon. This article introduces a statistical methodology for simultaneously determining tuning and calibration parameters in settings where data are available from a computer code and the associated physical experiment. Tuning parameters are set by minimizing a discrepancy measure while the distribution of the calibration parameters are determined based on a hierarchical Bayesian model. The proposed Bayesian model views the output as a realization of a Gaussian stochastic process with hyperpriors. Draws from the resulting posterior distribution are obtained by the Markov chain Monte Carlo simulation. Our methodology is compared with an alternative approach in examples and is illustrated in a biomechanical engineering application. Supplemental materials, including the software and a user manual, are available online and can be requested from the first author.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Technometrics Año: 2009 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Technometrics Año: 2009 Tipo del documento: Article Pais de publicación: Estados Unidos