Predicting the output from a complex computer code when fast approximations are available

• 成果类型: Article
• 署名作者: Kennedy, MC; O'Hagan, A
• 署名单位: University of Sheffield
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/87.1.1
• 发表日期: 2000
• 页码: 113
• 关键词: design

摘要

We consider prediction and uncertainty analysis for complex computer codes which can be run at different levels of sophistication. In particular, we wish to improve efficiency by combining expensive runs of the most complex versions of the code with relatively cheap runs from one or more simpler approximations. A Bayesian approach is described in which prior beliefs about the codes are represented in terms of Gaussian processes. An example is presented using two versions of an oil reservoir simulator.