Simultaneous Determination of Tuning and Calibration Parameters for Computer Experiments.
Simultaneous Determination of Tuning and Calibration Parameters for Computer Experiments.
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DOI：
10.1198/tech.2009.08126
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发表时间：
2009-11-01
期刊：
影响因子：
--
通讯作者：
Rawlinson JJ
中科院分区：
文献类型：
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作者：
Han G;Santner TJ;Rawlinson JJ
调整和校准是用于提高计算机模拟代码对物理现象的代表性的过程。本文介绍了一种统计方法，用于在可从计算机代码和相关物理实验获得数据的设置中同时确定调谐和校准参数。通过最小化差异度量来设置调谐参数，而基于分层贝叶斯模型来确定校准参数的分布。所提出的贝叶斯模型将输出视为具有超先验的高斯随机过程的实现。通过马尔可夫链蒙特卡罗模拟得到后验分布的拉伸值。我们的方法与另一种方法在实例中进行了比较，并在生物力学工程应用中进行了说明。补充材料，包括软件和用户手册，可在网上获得，并可向第一作者索要。
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.