Diagnostics for Gaussian Process Emulators
Diagnostics for Gaussian Process Emulators
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DOI：
10.1198/tech.2009.08019
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发表时间：
2009-11-01
期刊：
影响因子：
2.5
通讯作者：
O'Hagan, Anthony
中科院分区：
文献类型：
--
作者：
Bastos, Leonardo S.;O'Hagan, Anthony
数学模型，通常在称为模拟器的计算机程序中实现，广泛用于科学和技术的所有领域，以表示复杂的现实世界现象。模拟器通常非常复杂，以至于它们需要相当多的计算机时间或其他资源来运行。在这种情况下，已经开发了一种方法的基础上建立一个统计表示的模拟器，称为仿真器。构建仿真器的主要方法是使用高斯过程。这项工作提出了一些诊断，以验证和评估充分的高斯过程模拟器作为替代的模拟器。这些诊断是基于模拟器输出和高斯过程模拟器输出之间的比较，用于一些测试数据，称为验证数据，由不用于构建模拟器的模拟器运行的样本定义。我们的诊断注意考虑验证数据之间的相关性。为了说明验证过程，我们将这些诊断应用于两个不同的数据集。
Mathematical models, usually implemented in computer programs known as simulators, are widely used in all areas of science and technology to represent complex real-world phenomena. Simulators are often so complex that they take appreciable amounts of computer time or other resources to run. In this context, a methodology has been developed based on building a statistical representation of the simulator, known as an emulator. The principal approach to building emulators uses Gaussian processes. This work presents some diagnostics to validate and assess the adequacy of a Gaussian process emulator as surrogate for the simulator. These diagnostics are based on comparisons between simulator outputs and Gaussian process emulator outputs for some test data, known as validation data, defined by a sample of simulator runs not used to build the emulator. Our diagnostics take care to account for correlation between the validation data. To illustrate a validation procedure, we apply these diagnostics to two different data sets.