Bayesian emulation of complex multi-output and dynamic computer models
Bayesian emulation of complex multi-output and dynamic computer models
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DOI：
10.1016/j.jspi.2009.08.006
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发表时间：
2010-03-01
影响因子：
0.9
通讯作者：
O'Hagan, Anthony
中科院分区：
文献类型：
--
作者：
Conti, Stefano;O'Hagan, Anthony
计算机模型在科学研究中被广泛用于研究和预测复杂系统的行为。计算机密集型模拟器的运行时间通常是这样的，以至于进行灵敏度分析通常需要的数千次模型运行是不切实际的。不确定度分析或校准。为了解决这个问题，最近开发了基于统计元模型（模拟器）的高效技术，该模型是为了近似计算机模型而构建的。然而，这种方法对于动态模拟器来说就不那么简单了。用来表示随时间变化的系统。这里提出并对比了已建立的允许动态仿真的方法的概括。通过英国陆地碳动力学中心开发的谢菲尔德动态全球植被模型的应用，讨论和说明了优点和困难。(C) 2009 Elsevier B.V.版权所有
Computer models are widely used in scientific research to study and predict the behaviour of complex systems. The run times of computer-intensive simulators are often such that it is impractical to make the thousands of model runs that are conventionally required for sensitivity analysis. uncertainty analysis or calibration. In response to this problem, highly efficient techniques have recently been developed based on a statistical meta-model (the emulator) that is built to approximate the computer model. The approach, however, is less straightforward for dynamic simulators. designed to represent time-evolving systems. Generalisations of the established methodology to allow for dynamic emulation are here proposed and contrasted. Advantages and difficulties are discussed and illustrated with an application to the Sheffield Dynamic Global Vegetation Model, developed within the UK Centre for Terrestrial Carbon Dynamics. (C) 2009 Elsevier B.V. All rights reserved.