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Bayes Linear Analysis for Complex Physical Systems Modeled by Computer Simulators

机译:计算机模拟器模拟复杂物理系统的贝叶斯线性分析

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Most large and complex physical systems are studied by mathematical models, implemented as high dimensional computer simulators. While all such cases differ in physical description, each analysis of a physical system based on a computer simulator involves the same underlying sources of uncertainty. These sources are defined and described below. In addition, there is a growing field of study which aims to quantify and synthesize all of the uncertainties involved in relating models to physical systems, within the framework of Bayesian statistics, and to use the resultant uncertainty specification to address problems of forecasting and decision making based on the application of these methods. We present an overview of the current status and future challenges in this emerging methodology, illustrating with examples drawn from current areas of application including: asset management for oil reservoirs, galaxy modeling, and rapid climate change.
机译:通过数学模型研究了最大和复杂的物理系统,实现为高维计算机模拟器。虽然所有这种情况在物理描述中不同,但是基于计算机模拟器的物理系统的每个分析涉及相同的不确定性源。下面定义和描述这些来源。此外,还有一种日益增长的研究领域,旨在量化和综合贝叶斯统计框架内与物理系统相关的所有不确定性,并使用所得的不确定性规范来解决预测和决策问题基于这些方法的应用。我们概述了该新兴方法中的当前状态和未来挑战的概述,示出了从当前申请领域汲取的示例,包括:用于储油机,银河系建模和快速气候变化的资产管理。

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