基于物理过程模型的逆问题

IF 7.4 1区数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Annual Review of Statistics and Its Application Pub Date : 2023-08-16 DOI:10.1146/annurev-statistics-031017-100108

D. Bingham, T. Butler, D. Estep

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引用次数: 0

摘要

在不确定性和随机变异性的背景下，我们描述并比较了基于物理的过程模型的两种反问题:贝叶斯反问题和随机反问题。我们描述了这两个问题的基础，以便为解释对科学和工程推理重要的逆问题的适用性和解决方案创造一个背景。最后，我们将它们与相关问题的统计方法进行比较，包括计算机模型的贝叶斯校准。预计《统计年鉴及其应用》第11卷的最终在线出版日期为2024年3月。修订后的估计数请参阅http://www.annualreviews.org/page/journal/pubdates。

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Inverse Problems for Physics-Based Process Models

We describe and compare two formulations of inverse problems for a physics-based process model in the context of uncertainty and random variability: the Bayesian inverse problem and the stochastic inverse problem. We describe the foundations of the two problems in order to create a context for interpreting the applicability and solutions of inverse problems important for scientific and engineering inference. We conclude by comparing them to statistical approaches to related problems, including Bayesian calibration of computer models. Expected final online publication date for the Annual Review of Statistics and Its Application, Volume 11 is March 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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来源期刊

Annual Review of Statistics and Its Application MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY

CiteScore

13.40

自引率

1.30%

发文量

期刊介绍： The Annual Review of Statistics and Its Application publishes comprehensive review articles focusing on methodological advancements in statistics and the utilization of computational tools facilitating these advancements. It is abstracted and indexed in Scopus, Science Citation Index Expanded, and Inspec.