Industrial Impact of Bayes Linear Analysis

Michael Goldstein ()
Additional contact information
Michael Goldstein: Durham University, Department of Mathematical Sciences

A chapter in UK Success Stories in Industrial Mathematics, 2016, pp 91-97 from Springer

Abstract: Abstract Bayesian statistics plays a crucial role in the quantification of uncertainty for complex industrial problems. We discuss practical issues with the implementation of this approach, and explain the role of Bayes linear methodology in addressing such problems. We then discuss ways in which the Bayes linear approach has been implemented in industrial practice. We choose three areas of research and application to describe this impact. In each case, we review the underpinning technical research and then discuss the application. The chosen areas of impact are asset management, with reference to work by London Underground Ltd., chemical sensitisation analysis, with reference to methodology applied by Unilever and FERA, and reservoir engineering, with reference to software for history maching for reservoir simulators.

Keywords: Allergic Contact Dermatitis; History Match; Asset Management; Gaussian Graphical Model; Cinnamic Aldehyde (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-25454-8_12

Ordering information: This item can be ordered from
http://www.springer.com/9783319254548

DOI: 10.1007/978-3-319-25454-8_12

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().