 STEP 2: QuantifyEduard Hofer Chapter Chapter 3 in The Uncertainty Analysis of Model Results, 2018, pp 21-148 from Springer Abstract: Abstract This is the most important and most laborious analysis step. Its task is to express quantitatively what is known about each of the possibly important uncertainties of the computer model application. In other words, the task is to quantify the so-called state of knowledge. Subjective probability is the appropriate mathematical concept for state of knowledge quantifications. Section 3.1 briefly introduces this concept. Section 3.2 explains distinctions between data and model uncertainties that are important in the state of knowledge quantification. Ways to quantify the state of knowledge for uncertain data are presented in Sect. 3.3 while Sect. 3.4 presents those for model uncertainties. The subjects of Sect. 3.5 are the concept and sources of state of knowledge dependence together with ways of its quantification. The elicitation of the state of knowledge from experts and the corresponding probabilistic modelling are discussed in Sect. 3.6 for data as well as for models. Finally, Sect. 3.7 deals with the question of when and how to conduct a survey of expert opinion in order to arrive at state of knowledge quantifications that are supported by a broad base of expertise. Date: 2018 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-76297-5_3 Ordering information: This item can be ordered from DOI: 10.1007/978-3-319-76297-5_3 Access Statistics for this chapter More chapters in Springer Books from Springer |
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