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Utilizing Surrogate...
Utilizing Surrogate Numbers for Probability Elicitation
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- Danielson, Mats (författare)
- Stockholms universitet,Institutionen för data- och systemvetenskap
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- Ekenberg, Love (författare)
- Stockholms universitet,Institutionen för data- och systemvetenskap
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- Paulsson, Andreas (författare)
- Stockholms universitet,Institutionen för data- och systemvetenskap
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(creator_code:org_t)
- 2018-09-19
- 2018
- Engelska.
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Ingår i: Decision Making. - : IntechOpen. - 9781789237955 - 9781789237962 ; , s. 39-56
- Relaterad länk:
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https://doi.org/10.5...
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Abstract
Ämnesord
Stäng
- Comparatively few of the vast number of suggested decision-analytical methods have been widely spread in actual practice. The majority of those methods call for exact and accurate numbers as input, which could be one of several reasons for this lack of actual use; people frequently seem to be unfamiliar with, or reluctant to express those, in a sense, “true” values required. Many alternative methods to resolve this complication have been suggested over the years, including procedures for dealing with incomplete information. One way, which has proliferated for a while, is to introduce so-called surrogate numbers in the form of ordinal ranking methods for multi-criteria weights. In this chapter, we show how those can be adapted for use in probability elicitation. Furthermore, when decision-makers possess more information regarding the relative strengths of probabilities, that is, some form of cardinality, the input information to ordinal methods is sometimes too restricted. Therefore, we suggest a testing methodology and analyze the relevance of a set of cardinal ordering methods in addition to the ordinal ones.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
Nyckelord
- decision analysis
- probability elicitation
- cardinal ranking
- rank order
- imprecise probability
- Computer and Systems Sciences
- data- och systemvetenskap
Publikations- och innehållstyp
- vet (ämneskategori)
- kap (ämneskategori)
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