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This article has been bookmarked 2 times, initially on 2008-07-22.
| 2008-07-22 |
User mdreid
, 1 note
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This paper generalises the scoring rule weighted integral representation results of Schervish (as discussed in Buja et al. 2005) to the elicitation of properties of distributions.
They characterise which properties are "elicitable" - i.e., can be extracted from someone via a scoring rule - and show that these are precisely the properties that, for all values of the property, have convex level sets in the space of distributions.
Very nice paper!
2008-07-22 06:13:12
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Group Statistical Machine Learning
, 1 note
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|
This paper generalises the scoring rule weighted integral representation results of Schervish (as discussed in Buja et al. 2005) to the elicitation of properties of distributions.
They characterise which properties are "elicitable" - i.e., can be extracted from someone via a scoring rule - and show that these are precisely the properties that, for all values of the property, have convex level sets in the space of distributions.
Very nice paper!
2008-07-22 06:13:12
|
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