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Proper local scoring rules on discrete sample spaces

Abstract:

A scoring rule is a loss function measuring the quality of a quoted probability distribution $Q$ for a random variable $X$, in the light of the realized outcome $x$ of $X$; it is proper if the expected score, under any distribution $P$ for $X$, is minimized by quoting $Q=P$. Using the fact that any differentiable proper scoring rule on a finite sample space ${\mathcal{X}}$ is the gradient of a concave homogeneous function, we consider when such a rule can be local in the sense of depending on...

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Publication status:
Published

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Publisher copy:
10.1214/12-AOS972

Authors


Journal:
Annals of Statistics
Volume:
40
Issue:
1
Pages:
593-608
Publication date:
2011-04-12
DOI:
ISSN:
0090-5364
Source identifiers:
184650
Language:
English
Keywords:
Pubs id:
pubs:184650
UUID:
uuid:e7763430-4966-4c60-ba65-1bb45b7a2b73
Local pid:
pubs:184650
Deposit date:
2012-12-19

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