by Veronica Biazzo, Angelo Gilio, Giuseppe Sanfilippo
Abstract:
In this paper we study the relationship between the notion of coherence for conditional prevision assessments on a family of finite conditional random quantities and the notion of admissibility with respect to bounded strictly proper scoring rules. Our work extends recent results given by the last two authors of this paper on the equivalence between coherence and admissibility for conditional probability assessments. In order to prove that admissibility implies coherence a key role is played by the notion of Bregman divergence.
Reference:
Veronica Biazzo, Angelo Gilio, Giuseppe Sanfilippo, "Coherent Conditional Previsions and Proper Scoring Rules", Chapter in Advances in Computational Intelligence, Communications in Computer and Information Science, Springer, vol. 300, pp. 146-156, 2012. ([A
version similar to the published paper])
Bibtex Entry:
@INCOLLECTION{2012:3IPMU,
author = {Veronica Biazzo and Angelo Gilio and Giuseppe Sanfilippo},
title = {Coherent Conditional Previsions and Proper Scoring Rules},
booktitle = {Advances in Computational Intelligence},
publisher = {Springer},
year = {2012},
editor = {Salvatore Greco and Bernadette Bouchon-Meunier and Giulianella Coletti
and Mario Fedrizzi and Benedetto Matarazzo and Ronald R. Yager},
volume = {300},
series = {Communications in Computer and Information Science},
pages = {146--156},
note = {ISBN:978-3-642-31723-1},
abstract = {In this paper we study the relationship between the notion of coherence
for conditional prevision assessments on a family of finite conditional
random quantities and the notion of admissibility with respect to
bounded strictly proper scoring rules. Our work extends recent results
given by the last two authors of this paper on the equivalence between
coherence and admissibility for conditional probability assessments.
In order to prove that admissibility implies coherence a key role
is played by the notion of Bregman divergence.},
comment = {<a href="http://sites.unipa.it/sanfilippo/pdf/2012/ipmu/IPMU2012_quasiversion.pdf">[A
version similar to the published paper]</a>},
doi = {10.1007/978-3-642-31724-8_16},
isbn = {978-3-642-31723-1},
issn = {1865-0929},
location = {Heidelberg},
scopus = {{2-s2.0-84868266864}},
url = {http://www.springer.com/computer/ai/book/978-3-642-31723-1}
}