We provide a general inferential procedure based on coherent conditional possibilities and we show, by some examples, its possible use in medical diagnosis. In particular, the role of the likelihood in possibilistic setting is discussed and once the coherence of prior possibility and likelihood is checked, we update prior possibilities. (C) 2011 Elsevier Inc. All rights reserved.

Inferential models and relevant algorithms in a possibilistic framework / Baioletti, M.; Coletti, G.; Petturiti, D.; Vantaggi, Barbara. - In: INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. - ISSN 0888-613X. - STAMPA. - 52:5(2011), pp. 580-598. (Intervento presentato al convegno 8th Workshop on Uncertainty Processing (WUPES 09) tenutosi a Liblice, CZECH REPUBLIC nel 2009) [10.1016/j.ijar.2010.12.006].

Inferential models and relevant algorithms in a possibilistic framework

VANTAGGI, Barbara
2011

Abstract

We provide a general inferential procedure based on coherent conditional possibilities and we show, by some examples, its possible use in medical diagnosis. In particular, the role of the likelihood in possibilistic setting is discussed and once the coherence of prior possibility and likelihood is checked, we update prior possibilities. (C) 2011 Elsevier Inc. All rights reserved.
2011
inference; possibility; probability; coherence; likelihood
01 Pubblicazione su rivista::01a Articolo in rivista
Inferential models and relevant algorithms in a possibilistic framework / Baioletti, M.; Coletti, G.; Petturiti, D.; Vantaggi, Barbara. - In: INTERNATIONAL JOURNAL OF APPROXIMATE REASONING. - ISSN 0888-613X. - STAMPA. - 52:5(2011), pp. 580-598. (Intervento presentato al convegno 8th Workshop on Uncertainty Processing (WUPES 09) tenutosi a Liblice, CZECH REPUBLIC nel 2009) [10.1016/j.ijar.2010.12.006].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/376783
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