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. ( 8th Workshop on Uncertainty Processing (WUPES 09) Liblice, CZECH REPUBLIC 2009) [10.1016/j.ijar.2010.12.006].
Inferential models and relevant algorithms in a possibilistic framework
Petturiti, D.;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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
