A generalized Bayesian inference framework in order to embed fuzzy sets and partial probabilistic information is provided. The general framework of reference is that of coherent conditional probabilities, which allows giving a rigorous interpretation of membership function as a conditional probability, regarded as a function of the conditioning event. The inferential problem needs to be studied in situations where the prior can be partial: moreover, membership and prior can be given on different classes of events. This inferential model is applied for the virtual representation of a female avatar. (C) 2011 Elsevier B.V. All rights reserved.
Generalized Bayesian inference in a fuzzy context: From theory to a virtual reality application / Giulianella, Coletti; Osvaldo, Gervasi; Sergio, Tasso; Vantaggi, Barbara. - In: COMPUTATIONAL STATISTICS & DATA ANALYSIS. - ISSN 0167-9473. - STAMPA. - 56:4(2012), pp. 967-980. [10.1016/j.csda.2011.06.020]
Generalized Bayesian inference in a fuzzy context: From theory to a virtual reality application
VANTAGGI, Barbara
2012
Abstract
A generalized Bayesian inference framework in order to embed fuzzy sets and partial probabilistic information is provided. The general framework of reference is that of coherent conditional probabilities, which allows giving a rigorous interpretation of membership function as a conditional probability, regarded as a function of the conditioning event. The inferential problem needs to be studied in situations where the prior can be partial: moreover, membership and prior can be given on different classes of events. This inferential model is applied for the virtual representation of a female avatar. (C) 2011 Elsevier B.V. All rights reserved.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
