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How to exploit external model of data for parameter estimation?

Academic Article
Publication Date:
2006
abstract:
Any cooperation in multiple-participant decision making (DM) relies on an exchange of individual knowledge pieces and aims. A general methodology of their rational exploitation without calling for an objective mediator is still missing. Desired methodology is proposed for an important particular case, when a participant, performing Bayesian parameter estimation, is offered a model relating the observable data to their past history. The designed solution is based on the so-called fully probabilistic design (FPD) of DM strategies. The result reduces to an 'ordinary' Bayesian estimation if the offered model is the sample probability density function (pdf), i.e. if it provides additional observations.
Iris type:
01.01 Articolo in rivista
Keywords:
Bayesian estimation; decision making; fully probabilistic design; Kullback-Leibler
List of contributors:
Bodini, Antonella; Ruggeri, Fabrizio
Authors of the University:
BODINI ANTONELLA
Handle:
https://iris.cnr.it/handle/20.500.14243/52380
Published in:
INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING
Journal
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