Talks and Poster Presentations (without Proceedings-Entry):
R. Viertl, S. Taheri, M. Arefi:
"Possibilistic Bayesian Models";
Talk: WSC 2013 59th ISI Statistics World Congress,
Hong Kong, China;
2013-08-25
- 2013-08-30.
English abstract:
The problem of modeling and analyzing fuzzy data is investigated in a
possibilistic context, based on a Bayesian approach. Specially, we focus on the problem of point estimation when the available data of the underlying statistical model are fuzzy rather than crisp. To do this, first we extend the concept of likelihood function to fuzzy data. Then, to obtain the point estimation, we develop a method without considering a loss function and one considering a loss function based on a possibilistic posterior distribution. A few
numerical examples are presented to explain the applicability of the proposed approach.
Keywords:
Bayes approach Likelihood function Point estimation Possibilistic posterior distribution Possibility measure
Electronic version of the publication:
http://www.isi2013.hk/en/scientific_list_Aug_29.php
Created from the Publication Database of the Vienna University of Technology.