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A continuous updating rule for imprecise probabilities

Cattaneo, Marco E. G. V.


Marco E. G. V. Cattaneo


A. Laurent

O. Strauss

B. Bouchon-Meunier

R.R. Yager


The paper studies the continuity of rules for updating imprecise probability models when new data are observed. Discontinuities can lead to robustness issues: this is the case for the usual updating rules of the theory of imprecise probabilities. An alternative, continuous updating rule is introduced. © Springer International Publishing Switzerland 2014.

Book Type Book Chapter
Publication Date Jan 1, 2014
Journal Communications in Computer and Information Science
Print ISSN 1865-0929
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 444 CCIS
Issue PART 3
Pages 426-435
Series ISSN 1865-0929
ISBN 9783319088518; 9783319088525
APA6 Citation Cattaneo, M. E. G. V. (2014). A. Laurent, O. Strauss, B. Bouchon-Meunier, & R. Yager (Eds.), A continuous updating rule for imprecise probabilities. BMC. doi:10.1007/978-3-319-08852-5_44
Keywords Coherent lower and upper previsions; Natural extension; Regular extension; α-cut robustness; Hausdorff distance
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