A continuous updating rule for imprecise probabilities

Cattaneo, Marco E. G. V.

Abstract

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.

Citation

Cattaneo, M. E. G. V. (2014). A. Laurent, O. Strauss, B. Bouchon-Meunier, & R. Yager (Eds.), A continuous updating rule for imprecise probabilities. Springer Verlag. https://doi.org/10.1007/978-3-319-08852-5_44

• Book Type: Book Chapter
• Publication Date: Jan 1, 2014
• Deposit Date: Jun 29, 2018
• 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
• DOI: https://doi.org/10.1007/978-3-319-08852-5_44
• Keywords: Coherent lower and upper previsions; Natural extension; Regular extension; α-cut robustness; Hausdorff distance
• Public URL: https://hull-repository.worktribe.com/output/901299
• Publisher URL: https://link.springer.com/chapter/10.1007%2F978-3-319-08852-5_44