On the closure of aggregation rules for imprecise probabilities

Enrique Miranda, Ignacio Montes
Proceedings of the Fourteenth International Symposium on Imprecise Probabilities: Theories and Applications, PMLR 290:196-206, 2025.

Abstract

We consider the problem of aggregating a number of imprecise probability models into a joint one, and compare four aggregation rules: conjunction, disjunction, mixture and Pareto. We investigate for which particular cases of imprecise probability models these operators are closed, meaning that the output belongs to the same family as the inputs. Specifically, we analyse this problem for comparative probability models, $2$-monotone capacities, probability intervals, belief functions, p-boxes and minitive measures.

Cite this Paper

BibTeX
@InProceedings{pmlr-v290-miranda25a, title = {On the closure of aggregation rules for imprecise probabilities}, author = {Miranda, Enrique and Montes, Ignacio}, booktitle = {Proceedings of the Fourteenth International Symposium on Imprecise Probabilities: Theories and Applications}, pages = {196--206}, year = {2025}, editor = {Destercke, Sébastien and Erreygers, Alexander and Nendel, Max and Riedel, Frank and Troffaes, Matthias C. M.}, volume = {290}, series = {Proceedings of Machine Learning Research}, month = {15--18 Jul}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v290/main/assets/miranda25a/miranda25a.pdf}, url = {https://proceedings.mlr.press/v290/miranda25a.html}, abstract = {We consider the problem of aggregating a number of imprecise probability models into a joint one, and compare four aggregation rules: conjunction, disjunction, mixture and Pareto. We investigate for which particular cases of imprecise probability models these operators are closed, meaning that the output belongs to the same family as the inputs. Specifically, we analyse this problem for comparative probability models, $2$-monotone capacities, probability intervals, belief functions, p-boxes and minitive measures.} }
Endnote
%0 Conference Paper %T On the closure of aggregation rules for imprecise probabilities %A Enrique Miranda %A Ignacio Montes %B Proceedings of the Fourteenth International Symposium on Imprecise Probabilities: Theories and Applications %C Proceedings of Machine Learning Research %D 2025 %E Sébastien Destercke %E Alexander Erreygers %E Max Nendel %E Frank Riedel %E Matthias C. M. Troffaes %F pmlr-v290-miranda25a %I PMLR %P 196--206 %U https://proceedings.mlr.press/v290/miranda25a.html %V 290 %X We consider the problem of aggregating a number of imprecise probability models into a joint one, and compare four aggregation rules: conjunction, disjunction, mixture and Pareto. We investigate for which particular cases of imprecise probability models these operators are closed, meaning that the output belongs to the same family as the inputs. Specifically, we analyse this problem for comparative probability models, $2$-monotone capacities, probability intervals, belief functions, p-boxes and minitive measures.
APA
Miranda, E. & Montes, I.. (2025). On the closure of aggregation rules for imprecise probabilities. Proceedings of the Fourteenth International Symposium on Imprecise Probabilities: Theories and Applications, in Proceedings of Machine Learning Research 290:196-206 Available from https://proceedings.mlr.press/v290/miranda25a.html.

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