Vertical barrier models as unified distortions

Enrique Miranda, Renato Pelessoni, Paolo Vicig
Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications, PMLR 215:333-343, 2023.

Abstract

Vertical Barrier Models (VBM) are a family of imprecise probability models that generalise a number of well known distortion/neighbourhood models (such as the Pari-Mutuel Model, the Linear-Vacuous Model, and others) while still being relatively simple. Several of their properties were established by Pelessoni, Vicig, and Corsato. In this paper we explore, in a finite framework, further facets of these models: their interpretation as neighbourhood models, the structure of their credal set in terms of maximum number of its extreme points, the result of merging operations with VBMs, conditions for VBMs to be belief functions or possibility measures.

Cite this Paper

BibTeX
@InProceedings{pmlr-v215-miranda23b, title = {Vertical barrier models as unified distortions}, author = {Miranda, Enrique and Pelessoni, Renato and Vicig, Paolo}, booktitle = {Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications}, pages = {333--343}, year = {2023}, editor = {Miranda, Enrique and Montes, Ignacio and Quaeghebeur, Erik and Vantaggi, Barbara}, volume = {215}, series = {Proceedings of Machine Learning Research}, month = {11--14 Jul}, publisher = {PMLR}, pdf = {https://proceedings.mlr.press/v215/miranda23b/miranda23b.pdf}, url = {https://proceedings.mlr.press/v215/miranda23b.html}, abstract = {Vertical Barrier Models (VBM) are a family of imprecise probability models that generalise a number of well known distortion/neighbourhood models (such as the Pari-Mutuel Model, the Linear-Vacuous Model, and others) while still being relatively simple. Several of their properties were established by Pelessoni, Vicig, and Corsato. In this paper we explore, in a finite framework, further facets of these models: their interpretation as neighbourhood models, the structure of their credal set in terms of maximum number of its extreme points, the result of merging operations with VBMs, conditions for VBMs to be belief functions or possibility measures.} }
Endnote
%0 Conference Paper %T Vertical barrier models as unified distortions %A Enrique Miranda %A Renato Pelessoni %A Paolo Vicig %B Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications %C Proceedings of Machine Learning Research %D 2023 %E Enrique Miranda %E Ignacio Montes %E Erik Quaeghebeur %E Barbara Vantaggi %F pmlr-v215-miranda23b %I PMLR %P 333--343 %U https://proceedings.mlr.press/v215/miranda23b.html %V 215 %X Vertical Barrier Models (VBM) are a family of imprecise probability models that generalise a number of well known distortion/neighbourhood models (such as the Pari-Mutuel Model, the Linear-Vacuous Model, and others) while still being relatively simple. Several of their properties were established by Pelessoni, Vicig, and Corsato. In this paper we explore, in a finite framework, further facets of these models: their interpretation as neighbourhood models, the structure of their credal set in terms of maximum number of its extreme points, the result of merging operations with VBMs, conditions for VBMs to be belief functions or possibility measures.
APA
Miranda, E., Pelessoni, R. & Vicig, P.. (2023). Vertical barrier models as unified distortions. Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications, in Proceedings of Machine Learning Research 215:333-343 Available from https://proceedings.mlr.press/v215/miranda23b.html.

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