0507247 20240103222351.720190805235959.9 84988450716 000390837600060 10.1007/978-3-319-42972-4_60 8 s. P cav_un_epca*0507246978-3-319-42971-72194-5357487-494ChamSpringer2017FerraroM. B.GiordaniP.VantaggiB.GagolewskiM.GilM. Á.GrzegorzewskiP.HryniewiczOl. Credal Sets Multidimensional models Graphical Markov Models cav_un_auth*0101223 Vejnarová Jiřina Matematická teorie rozhodování Department of Decision Making Theory MTR MTR UTIA-B Department of Decision Making Theory Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2019/MTR/vejnarova-0507247.pdf cav_un_auth*0332303 GA16-12010S GA ČR CZ This paper is the second attempt to introduce the composition operator, already known from probability, possibility, evidence and valuation-based systems theories, also for credal sets. We try to avoid the discontinuity which was present in the original definition, but simultaneously to keep all the properties enabling us to design compositional models in a way analogous to those in the above-mentioned theories. These compositional models are aimed to be an alternative to Graphical Markov Models. Theoretical results achieved in this paper are illustrated by an example. cav_un_auth*0377913 International Conference on Soft Methods in Probability and Statistics-SMPS 2016 /8./ 20160912 20160914 Roma IT BA 10000 10100 10101 2020 1 PR RVO:67985556 http://hdl.handle.net/11104/0298572 S 60 3+4 Proceedings Paper Computer Science Artificial Intelligence|Robotics|Statistics Probability 3+4 Proceedings Paper Computer Science Artificial Intelligence|Robotics|Statistics Probability 3+4 Proceedings Paper Computer Science Artificial Intelligence|Robotics|Statistics Probability 2017 84988450716 SCOPUS PUBMED 000390837600060 WOS cav_un_epca*0507246 Soft Methods for Data Science Springer 2017 Cham 487 494 978-3-319-42971-7 Advances in Intelligent Systems and Computing 456 2194-5357 340 Ferraro M. B. 340 Giordani P. 340 Vantaggi B. 340 Gagolewski M. 340 Gil M. Á. 340 Grzegorzewski P. 340 Hryniewicz Ol.