Extreme Inaccuracies In Gaussian Bayesian Networks

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dc.contributor.authorGómez Villegas, Miguel Ángel
dc.contributor.authorMain Yaque, Paloma
dc.contributor.authorSusi García, María Del Rosario
dc.date.accessioned2023-06-20T09:36:57Z
dc.date.available2023-06-20T09:36:57Z
dc.date.issued2008
dc.description.abstractTo evaluate the impact of model inaccuracies over the network’s output, after the evidence propagation, in a Gaussian Bayesian network, a sensitivity measure is introduced. This sensitivity measure is the Kullback–Leibler divergence and yields different expressions depending on the type of parameter to be perturbed, i.e. on the inaccurate parameter. In this work, the behavior of this sensitivity measure is studied when model inaccuracies are extreme,i.e. when extreme perturbations of the parameters can exist. Moreover, the sensitivity measure is evaluated for extreme situations of dependence between the main variables of the network and its behavior with extreme inaccuracies. This analysis is performed to find the effect of extreme uncertainty about the initial parameters of the model in a Gaussian Bayesian network and about extreme values of evidence. These ideas and procedures are illustrated with an example.en
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.sponsorshipMinisterio de Educación, Formación Profesional y Deportes (España)
dc.description.sponsorshipUniversidad Complutense de Madrid
dc.description.sponsorshipComunidad de Madrid
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/15831
dc.identifier.citationGómez Villegas, M. Á., Main Yaque, P. & Susi García, M. R. «Extreme Inaccuracies in Gaussian Bayesian Networks». Journal of Multivariate Analysis, vol. 99, n.o 9, octubre de 2008, pp. 1929-40. DOI.org (Crossref), https://doi.org/10.1016/j.jmva.2008.02.027.
dc.identifier.doi10.1016/j.jmva.2008.02.027
dc.identifier.issn0047-259X
dc.identifier.officialurlhttps//doi.org/10.1016/j.jmva.2008.02.027
dc.identifier.relatedurlhttp://www.sciencedirect.com/science/article/pii/S0047259X08000389
dc.identifier.urihttps://hdl.handle.net/20.500.14352/50038
dc.issue.number9
dc.journal.titleJournal Of Multivariate Analysis
dc.language.isoeng
dc.page.final1940
dc.page.initial1929
dc.publisherElsevier
dc.relation.projectIDThis research was supported by the MEC from Spain, Grant MTM2005-05462, and the Universidad Complutense-Comunidad de Madrid, Grant UCM2005-910395.
dc.rights.accessRightsrestricted access
dc.subject.cdu519.22
dc.subject.keywordGaussian Bayesian network
dc.subject.keywordSensitivity analysis
dc.subject.keywordKullback-Leibler divergence
dc.subject.keywordSensitivity-Analysis
dc.subject.keywordStatistics & Probability
dc.subject.ucmEstadística matemática (Matemáticas)
dc.subject.unesco1209 Estadística
dc.titleExtreme Inaccuracies In Gaussian Bayesian Networksen
dc.typejournal article
dc.volume.number99
dspace.entity.typePublication
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