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dc.contributor.authorGómez Déniz, Emilio
dc.contributor.authorSarabia Alegría, José María 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2025-09-30T11:52:26Z
dc.date.available2025-09-30T11:52:26Z
dc.date.issued2025-04-28
dc.identifier.issn2073-8994
dc.identifier.otherPID2021-127989OB-I00es_ES
dc.identifier.urihttps://hdl.handle.net/10902/37569
dc.description.abstractWe combine two well-known statements of results in the statistical and mathematical literature, one related to symmetric continuous distributions and the other to the integration of functions, to obtain some new results regarding symmetric distributions and involving the value at risk and the tail value at risk, well-known tools used in actuarial and financial statistics, among others. Generalizations of the skew normal distribution in its univariate and multivariate versions obtained from one of the results are also shown, and a new method is proposed for generating families of skewed continuous distributions.es_ES
dc.format.extent13 p.es_ES
dc.language.isoenges_ES
dc.publisherMDPIes_ES
dc.rights© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/).es_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceSymmetry, 2025, 17(5), 670es_ES
dc.subject.otherSkew normal distributiones_ES
dc.subject.otherSymmetrices_ES
dc.subject.otherValue at riskes_ES
dc.subject.otherTail value at riskes_ES
dc.titleSome new results connected with symmetric random variables: generating skew distributionses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.3390/sym17050670es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.3390/sym17050670
dc.type.versionpublishedVersiones_ES


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Mostrar el registro sencillo

© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/).Excepto si se señala otra cosa, la licencia del ítem se describe como © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/).