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dc.contributor.authorGómez-Déniz, Emilio
dc.contributor.authorSarabia Alegría, José María 
dc.contributor.authorCalderín-Ojeda, Enrique
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2019-09-30T11:46:22Z
dc.date.available2019-09-30T11:46:22Z
dc.date.issued2019
dc.identifier.issn2227-9091
dc.identifier.otherECO2013-47092es_ES
dc.identifier.otherECO2017-85577-Pes_ES
dc.identifier.otherECO2016-476203-C2-1-Pes_ES
dc.identifier.urihttp://hdl.handle.net/10902/16937
dc.description.abstractABSTRACT: It is known that the classical ruin function under exponential claim-size distribution depends on two parameters, which are referred to as the mean claim size and the relative security loading. These parameters are assumed to be unknown and random, thus, a loss function that measures the loss sustained by a decision-maker who takes as valid a ruin function which is not correct can be considered. By using squared error loss function and appropriate distribution function for these parameters, the issue of estimating the ruin function derives in a mixture procedure. Firstly, a bivariate distribution for mixing jointly the two parameters is considered, and second, different univariate distributions for mixing both parameters separately are examined. Consequently, a catalogue of ruin probability functions and severity of ruin, which are more flexible than the original one, are obtained. The methodology is also extended to the Pareto claim size distribution. Several numerical examples illustrate the performance of these functions.es_ES
dc.description.sponsorshipThis research was funded by (EGD) [Ministerio de Economía y Competitividad, Spain] grant number [ECO2013–47092]; (EGD)[Ministerio de Economía, Industria y Competitividad. Agencia Estatal de Investigación] grant number [ECO2017–85577–P ]; (JMS) [(Ministerio de Economía, Industria y Competitividad. Agencia Estatal de Investigación] grant number [ECO2016-476203-C2-1-P]; (ECO), research partially carried out while Calderín-Ojeda visited ULPGC as part of his Special Study Program leave, University of Melbourne.es_ES
dc.format.extent16 p.es_ES
dc.language.isoenges_ES
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)es_ES
dc.rightsAttribution-NonCommercial 4.0 Internationales_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.sourceRisks 2019, 7, 68es_ES
dc.subject.otherLoss functiones_ES
dc.subject.otherExponential distributiones_ES
dc.subject.otherPareto distributiones_ES
dc.subject.otherRuin functiones_ES
dc.subject.otherSeverity of ruines_ES
dc.subject.otherUpper boundes_ES
dc.titleRuin probability functions and severity of ruin as a statistical decision problemes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.3390/risks7020068
dc.type.versionpublishedVersiones_ES


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Attribution-NonCommercial 4.0 InternationalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial 4.0 International