Assessing the effect of kurtosis deviations from Gaussianity on conditional distributions

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dc.contributor.authorGómez Villegas, Miguel Ángel
dc.contributor.authorMain Yaque, Paloma
dc.contributor.authorNavarro, H.
dc.contributor.authorSusi García, María Del Rosario
dc.date.accessioned2023-06-19T13:21:55Z
dc.date.available2023-06-19T13:21:55Z
dc.date.issued2013-07-01
dc.description.abstractThe multivariate exponential power family is considered for n-dimensional random variables, Z, with a known partition Z equivalent to (Y, X) of dimensions p and n - p, respectively, with interest focusing on the conditional distribution Y vertical bar X. An infinitesimal variation of any parameter of the joint distribution produces perturbations in both the conditional and marginal distributions. The aim of the study was to determine the local effect of kurtosis deviations using the Kullback-Leibler divergence measure between probability distributions. The additive decomposition of this measure in terms of the conditional and marginal distributions, Y vertical bar X and X, is used to define a relative sensitivity measure of the conditional distribution family {Y vertical bar X = x}. Finally, simulated results suggest that for large dimensions, the measure is approximately equal to the ratio p/n, and then the effect of non-normality with respect to kurtosis depends only on the relative size of the variables considered in the partition of the random vector.en
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.facultyInstituto de Matemática Interdisciplinar (IMI)
dc.description.refereedTRUE
dc.description.sponsorshipMinisterio de Ciencia, Innovación y Universidades (España)
dc.description.sponsorshipMetodos Bayesianos by BSCH-UCM, Spain
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/22607
dc.identifier.citationGómez Villegas, M. A., Main Yaque, P., Navarro, H. & Sus García, M. R. «Assessing the Effect of Kurtosis Deviations from Gaussianity on Conditional Distributions». Applied Mathematics and Computation, vol. 219, n.o 21, julio de 2013, pp. 10499-505. DOI.org (Crossref), https://doi.org/10.1016/j.amc.2013.04.031.
dc.identifier.doi10.1016/j.amc.2013.04.031
dc.identifier.issn0096-3003
dc.identifier.officialurlhttps//doi.org/10.1016/j.amc.2013.04.031
dc.identifier.relatedurlhttp://www.sciencedirect.com/science/article/pii/S0096300313004463
dc.identifier.urihttps://hdl.handle.net/20.500.14352/33338
dc.issue.number21
dc.journal.titleApplied Mathematics and Computation
dc.language.isoeng
dc.page.final10505
dc.page.initial10499
dc.publisherElsevier
dc.relation.projectIDMTM 2008-03282
dc.relation.projectIDGR58/08-A 910395
dc.rights.accessRightsrestricted access
dc.subject.cdu519.2
dc.subject.keywordMultivariate exponential power distributions
dc.subject.keywordKurtosis
dc.subject.keywordKullback-Leibler divergence
dc.subject.keywordRelative sensitivity
dc.subject.ucmEstadística matemática (Matemáticas)
dc.subject.unesco1209 Estadística
dc.titleAssessing the effect of kurtosis deviations from Gaussianity on conditional distributionsen
dc.typejournal article
dc.volume.number219
dspace.entity.typePublication
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