dc.creatorOsorio, Felipe
dc.creatorGalea Rojas, Manuel Jesús
dc.creatorHenríquez, Claudio
dc.creatorArellano Valle, Reinaldo Boris
dc.date.accessioned2024-04-18T20:03:32Z
dc.date.accessioned2024-05-02T17:15:48Z
dc.date.available2024-04-18T20:03:32Z
dc.date.available2024-05-02T17:15:48Z
dc.date.created2024-04-18T20:03:32Z
dc.date.issued2023
dc.identifier10.1007/s10182-022-00468-2
dc.identifier1863-818X
dc.identifier1863-8171
dc.identifierSCOPUS_ID:85146567536
dc.identifierhttps://www.springer.com/journal/10182
dc.identifierhttps://doi.org/10.1007/s10182-022-00468-2
dc.identifierhttps://repositorio.uc.cl/handle/11534/85240
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9267860
dc.description.abstractThe main aim of this paper is to propose a set of tools for assessing non-normality taking into consideration the class of multivariate t-distributions. Assuming second moment existence, we consider a reparameterized version of the usual t distribution, so that the scale matrix coincides with covariance matrix of the distribution. We use the local influence procedure and the Kullback–Leibler divergence measure to propose quantitative methods to evaluate deviations from the normality assumption. In addition, the possible non-normality due to the presence of both skewness and heavy tails is also explored. Our findings based on two real datasets are complemented by a simulation study to evaluate the performance of the proposed methodology on finite samples.
dc.languageen
dc.rightsacceso restringido
dc.subjectKullback–Leibler divergence
dc.subjectLocal influence
dc.subjectNegentropy
dc.subjectOutliers
dc.titleAddressing non-normality in multivariate analysis using the t-distribution
dc.typeartículo


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