Publicación: Assessment of extreme records in environmental data through the study of stochastic orders for scale mixtures of skew normal vectors
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2024-02-18
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info:eu-repo/semantics/openAccess
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Springer
Resumen
Scale mixtures of skew normal distributions are flexible models well-suited to handle departures from multivariate normality. This paper is concerned with the stochastic comparison of vectors that belong to the family of scale mixtures of skew normal distributions. The paper revisits some of their properties with a proposal that allows to carry out tail weight stochastic comparisons. The connections of the proposed stochastic orders with the non-normality parameters of the multivariate model are also studied for some popular distributions within the family. The role played by these parameters to tackle the non-normality of multivariate data is enhanced as a result. This work is motivated by the analysis of multivariate data in environmental studies which usually collect maximum or minimum values exhibiting departures from normality. The implications of our theoretical results in addressing the stochastic comparison of extreme environmental records is illustrated with an application to a real data study on maximum temperatures in the Iberian Peninsula throughout the last century. The resulting findings may elucidate whether extreme temperatures are evolving for such a long period.
Descripción
The registered version of this article, first published in “Environmental and Ecological Statistics, vol. 31, 2024", is available online at the publisher's website: Springer, https://doi.org/10.1007/s10651-024-00600-2
La versión registrada de este artículo, publicado por primera vez en “Environmental and Ecological Statistics, vol. 31, 2024", está disponible en línea en el sitio web del editor: Springer, https://doi.org/10.1007/s10651-024-00600-2
Categorías UNESCO
Palabras clave
convex transform order, kurtosis, Likelihood ratio order, maximum temperature data, tail weight
Citación
Arevalillo, J.M., Navarro, J. Assessment of extreme records in environmental data through the study of stochastic orders for scale mixtures of skew normal vectors. Environ Ecol Stat 31, 151–179 (2024). https://doi.org/10.1007/s10651-024-00600-2
Centro
Facultad de Ciencias
Departamento
Estadística, Investigación Operativa y Cálculo Numérico