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On conditional skewness with applications to environmental data
Authors:F.?Belzunce,J.?Mulero  author-information"  >  author-information__contact u-icon-before"  >  mailto:julio.mulero@ua.es"   title="  julio.mulero@ua.es"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author  author-information__orcid u-icon-before icon--orcid u-icon-no-repeat"  >  http://orcid.org/---"   itemprop="  url"   title="  View OrcID profile"   target="  _blank"   rel="  noopener"   data-track="  click"   data-track-action="  OrcID"   data-track-label="  "  >View author&#  s OrcID profile return OK on get,J.?M.?Ruíz,A.?Suárez-Llorens
Affiliation:1.Dpto. Estadística e Investigación Operativa, Facultad de Matemáticas,Universidad de Murcia,Murcia,Spain;2.Dpto. Matemáticas, Facultad de Ciencias,Universidad de Alicante,Alicante,Spain;3.Dpto. Estadística e Investigación Operativa,Universidad de Cádiz, Facultad de Ciencias,Cádiz,Spain
Abstract:The statistical literature contains many univariate and multivariate skewness measures that allow two datasets to be compared, some of which are defined in terms of quantile values. In most situations, the comparison between two random vectors focuses on univariate comparisons of conditional random variables truncated in quantiles; this kind of comparison is of particular interest in the environmental sciences. In this work, we describe a new approach to comparing skewness in terms of the univariate convex transform ordering proposed by van Zwet (Convex transformations of random variables. Mathematical Centre Tracts, Amsterdam, 1964), associated with skewness as well as concentration. The key to these comparisons is the underlying dependence structure of the random vectors. Below we describe graphical tools and use several examples to illustrate these comparisons.
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