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dc.contributor.authorJupp, P.E.
dc.contributor.authorRegoli, G.
dc.contributor.authorAzzalini, A.
dc.identifier.citationJupp , P E , Regoli , G & Azzalini , A 2016 , ' A general setting for symmetric distributions and their relationship to general distributions ' , Journal of Multivariate Analysis , vol. 148 , pp. 107-119 .
dc.identifier.otherPURE: 241247270
dc.identifier.otherPURE UUID: 57f03988-9fa2-4755-816f-87a19a2c2558
dc.identifier.otherBibtex: urn:fbb21aff2b7403d80b17de9eae30fbb6
dc.identifier.otherScopus: 84961789607
dc.identifier.otherORCID: /0000-0003-0973-8434/work/60195548
dc.identifier.otherWOS: 000375826400009
dc.description.abstractA standard method of obtaining non-symmetrical distributions is that of modulating symmetrical distributions by multiplying the densities by a perturbation factor. This has been considered mainly for central symmetry of a Euclidean space in the origin. This paper enlarges the concept of modulation to the general setting of symmetry under the action of a compact topological group on the sample space. The main structural result relates the density of an arbitrary distribution to the density of the corresponding symmetrised distribution. Some general methods for constructing modulating functions are considered. The effect that transformations of the sample space have on symmetry of distributions is investigated. The results are illustrated by general examples, many of them in the setting of directional statistics.
dc.relation.ispartofJournal of Multivariate Analysisen
dc.rights© 2016, Publisher / the Author(s). This work is made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at /
dc.subjectDirectional statisticsen
dc.subjectSkew-symmetric distributionen
dc.subjectSymmetry-modulated distributionen
dc.subjectQA Mathematicsen
dc.titleA general setting for symmetric distributions and their relationship to general distributionsen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. Applied Mathematicsen
dc.description.statusPeer revieweden

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