Show simple item record

dc.contributor.authorMeintanis, Simos G.
dc.contributor.authorStupfler, Gilles
dc.date.accessioned2016-09-06T06:55:42Z
dc.date.available2016-09-06T06:55:42Z
dc.date.issued2015
dc.identifier.citationMeintanis, S.G. & Stupfler, G. 2015. Transformations to symmetry based on the probability weighted characteristic function. Kybernetika, 51(4):571-587. [http://dx.doi.org/10.14736/kyb-2015-4-0571]en_US
dc.identifier.issn0023-5954 (Online)
dc.identifier.urihttp://hdl.handle.net/10394/18548
dc.identifier.urihttp://dx.doi.org/10.14736/kyb-2015-4-0571
dc.identifier.urihttp://www.kybernetika.cz/content/2015/4/571
dc.description.abstractWe suggest a nonparametric version of the probability weighted empirical characteristic function (PWECF) introduced by Meintanis et al. [10] and use this PWECF in order to estimate the parameters of arbitrary transformations to symmetry. The almost sure consistency of the resulting estimators is shown. Finite{sample results for i.i.d. data are presented and are subsequently extended to the regression setting. A real data illustration is also includeden_US
dc.language.isoenen_US
dc.publisherInstitute of Information Theory and Automationen_US
dc.subjectCharacteristic functionen_US
dc.subjectempirical characteristic functionen_US
dc.subjectprobability weighted momentsen_US
dc.subjectsymmetry transformationen_US
dc.titleTransformations to symmetry based on the probability weighted characteristic functionen_US
dc.typeArticleen_US
dc.contributor.researchID21262977 - Meintanis, Simos George


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record