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Transformations to symmetry based on the probability weighted characteristic function

Abstract : We suggest a nonparametric version of the probability weighted empirical characteristic function (PWECF) introduced by Meintanis \et al.\ \\cite\meiswaall2014\ 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 included.
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https://hal-amu.archives-ouvertes.fr/hal-01457397
Contributor : Patrice Cacciuttolo <>
Submitted on : Monday, February 6, 2017 - 2:18:31 PM
Last modification on : Wednesday, August 5, 2020 - 3:12:28 AM

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Simos G. Meintanis, Gilles Stupfler. Transformations to symmetry based on the probability weighted characteristic function. Kybernetika, 2015, 51 (4), pp.571--587. ⟨10.14736/kyb-2015-4-0571⟩. ⟨hal-01457397⟩

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