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Transformations to symmetry based on the probability weighted characteristic function

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Meintanis, Simos G.
Stupfler, Gilles

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Institute of Information Theory and Automation

Abstract

We 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 included

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Meintanis, 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]

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