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A unified approach to Stein characterizations

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  • Christophe Ley
  • Yvik Swan
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    Abstract

    This article deals with Stein characterizations of probability distributions. We provide a general framework for interpreting these in terms of the parameters of the underlying distribution. In order to do so we introduce two concepts (a class of functions and an operator) which generalize those which were developed in the 70’s by Charles Stein and Louis Chen for characterizing the Gaussian and the Poisson distributions. Our methodology (i) allows for writing many (if not all) known univariate Stein characterizations, (ii) permits to identify clearly minimal conditions under which these results hold and (iii) provides a straightforward tool for constructing new Stein characterizations. Our parametric interpretation of Stein characterizations also raises a number of questions which we outline at the end of the paper.

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    File URL: https://dipot.ulb.ac.be/dspace/bitstream/2013/88988/4/Stein.pdf
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    Bibliographic Info

    Paper provided by ULB -- Universite Libre de Bruxelles in its series Working Papers ECARES with number 2013/88988.

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    Length: 26 p.
    Date of creation: 2011
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    Publication status: Published by:
    Handle: RePEc:eca:wpaper:2013/88988

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    Related research

    Keywords: characterization theorem; Stein characterizations; location and scale parameters; parameter of interest; generalized (standardized) score function;

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    1. Yosef Rinott & Vladimir Rotar, 2000. "Normal approximations by Stein's method," Decisions in Economics and Finance, Springer, vol. 23(1), pages 15-29.
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