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Box—Cox Transformation for Semiparametric Comparison of Two Samples

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Foundations of Statistical Inference

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

Abstract

We consider the density ratio model which specifies a linear parametric function of the log-likelihood ratio of two densities without assuming any specific form about them and has been found useful for semiparametric comparison of two samples. We study the Box-Cox family of transformations in the context of the density ratio model to suggest a data driven method for identification of the model’s true parametric part. The methodology is illustrated by a real data example.

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References

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Author information

Authors and Affiliations

  1. Department of Mathematics and Statistics, University of Cyprus, Nicosia, Cyprus

    Konstantinos Fokianos

Authors
  1. Konstantinos Fokianos
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Editor information

Editors and Affiliations

  1. Department of Statistics, Hebrew University, Jerusalem, 91905, Israel

    Yoel Haitovsky  & Yaacov Ritov  & 

  2. Department of Mathematical Stochastics, University of Freiburg, Eckerstraße 1, Freiburg, 79104, Germany

    Hans Rudolf Lerche

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© 2003 Springer-Verlag Berlin Heidelberg

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Fokianos, K. (2003). Box—Cox Transformation for Semiparametric Comparison of Two Samples. In: Haitovsky, Y., Ritov, Y., Lerche, H.R. (eds) Foundations of Statistical Inference. Contributions to Statistics. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57410-8_12

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  • DOI: https://doi.org/10.1007/978-3-642-57410-8_12

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-0047-0

  • Online ISBN: 978-3-642-57410-8

  • eBook Packages: Springer Book Archive

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