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Commentary--A Latent Variable Perspective of Copula Modeling

Author

Listed:
  • Edward I. George

    () (Department of Statistics, The Wharton School of the University of Pennsylvania, Philadelphia, Pennsylvania 19104)

  • Shane T. Jensen

    () (Department of Statistics, The Wharton School of the University of Pennsylvania, Philadelphia, Pennsylvania 19104)

Abstract

The likelihood for copula modeling appears when both the data and the copula representations are seen as being driven by common uniform latent variables. This perspective facilitates Bayesian inference for prediction and copula selection.

Suggested Citation

  • Edward I. George & Shane T. Jensen, 2011. "Commentary--A Latent Variable Perspective of Copula Modeling," Marketing Science, INFORMS, vol. 30(1), pages 22-24, 01-02.
  • Handle: RePEc:inm:ormksc:v:30:y:2011:i:1:p:22-24
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    File URL: http://dx.doi.org/10.1287/mksc.1100.0579
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    References listed on IDEAS

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    1. Peter J. Danaher & Michael S. Smith, 2011. "Modeling Multivariate Distributions Using Copulas: Applications in Marketing," Marketing Science, INFORMS, vol. 30(1), pages 4-21, 01-02.
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    Cited by:

    1. Peter J. Danaher & Michael S. Smith, 2011. "Rejoinder--Estimation Issues for Copulas Applied to Marketing Data," Marketing Science, INFORMS, vol. 30(1), pages 25-28, 01-02.

    More about this item

    Keywords

    Bayesian analysis; latent variable; likelihood;

    Statistics

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