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Bivariate kurtotic distributions of garment fibre data

Author

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  • C. J. Hoggart
  • S. G. Walker
  • A. F. M. Smith

Abstract

Summary. A bivariate and unimodal distribution is introduced to model an unconventionally distributed data set collected by the Forensic Science Service. This family of distributions allows for a different kurtosis in each orthogonal direction and has a constructive rather than probability density function definition, making conventional inference impossible. However, the construction and inference work well with a Bayesian Markov chain Monte Carlo analysis.

Suggested Citation

  • C. J. Hoggart & S. G. Walker & A. F. M. Smith, 2003. "Bivariate kurtotic distributions of garment fibre data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(3), pages 323-335, July.
    • Handle: RePEc:bla:jorssc:v:52:y:2003:i:3:p:323-335
    DOI: 10.1111/1467-9876.00407
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    Cited by:

    1. Jose T.A.S. Ferreira & Mark F.J. Steel, 2004. "Bayesian Multivariate Regression Analysis with a New Class of Skewed Distributions," Econometrics 0403001, University Library of Munich, Germany.
    2. Ferreira, Jose T.A.S. & Steel, Mark F.J., 2007. "Model comparison of coordinate-free multivariate skewed distributions with an application to stochastic frontiers," Journal of Econometrics, Elsevier, vol. 137(2), pages 641-673, April.

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