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Representation of multivariate Bernoulli distributions with a given set of specified moments

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  • Fontana, Roberto
  • Semeraro, Patrizia

Abstract

We propose a simple but new method of characterizing multivariate Bernoulli variables belonging to a given class, i.e., with some specified moments. Within a given class, this characterization allows us to generate easily a sample of mass functions. It also provides the bounds that all the moments must satisfy to be compatible and the possibility to choose the best distribution according to a certain criterion. For the special case of the Fréchet class of the multivariate Bernoulli distributions with given margins, we find a polynomial characterization of the class. Our characterization allows us to have bounds for the higher order moments. An algorithm is presented and illustrated.

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  • Fontana, Roberto & Semeraro, Patrizia, 2018. "Representation of multivariate Bernoulli distributions with a given set of specified moments," Journal of Multivariate Analysis, Elsevier, vol. 168(C), pages 290-303.
    • Handle: RePEc:eee:jmvana:v:168:y:2018:i:c:p:290-303
    DOI: 10.1016/j.jmva.2018.08.003
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    References listed on IDEAS

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    1. N. Rao Chaganty & Harry Joe, 2006. "Range of correlation matrices for dependent Bernoulli random variables," Biometrika, Biometrika Trust, vol. 93(1), pages 197-206, March.
    2. Teugels, Jozef L, 1990. "Some representations of the multivariate Bernoulli and binomial distributions," Journal of Multivariate Analysis, Elsevier, vol. 32(2), pages 256-268, February.
    3. N. Rao Chaganty & Harry Joe, 2004. "Efficiency of generalized estimating equations for binary responses," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(4), pages 851-860, November.
    4. Bahjat F. Qaqish, 2003. "A family of multivariate binary distributions for simulating correlated binary variables with specified marginal means and correlations," Biometrika, Biometrika Trust, vol. 90(2), pages 455-463, June.
    5. Sharakhmetov, Sh. & Ibragimov, R., 2002. "A Characterization of Joint Distribution of Two-Valued Random Variables and Its Applications," Journal of Multivariate Analysis, Elsevier, vol. 83(2), pages 389-408, November.
    6. Oman, Samuel D., 2009. "Easily simulated multivariate binary distributions with given positive and negative correlations," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 999-1005, February.
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    Cited by:

    1. Roberto Fontana & Elisa Luciano & Patrizia Semeraro, 2021. "Model risk in credit risk," Mathematical Finance, Wiley Blackwell, vol. 31(1), pages 176-202, January.
    2. Blier-Wong, Christopher & Cossette, Hélène & Marceau, Etienne, 2022. "Stochastic representation of FGM copulas using multivariate Bernoulli random variables," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    3. Andrea Collevecchio & Robert Griffiths, 2023. "A Class of Non-Reversible Hypercube Long-Range Random Walks and Bernoulli Autoregression," Journal of Theoretical Probability, Springer, vol. 36(1), pages 623-645, March.

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