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Partially Schur-constant models

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  • Castañer, Anna
  • Claramunt, M. Mercè
  • Lefèvre, Claude
  • Loisel, Stéphane

Abstract

In this paper, we introduce a new multivariate dependence model that generalizes the standard Schur-constant model. The difference is that the random vector considered is partially exchangeable, instead of exchangeable, whence the term partially Schur-constant. Its advantage is to allow some heterogeneity of marginal distributions and a more flexible dependence structure, which broadens the scope of potential applications. We first show that the associated joint survival function is a monotonic multivariate function. Next, we derive two distributional representations that provide an intuitive understanding of the underlying dependence. Several other properties are obtained, including correlations within and between subvectors. As an illustration, we explain how such a model could be applied to risk management for insurance networks.

Suggested Citation

  • Castañer, Anna & Claramunt, M. Mercè & Lefèvre, Claude & Loisel, Stéphane, 2019. "Partially Schur-constant models," Journal of Multivariate Analysis, Elsevier, vol. 172(C), pages 47-58.
    • Handle: RePEc:eee:jmvana:v:172:y:2019:i:c:p:47-58
    DOI: 10.1016/j.jmva.2019.01.007
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    References listed on IDEAS

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    9. Claude Lefèvre & Stéphane Loisel & Sergey Utev, 2018. "Markov Property in Discrete Schur-constant Models," Methodology and Computing in Applied Probability, Springer, vol. 20(3), pages 1003-1012, September.
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    Cited by:

    1. Claude Lefèvre & Matthieu Simon, 2021. "Schur-Constant and Related Dependence Models, with Application to Ruin Probabilities," Methodology and Computing in Applied Probability, Springer, vol. 23(1), pages 317-339, March.

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