Copula directed acyclic graphs

Eugen Pircalabelu, Gerda Claeskens and Irène Gijbels
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Eugen Pircalabelu: Université catholique de Louvain, LIDAM/ISBA, Belgium

No 2017034, LIDAM Reprints ISBA from Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA)

Abstract: A new methodology for selecting a Bayesian network for continuous data outside the widely used class of multivariate normal distributions is developed. The `copula DAGs' combine directed acyclic graphs and their associated probability models with copula C/D-vines. Bivariate copula densities introduce flexibility in the joint distributions of pairs of nodes in the network. An information criterion is studied for graph selection tailored to the joint modeling of data based on graphs and copulas. Examples and simulation studies show the flexibility and properties of the method.

Keywords: Theoretical Computer Science; Statistics; Probability and Uncertainty; Statistics and Probability; Computational Theory and Mathematics (search for similar items in EconPapers)
Pages: 31
Date: 2017-01-01
Note: In: Statistics and Computing, vol. 27(1), p. 55-78 (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:aiz:louvar:2017034

DOI: 10.1007/s11222-015-9599-9

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