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- W1965986575 abstract "The necessity to interconnect several observed or measured quantities arises in many fields of science. And this need led, as early as in the 1940s and 1950s, to the proposals of different solutions, e.g., the IPF Procedure or copula apparatus. Multidimensional copulas alone appeared to be insufficiently flexible to model complex dependency structures in multivariate distributions, and therefore other solutions were introduced, e.g., vines. In this paper the author defines a general method of continuous density composition, providing a flexible possibility to build a multivariate continuous distribution from low-dimensional “pieces”. The model of multivariate distribution is based on iterative application of the operator of composition, and it is shown that, under the assumption of consistency of the composed probability densities, the application of the operator of composition maximizes the differential entropy in the space of all common extensions of both operands’ probability densities. Furthermore, a special case of compositional models is introduced here based on Archimedean copulas, and thus a copula-based approach to the modeling of multivariate dependence structure is presented as an alternative to the vines." @default.
- W1965986575 created "2016-06-24" @default.
- W1965986575 creator A5013531947 @default.
- W1965986575 date "2014-01-01" @default.
- W1965986575 modified "2023-09-23" @default.
- W1965986575 title "An operator of composition for the multivariate copula construction" @default.
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- W1965986575 doi "https://doi.org/10.1063/1.4903702" @default.
- W1965986575 hasPublicationYear "2014" @default.
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