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copulaedas: An R Package for Estimation of Distribution Algorithms Based on Copulas

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  • Gonzalez-Fernandez, Yasser
  • Soto, Marta

Abstract

The use of copula-based models in EDAs (estimation of distribution algorithms) is currently an active area of research. In this context, the copulaedas package for R provides a platform where EDAs based on copulas can be implemented and studied. The package offers complete implementations of various EDAs based on copulas and vines, a group of well-known optimization problems, and utility functions to study the performance of the algorithms. Newly developed EDAs can be easily integrated into the package by extending an S 4 class with generic functions for their main components. This paper presents copulaedas by providing an overview of EDAs based on copulas, a description of the implementation of the package, and an illustration of its use through examples. The examples include running the EDAs defined in the package, implementing new algorithms, and performing an empirical study to compare the behavior of different algorithms on benchmark functions and a real-world problem.

Suggested Citation

  • Gonzalez-Fernandez, Yasser & Soto, Marta, 2014. "copulaedas: An R Package for Estimation of Distribution Algorithms Based on Copulas," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i09).
    • Handle: RePEc:jss:jstsof:v:058:i09
    DOI: http://hdl.handle.net/10.18637/jss.v058.i09
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    2. Aas, Kjersti & Czado, Claudia & Frigessi, Arnoldo & Bakken, Henrik, 2009. "Pair-copula constructions of multiple dependence," Insurance: Mathematics and Economics, Elsevier, vol. 44(2), pages 182-198, April.
    3. Joe, Harry, 2005. "Asymptotic efficiency of the two-stage estimation method for copula-based models," Journal of Multivariate Analysis, Elsevier, vol. 94(2), pages 401-419, June.
    4. Hering, Christian & Hofert, Marius & Mai, Jan-Frederik & Scherer, Matthias, 2010. "Constructing hierarchical Archimedean copulas with Lévy subordinators," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1428-1433, July.
    5. Santana, Roberto & Bielza, Concha & Larrañaga, Pedro & Lozano, Jose A. & Echegoyen, Carlos & Mendiburu, Alexander & Armañanzas, Rubén & Shakya, Siddartha, 2010. "Mateda-2.0: A MATLAB Package for the Implementation and Analysis of Estimation of Distribution Algorithms," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 35(i07).
    6. Kojadinovic, Ivan & Yan, Jun, 2010. "Modeling Multivariate Distributions with Continuous Margins Using the copula R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 34(i09).
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