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Enjoy the Joy of Copulas: With a Package copula

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  • Jun Yan
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    Abstract

    Copulas have become a popular tool in multivariate modeling successfully applied in many fields. A good open-source implementation of copulas is much needed for more practitioners to enjoy the joy of copulas. This article presents the design, features, and some implementation details of the R package copula. The package provides a carefully designed and easily extensible platform for multivariate modeling with copulas in R. S4 classes for most frequently used elliptical copulas and Archimedean copulas are implemented, with methods for density/distribution evaluation, random number generation, and graphical display. Fitting copula-based models with maximum likelihood method is provided as template examples. With the classes and methods in the package, the package can be easily extended by user-defined copulas and margins to solve problems.

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    Article provided by American Statistical Association in its journal Journal of Statistical Software.

    Volume (Year): 21 ()
    Issue (Month): i04 ()
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    Handle: RePEc:jss:jstsof:21:i04

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    Cited by:
    1. Rogelio Salinas-Gutiérrez & Arturo Hernández-Aguirre & Enrique Villa-Diharce, 2014. "Copula selection for graphical models in continuous Estimation of Distribution Algorithms," Computational Statistics, Springer, vol. 29(3), pages 685-713, June.
    2. Erlend Bø & Peter Lambert & Thor Thoresen, 2012. "Horizontal inequity under a dual income tax system: principles and measurement," International Tax and Public Finance, Springer, vol. 19(5), pages 625-640, October.
    3. Miao, Ruiqing & Khanna, Madhu, 2013. "Crop Insurance for Energy Grasses," 2013 AAEA: Crop Insurance and the Farm Bill Symposium, October 8-9, Louisville, KY 156936, Agricultural and Applied Economics Association.
    4. Chukiat Chaiboonsri & Prasert Chaitip, 2012. "A Comparative Analysis of ASEAN Currencies Using a Copula Approach and a Dynamic Copula Approach," Annals of the University of Petrosani, Economics, University of Petrosani, Romania, vol. 12(4), pages 39-52.
    5. Christophe Dutang & Vincent Goulet & Mathieu Pigeon, . "actuar: An R Package for Actuarial Science," Journal of Statistical Software, American Statistical Association, vol. 25(i07).
    6. Jäschke, Stefan, 2014. "Estimation of risk measures in energy portfolios using modern copula techniques," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 359-376.
    7. Schomaker, Michael & Wan, Alan T.K. & Heumann, Christian, 2010. "Frequentist Model Averaging with missing observations," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3336-3347, December.
    8. Fantazzini, Dean, 2011. "Analysis of multidimensional probability distributions with copula functions. II," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 23(3), pages 98-132.
    9. Göran Kauermann & Renate Meyer, 2014. "Penalized marginal likelihood estimation of finite mixtures of Archimedean copulas," Computational Statistics, Springer, vol. 29(1), pages 283-306, February.
    10. Pandit, Mahesh & Paudel, Krishna P. & Mishra, Ashok K., 2013. "Do Agricultural Subsidies Affect the Labor Allocation Decision? Comparing Parametric and Semiparametric Methods," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(1), April.
    11. Bee, Marco, 2011. "Adaptive Importance Sampling for simulating copula-based distributions," Insurance: Mathematics and Economics, Elsevier, vol. 48(2), pages 237-245, March.
    12. Denecke, Liesa & Müller, Christine H., 2011. "Robust estimators and tests for bivariate copulas based on likelihood depth," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2724-2738, September.
    13. Schomaker, Michael & Heumann, Christian, 2014. "Model selection and model averaging after multiple imputation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 758-770.
    14. Kim, Jong-Min & Jung, Yoon-Sung & Choi, Taeryon & Sungur, Engin A., 2011. "Partial correlation with copula modeling," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1357-1366, March.
    15. Michael Schomaker, 2012. "Shrinkage averaging estimation," Statistical Papers, Springer, vol. 53(4), pages 1015-1034, November.

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