Provides tools for the statistical analysis of regular vine copula models, see Aas et al. (2009) <doi:10.1016/j.insmatheco.2007.02.001> and Dissman et al. (2013) <doi:10.1016/j.csda.2012.08.010>. The package includes tools for parameter estimation, model selection, simulation, goodness-of-fit tests, and visualization. Tools for estimation, selection and exploratory data analysis of bivariate copula models are also provided.
Vine copulas are a flexible class of dependence models consisting of bivariate building blocks (see e.g., Aas et al., 2009). This package is primarily made for the statistical analysis of vine copula models. The package includes tools for parameter estimation, model selection, simulation, goodness-of-fit tests, and visualization. Tools for estimation, selection and exploratory data analysis of bivariate copula models are also provided.
The DESCRIPTION file:
This package was not yet installed at build time.
The package VineCopula is a continuation of the
package CDVine by U. Schepsmeier and E. C. Brechmann (see Brechmann
and Schepsmeier (2013)). It includes all functions implemented in CDVine for
the bivariate case (BiCop-functions).
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bivariate copulas. Statistical Papers, 55 (2), 525-542.
https://link.springer.com/article/10.1007/s00362-013-0498-x.
Schepsmeier, U. (2013) A goodness-of-fit test for regular vine copula models. Preprint https://arxiv.org/abs/1306.0818
Schepsmeier, U. (2015) Efficient information based goodness-of-fit tests for vine copula models with fixed margins. Journal of Multivariate Analysis 138, 34-52.
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https://link.springer.com/article/10.1007/s00180-013-0423-8#.
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