Statistical Inference of C- And D-Vine Copulas
Functions for statistical inference of canonical vine (C-vine)
and D-vine copulas. Tools for bivariate exploratory data analysis and for bivariate
as well as vine copula selection are provided. Models can be estimated
either sequentially or by joint maximum likelihood estimation.
Sampling algorithms and plotting methods are also included.
Data is assumed to lie in the unit hypercube (so-called copula
data).

Sampling from Conditional C- and D-Vine Copulas
Provides tools for sampling from a conditional copula density decomposed via
Pair-Copula Constructions as C- or D- vine. Here, the vines which can be used for such
sampling are those which sample as first the conditioning variables (when following the
sampling algorithms shown in Aas et al. (2009) <DOI:10.1016/j.insmatheco.2007.02.001>).
The used sampling algorithm is presented and discussed in Bevacqua et al. (2017)
<DOI:10.5194/hess-2016-652>, and it is a modified version of that from Aas et al. (2009)
<DOI:10.1016/j.insmatheco.2007.02.001>. A function is available to select the best vine
(based on information criteria) among those which allow for such conditional sampling.
The package includes a function to compare scatterplot matrices and pair-dependencies of
two multivariate datasets.
person("Emanuele", "Bevacqua", role = c("aut", "cre"),
email = "emanuele.bevacqua@uni-graz.at")

Provides tools for sampling from a conditional copula density decomposed via
Pair-Copula Constructions as C- or D- vine. Here, the vines which can be used for such a
sampling are those which sample as first the conditioning variables (when following the
sampling algorithms shown in Aas et al. (2009) <DOI:10.1016/j.insmatheco.2007.02.001>).
The used sampling algorithm is presented and discussed in Bevacqua et al. (2017)
<DOI:10.5194/hess-2016-652>, and it is a modified version of that from Aas et al. (2009)
<DOI:10.1016/j.insmatheco.2007.02.001>. A function is available to select the best vine
(based on information criteria) among those which allow for such a conditional sampling.
The package includes a function to compare scatterplot matrices and pair-dependencies of
two multivariate datasets.