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VecDep

This R package gathers together several functions that can be used for copula-based measuring of dependence between a finite amount of random vectors.

In particular, several estimation procedures are implemented for the class of phi-dependence measures, including Gaussian copula and hierarchical Archimedean copula methods, as studied in

• De Keyser, S. & Gijbels, I. (2024). Parametric dependence between random vectors via copula-based divergence measures. Journal of Multivariate Analysis 203:105336. doi: https://doi.org/10.1016/j.jmva.2024.105336,

and a semi-parametric meta-elliptical method and fully non-parametric methods, as investigated in

• De Keyser, S. & Gijbels, I. (2024). Hierarchical variable clustering via copula-based divergence measures between random vectors. International Journal of Approximate Reasoning 165:109090. doi: https://doi.org/10.1016/j.ijar.2023.109090.

The latter reference also discusses an algorithm for hierarchical variable clustering based on multivariate similarities between random vectors, which is implemented in this R package as well. Next to this, functions for Bures-Wasserstein dependence coefficients and Gaussian copula correlation matrix penalization techniques, as discussed in

• De Keyser, S. & Gijbels, I. (2024). High-dimensional copula-based Wasserstein dependence. doi: https://doi.org/10.48550/arXiv.2404.07141,

are implemented as well.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.