person("Younghoon", "Kim", role = "ctb"),
person("Vladas", "Pipiras", role = "ctb")
Imports: methods, stats, utils, MASS, Rcpp (>= 1.0.3), Matrix, ggplot2,

Title: Penalized Estimation of Multiple-Subject Vector Autoregressive

Title: Measuring Multivariate Dependence Using Distance Multivariance
Authors@R: c(person("Björn", "Böttcher", email = "bjoern.boettcher@tu-dresden.de", role = c("aut", "cre")),person("Martin", "Keller-Ressel", email = "martin.keller-ressel@tu-dresden.de", role = "ctb"))
Description: Distance multivariance is a measure of dependence which can be used to detect and quantify dependence structures. The necessary functions are implemented in this packages, and examples are given. For the theoretic background we refer to the forthcoming papers: B. Böttcher, M. Keller-Ressel, R.L. Schilling (2017) Detecting independence of random vectors I + II. Preprints.

person("Björn", "Böttcher", email = "bjoern.boettcher@tu-dresden.de",role = c("aut", "cre")),
person("Martin", "Keller-Ressel", email = "martin.keller-ressel@tu-dresden.de", role = "ctb")
Description: Distance multivariance is a measure of dependence which can be used to detect
and quantify dependence. The necessary functions are implemented in this packages,
and examples are given. For the theoretic background we refer to the papers:
B. Böttcher, M. Keller-Ressel, R.L. Schilling, Detecting independence of random vectors I. Generalized distance covariance and Gaussian covariance. Preprint 2017, <arXiv:1711.07778>.
B. Böttcher, M. Keller-Ressel, R.L. Schilling, Detecting independence of random vectors II. Distance multivariance and Gaussian multivariance. Preprint 2017, <arXiv:1711.07775>.
B. Böttcher, Dependence Structures - Estimation and Visualization Using Distance Multivariance. Preprint 2017, <arXiv:1712.06532>.

G. Berschneider, B. Böttcher, On complex Gaussian random fields, Gaussian quadratic forms and sample distance multivariance. Preprint 2018, <arXiv:1808.07280>.
Imports: abind, igraph, graphics, stats, Rcpp