Package: multivariance
Title: Measuring Multivariate Dependence Using Distance Multivariance
Version: 2.4.1
Date: 2021-10-06
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 of arbitrarily many random vectors. The necessary functions are
    implemented in this packages and examples are given. It includes: distance multivariance, 
    distance multicorrelation, dependence structure detection, tests of independence and
    copula versions of distance multivariance based on the Monte Carlo empirical transform.
    Detailed references are given in the package description, as starting point for the 
    theoretic background we refer to:
    B. Böttcher, Dependence and Dependence Structures: Estimation and Visualization Using 
    the Unifying Concept of Distance Multivariance. Open Statistics, Vol. 1, No. 1 (2020), 
    <doi:10.1515/stat-2020-0001>.
Depends: R (>= 3.3.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: igraph, graphics, stats, Rcpp, microbenchmark
RoxygenNote: 7.1.2
Suggests: testthat
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2021-10-06 15:06:41 UTC; BB
Author: Björn Böttcher [aut, cre],
  Martin Keller-Ressel [ctb]
Maintainer: Björn Böttcher <bjoern.boettcher@tu-dresden.de>
Repository: CRAN
Date/Publication: 2021-10-06 15:50:05 UTC
Built: R 4.6.0; x86_64-apple-darwin20; 2026-04-27 18:44:24 UTC; unix
Archs: multivariance.so.dSYM
