multivariance: Measuring Multivariate Dependence Using Distance Multivariance

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, Dependence and Dependence Structures: Estimation and Visualization Using Distance Multivariance. <arXiv:1712.06532>. B. Böttcher, M. Keller-Ressel, R.L. Schilling, Detecting independence of random vectors: generalized distance covariance and Gaussian covariance. VMSTA, 2018, Vol. 5, No. 3, 353-383. <arXiv:1711.07778>. B. Böttcher, M. Keller-Ressel, R.L. Schilling, Distance multivariance: New dependence measures for random vectors. <arXiv:1711.07775>. G. Berschneider, B. Böttcher, On complex Gaussian random fields, Gaussian quadratic forms and sample distance multivariance. <arXiv:1808.07280>.

Version: 2.2.0
Depends: R (≥ 3.3.0)
Imports: igraph, graphics, stats, Rcpp, microbenchmark
LinkingTo: Rcpp
Suggests: testthat
Published: 2019-06-18
Author: Björn Böttcher [aut, cre], Martin Keller-Ressel [ctb]
Maintainer: Björn Böttcher <bjoern.boettcher at tu-dresden.de>
License: GPL-3
NeedsCompilation: yes
Materials: NEWS
CRAN checks: multivariance results

Downloads:

Reference manual: multivariance.pdf
Package source: multivariance_2.2.0.tar.gz
Windows binaries: r-devel: multivariance_2.2.0.zip, r-release: multivariance_2.2.0.zip, r-oldrel: multivariance_2.2.0.zip
OS X binaries: r-release: multivariance_2.2.0.tgz, r-oldrel: multivariance_2.2.0.tgz
Old sources: multivariance archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=multivariance to link to this page.