wdm: Weighted Dependence Measures

Provides efficient implementations of weighted dependence measures and related asymptotic tests for independence. Implemented measures are the Pearson correlation, Spearman's rho, Kendall's tau, Blomqvist's beta, and Hoeffding's D; see, e.g., Nelsen (2006) <doi:10.1007/0-387-28678-0> and Hollander et al. (2015, ISBN:9780470387375).

Version: 0.2.4
Depends: R (≥ 3.2.0)
Imports: Rcpp
LinkingTo: Rcpp
Suggests: testthat, Hmisc, copula, covr
Published: 2023-08-10
DOI: 10.32614/CRAN.package.wdm
Author: Thomas Nagler [aut, cre]
Maintainer: Thomas Nagler <mail at tnagler.com>
BugReports: https://github.com/tnagler/wdm-r/issues
License: MIT + file LICENSE
URL: https://github.com/tnagler/wdm-r
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: wdm results


Reference manual: wdm.pdf


Package source: wdm_0.2.4.tar.gz
Windows binaries: r-devel: wdm_0.2.4.zip, r-release: wdm_0.2.4.zip, r-oldrel: wdm_0.2.4.zip
macOS binaries: r-release (arm64): wdm_0.2.4.tgz, r-oldrel (arm64): wdm_0.2.4.tgz, r-release (x86_64): wdm_0.2.4.tgz, r-oldrel (x86_64): wdm_0.2.4.tgz
Old sources: wdm archive

Reverse dependencies:

Reverse imports: CondCopulas, ElliptCopulas, MMDCopula, svines, TSEAL, wdnet
Reverse linking to: portvine, rvinecopulib, svines, vinereg
Reverse suggests: correlation, lcopula


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