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multivariance  

Measuring Multivariate Dependence Using Distance Multivariance
View on CRAN: Click here


Download and install multivariance package within the R console
Install from CRAN:
install.packages("multivariance")

Install from Github:
library("remotes")
install_github("cran/multivariance")

Install by package version:
library("remotes")
install_version("multivariance", "2.4.1")



Attach the package and use:
library("multivariance")
Maintained by
Björn Böttcher
[Scholar Profile | Author Map]
First Published: 2017-11-02
Latest Update: 2021-10-06
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. B
How to cite:
Björn Böttcher (2017). multivariance: Measuring Multivariate Dependence Using Distance Multivariance. R package version 2.4.1, https://cran.r-project.org/web/packages/multivariance. Accessed 02 May. 2025.
Previous versions and publish date:
1.0.5 (2017-11-02 14:46), 1.1.0 (2018-01-10 17:12), 1.2.0 (2018-09-13 17:20), 1.2.1 (2019-01-05 01:20), 2.0.0 (2019-02-06 14:30), 2.1.0 (2019-03-19 16:00), 2.2.0 (2019-06-18 14:20), 2.3.0 (2020-04-23 18:50), 2.4.0 (2020-12-10 16:50)
Other packages that cited multivariance R package
View multivariance citation profile
Other R packages that multivariance depends, imports, suggests or enhances
Complete documentation for multivariance
Functions, R codes and Examples using the multivariance R package
Some associated functions: N.coefficients . anscombe.extended . cdm.mu.bcd . cdm . cdms.mu.bcd . cdms . circle.coordinates . clean.graph . coins . copula.multicorrelation . copula.multicorrelation.test . copula.multivariance . d2 . dep_struct_iterated_13_100 . dep_struct_ring_15_100 . dep_struct_several_26_100 . dep_struct_star_9_100 . dependence.structure.full . dependence.structure . dist.to.matrix . dm . dms . double.center . doubleCenterBiasCorrected . doubleCenterBiasCorrectedUpper . doubleCenterBiasCorrectedUpperLower . doubleCenterSymMat . emp.transf.dep . emp.transf . emp.transf.vec . fastEuclideanCdm . fastdist . find.cluster . independence.test . is.doubly.centered . layout_on_circles . lower.order . m.multivariance . match.rows . match_rows . moments.for.pearson . mu3.unbiased . multicorrelation.bias.corrected . multicorrelation . multivariance-package . multivariance . multivariance.pvalue . multivariance.test . multivariance.timing . multivariances.all . p.value.to.star.label . pairwise.multicorrelation.bias.corrected . pearson.pvalue . pearson.pvalue.unif . pearson.qf . rejection.level . resample.multivariance . resample.pvalue . resample.rejection.level . sample.cdms . sample.cols . signed.sqrt . simple.int.hash . sums.of.products . tetrahedron . total.multicorrelation.bias.corrected.upper . total.multivariance . 
Some associated R codes: RcppExports.R . multivariance-functions.R .  Full multivariance package functions and examples
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