energy: E-Statistics: Multivariate Inference via the Energy of Data

E-statistics (energy) tests and statistics for multivariate and univariate inference, including distance correlation, one-sample, two-sample, and multi-sample tests for comparing multivariate distributions, are implemented. Measuring and testing multivariate independence based on distance correlation, partial distance correlation, multivariate goodness-of-fit tests, clustering based on energy distance, testing for multivariate normality, distance components (disco) for non-parametric analysis of structured data, and other energy statistics/methods are implemented.

AuthorMaria L. Rizzo and Gabor J. Szekely
Date of publication2016-08-26 07:34:19
MaintainerMaria Rizzo <mrizzo@bgsu.edu>
LicenseGPL (>= 2)
Version1.7-0

View on CRAN

Functions

bcdcor Man page
Dcenter Man page
D_center Man page
dcor Man page
DCOR Man page
dcor.t Man page
dcor.ttest Man page
dcov Man page
dcov.test Man page
dcovU Man page
dcovU_stats Man page
disco Man page
disco.between Man page
distance covariance Man page
edist Man page
energy Man page
energy.hclust Man page
energy-package Man page
eqdist.e Man page
eqdist.etest Man page
indep.e Man page
indep.etest Man page
indep.test Man page
ksample.e Man page
mvI Man page
mvI.test Man page
mvnorm.e Man page
mvnorm.etest Man page
normal.e Man page
pdcor Man page
pdcor.test Man page
pdcov Man page
pdcov.test Man page
poisson.m Man page
poisson.mtest Man page
print.disco Man page
Ucenter Man page
U_center Man page
U_product Man page

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