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, k-groups and hierarchical 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.
||EnergyOnlineCPM, HellCor, MBC
||ANCOMBC, biosensors.usc, cassowaryr, CircMLE, Compositional, EDMeasure, etree, fAssets, GiniDistance, itdr, kpcalg, linkspotter, metrica, mgc, miRLAB, miRSM, MVN, MXM, nda, pgraph, PhyloProfile, scperturbR, Statsomat, stops, TDAkit, VariableScreening
||compositions, copulaSim, correlation, dimRed, FCPS, Pigengene, shotGroups, steadyICA, tourr
Please use the canonical form
to link to this page.