# dCov: Calculating distance covariance of two vectors or columns of... In nda: Generalized Network-Based Dimensionality Reduction and Analysis

 dCov R Documentation

## Calculating distance covariance of two vectors or columns of a matrix

### Description

Calculating distance covariance of two vectors or columns of a matrix for Generalized Network-based Dimensionality Reduction and Analysis (GNDA).

The calculation is very slow for large matrices!

dCov(x,y=NULL)

### Arguments

 x a numeric vector, a numeric matrix (in this case y=NULL), or a numeric data frame (in this case y=NULL) y a numeric vector (optional)

### Details

If x is a numeric vector, y must be specified. If x is a numeric matrix or numeric data frame, y must be ignored from the parameters.

### Value

Either a distance covariance value of vectors x and y, or a distance covariance matrix of x.

### Author(s)

Prof. Zsolt T. Kosztyan, Department of Quantitative Methods, Institute of Management, Faculty of Business and Economics, University of Pannonia, Hungary

e-mail: kosztyan.zsolt@gtk.uni-pannon.hu

### References

Rizzo M, Szekely G (2021). _energy: E-Statistics: Multivariate Inference via the Energy of Data_. R package version 1.7-8, <URL: https://CRAN.R-project.org/package=energy>.

### Examples

# Specification of distance covariance value of vectors x and y.
x<-rnorm(36)
y<-rnorm(36)
dCov(x,y)
# Specification of distance covariance matrix.
x<-matrix(rnorm(36),nrow=6)
dCov(x)

nda documentation built on Sept. 27, 2023, 9:08 a.m.