dcov2d: Fast distance covariance for two bivariate variables

In dcov: A Fast Implementation of Distance Covariance

Description

This method implements the fast algorithm proposed by Huo and Székely. The result of dcov2d and dcor2d is same with the result of energy::dcov2d and energy::dcor2d

Usage

dcov2d(x, y, type = c("V", "U"))

dcor2d(x, y, type = c("V", "U"))

Arguments

x	the vector of x
y	the vector of y
type	"V" or "U", for V- or U-statistics of distance covariance or correlation. The default value is "V".

References

Székely, G. J., Rizzo, M. L., & Bakirov, N. K. (2007). Measuring and testing dependence by correlation of distances. The annals of statistics, 35(6), 2769-2794.

Székely, G. J., & Rizzo, M. L. (2013). The distance correlation t-test of independence in high dimension. Journal of Multivariate Analysis, 117, 193-213.

Huo, X., & Székely, G. J. (2016). Fast computing for distance covariance. Technometrics, 58(4), 435-447.

Examples

x = rnorm(200)
y = rnorm(200)
dcov2d(x,y)
dcor2d(x,y)

dcov documentation built on July 1, 2020, 6:20 p.m.