mdcov: Marginal distance covariance This function implements the...

In dcov: A Fast Implementation of Distance Covariance

Description

Marginal distance covariance This function implements the method of calculating distance covariance between y and each column in x

Usage

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

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

Arguments

y	the matrix of y
x	the matrix of x, distance covariance is calculated for each variable in x with y.
type	"V" or "U", for V- or U-statistics of distance covariance or correlation. The default value is "V".

Examples

n = 200; p = 10
y = matrix(rnorm(n*2),n,2)
x = matrix(rnorm(n*p),n,p)
res1 = mdcov(y,x)
res2 = numeric(p)
for(j in 1:p){res2[j] = dcov::dcov(y,x[,j])}
# res1 is same with res2
res1 - res2
res3 = mdcor(y,x)
res4 = numeric(p)
for(j in 1:p){res4[j] = dcov::dcor(y,x[,j])}
# res3 is same with res4
res3-res4

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