My_DCOR: my program to get distance correlation

In jasonzyx/aSPC: An Adaptive Sum of Powered Correlation Test (aSPC) to Test Global Association Between Two Groups of Variables

Description

my program to get distance correlation

Usage

My_DCOR(A, B, dVarX, dVarY)

Arguments

A,	doubly centered matrix from get_doublyCenterDist(x, index)$mat
B,	doubly centered matrix from get_doublyCenterDist(x, index)$mat
dVarX,	doubly centered matrix from get_doublyCenterDist(x, index)$dVar
dVarY,	doubly centered matrix from get_doublyCenterDist(x, index)$dVar

Value

the P-values of SPC and aSPC tests

References

Xu Z., Pan W. An adaptive and powerful test for two groups of variables with high dimension

Examples

library(mvtnorm)
sigma = diag(0.9, 10) + 0.1
n = 500 # sample size
Z = rmvnorm(n=n, mean=rep(0,10), sigma=sigma)
X = rmvnorm(n=n, mean=rep(0,25), sigma=diag(1, 25))
Y = rmvnorm(n=n, mean=rep(0,25), sigma=diag(1, 25))
X = as.data.frame(cbind(Z[,1:5], X))
Y = as.data.frame(cbind(Z[,6:10], Y))
dim(X)
dim(Y)
set.seed(123) # to ensure we can replicate the permutation P-value

a = proc.time()
aSPC_dcor(X, Y, pow = c(1:8, Inf), B = 50)
proc.time() - a

a = proc.time()
aSPC(X, Y, pow = c(1:8, Inf), B = 50, method = "dcor_fast")
proc.time() - a

a = proc.time()
aSPC(X, Y, pow = c(1:8, Inf), B = 50, method = "dcor")
proc.time() - a

jasonzyx/aSPC documentation built on May 18, 2019, 5:55 p.m.