# R/identCorrelationMatricesTest.r In ldstatsHD: Linear Dependence Statistics for High-Dimensional Data

#### Defines functions identCorrelationMatrices.test

```identCorrelationMatrices.test  <- function(D1, testStatistic = c("AS", "max", "exc"),
testNullDist = c("asyIndep", "asyDep", "np"), nite= 500,
threshold = 2.3, excAdj = TRUE, conf.level = 0.95,
norm.approx = FALSE, ...)
{
## Data scaling
D1    <- scale(D1)
N     <- dim(D1)
P     <- dim(D1)

## Fisher Transform correlation differences
Test  <- ztransf(lowerTri(cor(D1))) * sqrt(N-3)
P2    <- length(Test)

## Permutations
if(any(testNullDist=="asyDep") | any(testNullDist=="np"))
{
pb       <- txtProgressBar(min = 0, max = nite, style = 3)

## Monte Carlo
TestsP <- array(0,dim=c(nite,P2))
for(k in 1:nite){
setTxtProgressBar(pb, k)
D2 		  <- mvrnorm(N, rep(0,P), diag(rep(1,P)))
TestsP[k,] <- ztransf(lowerTri(cor(D2))) * sqrt(N-3)
}
close(pb)
}
else
TestsP <- NULL

## Functions call
obj <- list()

## Tests
if(any(testNullDist == "asyDep"))
{
if(any(testStatistic == "AS"))
obj\$AS\$ad  <- equalCorrelationsTestSS(Test = Test, theta = NULL, TestsP = TestsP, sumSquares = TRUE, dependency = TRUE,
conf.level = conf.level, norm.approx = norm.approx)
if(any(testStatistic == "max"))
obj\$MAX\$ad  <- equalCorrelationsTestMax(Test = Test, theta = NULL, TestsP = TestsP, dependency = TRUE, N = N, P = P,
nite = nite, psiAdj = FALSE, thetaKnown = NULL, conf.level = conf.level)
if(any(testStatistic == "exc"))
obj\$EXC\$ad  <- equalCorrelationsTestExc(Test = Test, theta = NULL, TestsP = TestsP, dependency = TRUE, EX = threshold,
}

if(any(testNullDist == "asyIndep"))
{
if(any(testStatistic=="AS"))
obj\$AS\$ai  <- equalCorrelationsTestSS(Test = Test, theta = NULL, TestsP = NULL, sumSquares = TRUE, dependency = FALSE,
conf.level = conf.level, norm.approx = norm.approx)
if(any(testStatistic == "max"))
obj\$MAX\$ai  <- equalCorrelationsTestMax(Test = Test, theta = NULL, TestsP = NULL, dependency = FALSE, N = N, P = P,
nite = 0, psiAdj = FALSE, thetaKnown = 0, conf.level = conf.level)
if(any(testStatistic == "exc"))
obj\$EXC\$ai  <- equalCorrelationsTestExc(Test = Test, theta = NULL, TestsP = NULL, dependency = FALSE, EX = threshold,
}

if(any(testNullDist=="np"))
{
resAUX  <- equalCorrelationsTestPerm(Test = Test, theta = NULL, TestsP = TestsP, sumSquares = TRUE, dependency = TRUE,

if(any(testStatistic=="AS"))    obj\$AS\$np 	<- resAUX\$AS
if(any(testStatistic=="max"))   obj\$MAX\$np <- resAUX\$MAX
if(any(testStatistic=="exc"))   obj\$EXC\$np <- resAUX\$EXC
}

return(obj)
}
```

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ldstatsHD documentation built on Aug. 14, 2017, 5:06 p.m.