Multivariate Distance Correlation for two sets of variables

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Description

Computes the distances within two sets of variables and the corresponding distance correlation.

Usage

1
dcorMVtable(x, ind = 1, method = "euclidean")

Arguments

x

A contingency table of class table.

ind

The indices for the first set of variables. The second set consists of all remaining variables.

method

The method for dist

Value

The distance correlation between 0 and 1 for the distances from the two sets of variables.

Note

This code has not been tested thoroughly and may still contain errors.

Author(s)

Alexander Pilhoefer

See Also

dcorMVdata, wdcor, approx.dcor

Examples

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## Not run: 
	A2 <- arsim(2000,c(8,9),5,0.1)
	A2 <- optile(A2, iter=100)
	BCI(A2)
	wdcor(A2)
	
	p1 <- runif(11)+0.1
	p1 <- p1/sum(p1)
	A2b <- apply(A2,1:2,function(z) rmultinom(1,z,p1))
	
	# now the first variable is roughly independent from the other two:
	
	dcorMVtable(as.table(A2b),ind = 1)
	
	# here the third variable is NOT independent from the others:
	A3 <- arsim(2000,c(8,9,11),5,0.1)
	A3 <- optile(A3, iter=100)
	BCI(A3)
	dcorMVtable(A3,ind = 3)
	
	

## End(Not run)

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