dcorMVtable: Multivariate Distance Correlation for two sets of variables

In extracat: Categorical Data Analysis and Visualization

Description

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

Usage

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

## 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)

extracat documentation built on July 17, 2018, 5:05 p.m.