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

 `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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23``` ```## 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) ```