rdcor (version 1.0)

Permutation-based hypothesis testing for the rank distance correlation: Permutation-based hypothesis testing for the rank distance correlation

Description

Permutation-based hypothesis testing for the rank distance correlation.

Usage

rdcor.test(y, x, B = 499)

Value

If x is a vector a vector with the rank distance correlation and the permuation-based p-value. If x is a matrix, this returns a matrix with two columns: the rank distance correlation and the permutation-based p-value.

Arguments

y

A numerical vector.

x

A numerical vector or a numerical matrix.

B

The number of permutations to implement.

Author

Michail Tsagris.

R implementation and documentation: Michail Tsagris .

Details

Permutation-based hypothesis testing between y and x or between y and each column of x is performed.

References

Shi H., Drton M. and Han F. (2022). Distribution-free consistent independence tests via center-outward ranks and signs. Journal of the American Statistical Association, 117(537): 395--410.

Zhang Q. (2025). On the connections between Chatterjee's correlation and rank distance correlation. Journal of Nonparametric Statistics, 1--18.

See Also

rdcor, rdcor.mat

Examples

y <- iris[, 1]
x <- matrix( rnorm(150 * 10), ncol = 10 )
rdcor.test(y, x)