mutual independence {energy} | R Documentation |
Energy Test of Mutual Independence
Description
The test statistic is the sum of d-1 bias-corrected squared dcor statistics where the number of variables is d. Implementation is by permuation test.
Usage
mutualIndep.test(x, R)
Arguments
x |
data matrix or data frame |
R |
number of permutation replicates |
Details
A population coefficient for mutual independence of d random variables, , is
which is non-negative and equals zero iff mutual independence holds. For example, if d=4 the population coefficient is
A permutation test is implemented based on the corresponding sample coefficient. To test mutual independence of
the test statistic is the sum of the d-1
statistics (bias-corrected statistics):
.
Value
mutualIndep.test
returns an object of class power.htest
.
Note
See Szekely and Rizzo (2014) for details on unbiased and bias-corrected
(
bcdcor
) statistics.
Author(s)
Maria L. Rizzo mrizzo@bgsu.edu and Gabor J. Szekely
References
Szekely, G.J., Rizzo, M.L., and Bakirov, N.K. (2007),
Measuring and Testing Dependence by Correlation of Distances,
Annals of Statistics, Vol. 35 No. 6, pp. 2769-2794.
doi:10.1214/009053607000000505
Szekely, G.J. and Rizzo, M.L. (2014), Partial Distance Correlation with Methods for Dissimilarities. Annals of Statistics, Vol. 42 No. 6, 2382-2412.
See Also
Examples
x <- matrix(rnorm(100), nrow=20, ncol=5)
mutualIndep.test(x, 199)