mdm_test {EDMeasure} | R Documentation |
mdm_test
tests mutual independence of all components in X
,
where each component contains one variable (univariate) or more variables (multivariate).
All tests are implemented as permutation tests.
mdm_test(X, dim_comp = NULL, num_perm = NULL, type = "comp_simp")
X |
A matrix or data frame, where rows represent samples, and columns represent variables. |
dim_comp |
The numbers of variables contained by all components in |
num_perm |
The number of permutation samples drawn to approximate the asymptotic distributions of mutual dependence measures. If omitted, an adaptive number is used. |
type |
The type of mutual dependence measures, including
From experiments, |
mdm_test
returns a list including the following components:
stat |
The value of the mutual dependence measure. |
pval |
The p-value of the mutual independence test. |
Jin, Z., and Matteson, D. S. (2017). Generalizing Distance Covariance to Measure and Test Multivariate Mutual Dependence. arXiv preprint arXiv:1709.02532. https://arxiv.org/abs/1709.02532.
## Not run: # X is a 10 x 3 matrix with 10 samples and 3 variables X <- matrix(rnorm(10 * 3), 10, 3) # assume X = (X1, X2) where X1 is 1-dim, X2 is 2-dim mdm_test(X, dim_comp = c(1, 2), type = "asym_dcov") # assume X = (X1, X2) where X1 is 2-dim, X2 is 1-dim mdm_test(X, dim_comp = c(2, 1), type = "sym_dcov") # assume X = (X1, X2, X3) where X1 is 1-dim, X2 is 1-dim, X3 is 1-dim mdm_test(X, dim_comp = c(1, 1, 1), type = "comp_simp") ## End(Not run)