mdc_test {MDCcure} | R Documentation |
MDC-Based Dependence Tests Between Multivariate Data and a Covariate
Description
Computes dependence between a multivariate dataset x
and a univariate covariate y
using different variants of the MDC (martingale difference correlation) test.
Usage
mdc_test(x, y, method, permutations = 999, parallel = TRUE, ncores = -1)
Arguments
x |
Vector or matrix where rows represent samples, and columns represent variables. |
y |
Covariate vector. |
method |
Character string indicating the test to perform. One of:
|
permutations |
Number of permutations. Defaults to 999. |
parallel |
Logical. Whether to use parallel computing. Defaults to |
ncores |
Number of threads for parallel computing (used only if |
Value
A list containing the test results and p-values.
References
Shao, X., and Zhang, J. (2014). Martingale difference correlation...
Examples
set.seed(123)
x <- matrix(rnorm(50 * 5), nrow = 50)
y <- rbinom(50, 1, 0.5)
mdc_test(x, y, method = "FMDCU")