mdc {EDMeasure}  R Documentation 
mdc
measures conditional mean dependence of Y
given X
,
where each contains one variable (univariate) or more variables (multivariate).
mdc(X, Y, center = "U")
X 
A vector, matrix or data frame, where rows represent samples, and columns represent variables. 
Y 
A vector, matrix or data frame, where rows represent samples, and columns represent variables. 
center 
The approach for centering, including

mdc
returns the squared martingale difference correlation of Y
given X
.
Shao, X., and Zhang, J. (2014). Martingale difference correlation and its use in highdimensional variable screening. Journal of the American Statistical Association, 109(507), 13021318. http://dx.doi.org/10.1080/01621459.2014.887012.
Park, T., Shao, X., and Yao, S. (2015). Partial martingale difference correlation. Electronic Journal of Statistics, 9(1), 14921517. http://dx.doi.org/10.1214/15EJS1047.
# X, Y are 10 x 2 matrices with 10 samples and 2 variables
X < matrix(rnorm(10 * 2), 10, 2)
Y < matrix(rnorm(10 * 2), 10, 2)
mdc(X, Y, center = "U")
mdc(X, Y, center = "D")