Description Usage Arguments Value References Examples
mdc
measures conditional mean dependence of Y
given X
,
where each contains one variable (univariate) or more variables (multivariate).
1 | 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 high-dimensional variable screening. Journal of the American Statistical Association, 109(507), 1302-1318. 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), 1492-1517. http://dx.doi.org/10.1214/15-EJS1047.
1 2 3 4 5 6 |
[1] 0.08638844
[1] 0.3804826
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