Description Usage Arguments Value References Examples
pmdc
measures conditional mean dependence of Y
given X
adjusting for the
dependence on Z
, where each contains one variable (univariate) or more variables (multivariate).
Only the U-centering approach is applied.
1 | pmdc(X, Y, Z)
|
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. |
Z |
A vector, matrix or data frame, where rows represent samples, and columns represent variables. |
pmdc
returns the squared partial martingale difference correlation
of Y
given X
adjusting for the dependence on Z
.
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.
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