pmdc {MDCcure} | R Documentation |
Partial Martingale Difference Correlation (pMDC)
Description
pmdd
measures conditional mean dependence of Y
given X
, adjusting for the dependence on Z
.
Usage
pmdc(X, Y, Z)
Arguments
X |
A vector or matrix where rows represent samples and columns represent variables. |
Y |
A vector or matrix where rows represent samples and columns represent variables. |
Z |
A vector or matrix where rows represent samples and columns represent variables. |
Value
Returns the squared partial martingale difference correlation of Y
given X
, adjusting for the dependence on Z
.
References
Park, T., Shao, X., and Yao, S. (2015). Partial martingale difference correlation. Electronic Journal of Statistics, 9(1), 1492-1517. doi:10.1214/15-EJS1047.
Examples
# Generate example data
set.seed(123)
n <- 50
x <- matrix(rnorm(n * 5), nrow = n) # explanatory variables
y <- matrix(rnorm(n), nrow = n) # response variable
z <- matrix(rnorm(n * 2), nrow = n) # conditioning variables
# Compute partial MDD
pmdd(x, y, z)
[Package MDCcure version 0.1.0 Index]