mdc {MDCcure} | R Documentation |
Martingale Difference Correlation (MDC)
Description
mdc
computes the squared martingale difference correlation between a response variable Y
and explanatory variable(s) X
, measuring conditional mean dependence.
X
can be either univariate or multivariate.
Usage
mdc(X, Y, center = "U")
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. |
center |
Character string indicating the centering method to use. One of:
|
Value
Returns the squared martingale difference correlation of Y
given X
.
References
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. doi:10.1080/01621459.2014.887012.
See Also
Examples
# Generate example data
set.seed(123)
n <- 50
x <- matrix(rnorm(n * 5), nrow = n) # multivariate data with 5 variables
y <- rbinom(n, 1, 0.5) # binary covariate
# Compute MDC with U-centering
mdc(x, y, center = "U")
# Compute MDC with double-centering
mdc(x, y, center = "D")