Calculates the randomized dependence coefficient based on interim results. It is a generalized dependence measure based on maximum correlation of random non-linear projections.
rdcPart(subsetX, xTrans, yTrans, s=1/6, f=sin, randX)Subset of the covariate matrix as indices (integer vector).
Transformed matrix to the [0, 1] scale (numeric matrix).
Random, non-linear projection of the response (numeric vector).
Variance of the random weights. Default is 1/6.
Non-linear transformation function. Default is sin.
Random weights (numeric vector).
Value of randomized dependence coefficient (numeric scalar).
This function allows for more efficient calculation than the complete calculation by excluding repetitive calculations.
David Lopez-Paz et. al, (2013), The randomized dependence coefficient, Proceedings of Advances in Neural Information Processing Systems 26 (NIPS)