kernelPSI (version 1.1.1)

quadHSIC: Determines the quadratic form of the HSIC unbiased estimator

Description

For a linear kernel of the outcome \(L = Y^\top Y\), the unbiased HSIC estimator implemented in HSIC can be expressed as a quadratic form of the outcome \(Y\) i.e. \(HSIC(K, L) = Y^\top Q(K) Y\). Here, the matrix \(Q\) only depends on the kernel similarity matrix \(K\).

Usage

quadHSIC(K)

Arguments

K

kernel similarity matrix

Value

the matrix of the HSIC estimator quadratic form

Examples

# NOT RUN {
n <- 50
p <- 20
X <- matrix(rnorm(n*p), nrow = n, ncol = p)
K <-  X %*% t(X) / p
Q <- quadHSIC(K)
# }