norm_matrix_K: Computation of the K-norm of a set of functions

In ardeeshany/FLAME: FLAME for high-dimensional Function-on-Scalar regression problems

Description

It computes the norm associated to the kernel K of a set of functions. The functions are represented as their projection on a kernel basis.

Usage

norm_matrix_K(M, eigenval)

Arguments

M	matrix. J \times N matrix containing in the column n the coefficients of the projection of a function y_n on the J eigenfunctions of the kernel.
eigenval	vector. J-length vector of the eigenvalues of the kernel.

Value

vector of length N containing the K-norm of the functions

Examples

data(SobolevKernel)
data(simulation)
norm_K = sum(norm_matrix_K(Y_matrix, eigenval))

ardeeshany/FLAME documentation built on May 14, 2019, 8:41 a.m.