generate.eigen.cubic: Grid Points and Eigendecomposition of Reproducing Kernal for...

In danqingxu/lrspline: Low-rank Approximation of Smoothing Splines for Massive Data

Description

Generates eigendecomposition from grid points from an interval.

Usage

generate.eigen.cubic(N = 1000, a = 0, b = 1)

Arguments

N	The number of grid points. It should be an integer. The default value is 1000.
a	The lower limit of the interval used for grid points. The default value is 0.
b	The upper limit of the interval used for grid points. The default value is 1.

Value

It returns (and saves) a list of following components:

e	A list of two elements of "values" and "vectors", which refer respectively, the eigenvalues and eigenfunctions of reproducing kernel for cubic splines at the pre-selected grid points.
xg	A vector of grid points.

Examples

## Not run: 
eigen_res <- generate.eigen.cubic(N=1000,a=2,b=3)

## End(Not run)

danqingxu/lrspline documentation built on Dec. 19, 2021, 8:10 p.m.