get_delaigle_eigen: Get True eigenfunction for simulation in Delaigle et...

In statKim/robfpca: Functional principal component analysis for partially observed elliptical process

Get True eigenfunction for simulation in Delaigle et al.(2021).

Description

True eigenfunctions are obtained for given grids from the setting of Delaigle et al.(2021) with model 2.

Usage

get_delaigle_eigen(grid, model = 2)

Arguments

grid	a vector containing the observed timepoints.
model	The model option for Delaigle et al.(2021).

Value

a p x k matrix containing the eigenfunctions where p is the length of grids and k is the number of true components.

References

Delaigle, A., Hall, P., Huang, W., & Kneip, A. (2021). Estimating the covariance of fragmented and other related types of functional data. Journal of the American Statistical Association, 116(535), 1383-1401.

Examples

gr <- seq(0, 1, length.out = 51)
eig.true <- get_delaigle_eigen(gr, model = 2)
matplot(eig.true, type = "l")

statKim/robfpca documentation built on April 15, 2023, 10:12 p.m.