multilevel_exponential_fpca: Estimate mean function, eigenfunctions, and eigenvalues for...

In acweisha/gFPCAClassif: Classification of Binary Functional Data

Description

Estimate mean function, eigenfunctions, and eigenvalues for the multilevel model using the Exponential approximation

Usage

multilevel_exponential_fpca(
  X_dat,
  J,
  pve1 = 0.99,
  pve2 = 0.99,
  fix_number_of_functions = NA,
  k = 5,
  bs0 = "cr"
)

Arguments

X_dat	NJ x D matrix of observations
J	Number of realizations per individual
pve1	Proportion of variance explained for the first component
pve2	Proportion of variance explained for the second component
fix_number_of_functions	if you do not want to used PVE you can fix the number of eigenfunctions to output
k	number of basis functions in the
bs0	The basis functions used when smoothing the covariance functions

Value

Mean function, eigenfunctions and eigenvalues for both types of covariance functions

acweisha/gFPCAClassif documentation built on Dec. 18, 2021, 10:23 p.m.