compute_var

Vector containing the estimated variances on each dimension.

sigma_sq

List containing the multivariate Eigenvalues for each variance
component.

values

Vector containing the squared norms to be used as weights on
the Eigenvalues.

norms_sq

Pre-specified level of explained variance of results of
MFPCA.

mfpc_cutoff

This is an internal function. The function takes all the information needed
to calculate how many FPCs are needed to reach the pre-specified cutoff
level.

internal

An implementation for multivariate functional additive mixed
models (multiFAMM), see Volkmann et al. (2021, <arXiv:2103.06606>). It builds on developed methods for univariate sparse
functional regression models and multivariate functional principal component
analysis. This package contains the function to run a multiFAMM and some
convenience functions useful when working with large models. An additional
package on GitHub contains more convenience functions to reproduce the
analyses of the corresponding paper
(<https://github.com/alexvolkmann/multifammPaper>).

compute_var: Compute the Number of FPCs needed

Description

Usage

Arguments