Learn R Programming

multiFAMM

This package provides 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. A development version of this package can be found on GitHub (alexvolkmann/multifamm). An additional package on GitHub contains more convenience functions to reproduce the analyses of the corresponding paper (alexvolkmann/multifammPaper).

Copy Link

Version

Install

install.packages('multifamm')

Monthly Downloads

243

Version

0.1.1

License

GPL (>= 2)

Maintainer

Alexander Volkmann

Last Published

September 28th, 2021

Functions in multifamm (0.1.1)

multiFAMM

Multivariate Functional Additive Mixed Model Regression
conduct_mfpca

Conduct the MFPCA
extract_components

Extract Model Components to be Compared
snooker

Snooker data
predict_mean

Predict The Mean Function For the FPC Plots
compute_var

Compute the Number of FPCs needed
extract_var_info

Extract Variance Information from MFPCA Object
prepare_mfpca

Prepare Information Necessary for MFPCA
phonetic_subset

Phonetic data (subset)
phonetic

Phonetic data
prune_mfpc

Prune the MFPC object to include only a prespecified level of explained var
extract_components_uni

Extract Model Components to be Compared from Univariate Model
refit_for_weights

Refit the model under an independence assumption