MJMbamlss: Multivariate Joint Models with 'bamlss'

Multivariate joint models of longitudinal and time-to-event data based on functional principal components implemented with 'bamlss'. Implementation for Volkmann, Umlauf, Greven (2023) <arXiv:2311.06409>.

Version: 0.1.0
Depends: R (≥ 3.5), mgcv, bamlss
Imports: stats, funData, statmod, mvtnorm, zoo, coda, gamm4, Matrix, refund, utils, fdapace, sparseFLMM, MFPCA, foreach
LinkingTo: Rcpp, RcppEigen
Suggests: testthat (≥ 3.0.0), splines, tidyverse
Published: 2023-11-27
Author: Nikolaus Umlauf ORCID iD [aut], Alexander Volkmann [aut, cre]
Maintainer: Alexander Volkmann <alexander.volkmann at hu-berlin.de>
License: GPL-3
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: MJMbamlss results

Documentation:

Reference manual: MJMbamlss.pdf

Downloads:

Package source: MJMbamlss_0.1.0.tar.gz
Windows binaries: r-devel: MJMbamlss_0.1.0.zip, r-release: MJMbamlss_0.1.0.zip, r-oldrel: MJMbamlss_0.1.0.zip
macOS binaries: r-release (arm64): MJMbamlss_0.1.0.tgz, r-oldrel (arm64): MJMbamlss_0.1.0.tgz, r-release (x86_64): MJMbamlss_0.1.0.tgz

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