jmcm: Joint Mean-Covariance Models using 'Armadillo' and S4

Fit joint mean-covariance models for longitudinal data. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Armadillo' C++ library for numerical linear algebra and 'RcppArmadillo' glue.

Version: 0.2.4
Depends: R (≥ 3.2.2)
Imports: Formula, methods, Rcpp (≥ 0.12.14)
LinkingTo: Rcpp, RcppArmadillo (≥ 0.9.900.1.0), roptim
Suggests: testthat, R.rsp
Published: 2021-01-12
DOI: 10.32614/CRAN.package.jmcm
Author: Jianxin Pan [aut, cre], Yi Pan [aut]
Maintainer: Jianxin Pan <Jianxin.Pan at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
SystemRequirements: C++11
Citation: jmcm citation info
Materials: NEWS
CRAN checks: jmcm results


Reference manual: jmcm.pdf
Vignettes: jmcm: An R Package for Joint Mean-Covariance Modelling of Longitudinal Data


Package source: jmcm_0.2.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): jmcm_0.2.4.tgz, r-oldrel (arm64): jmcm_0.2.4.tgz, r-release (x86_64): jmcm_0.2.4.tgz, r-oldrel (x86_64): jmcm_0.2.4.tgz
Old sources: jmcm archive

Reverse dependencies:

Reverse depends: varjmcm
Reverse suggests: slim


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