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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
Author: Jianxin Pan [aut, cre], Yi Pan [aut]
Maintainer: Jianxin Pan <Jianxin.Pan at manchester.ac.uk>
BugReports: https://github.com/ypan1988/jmcm/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/ypan1988/jmcm/
NeedsCompilation: yes
SystemRequirements: C++11
Citation: jmcm citation info
Materials: NEWS
CRAN checks: jmcm results

Documentation:

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

Downloads:

Package source: jmcm_0.2.4.tar.gz
Windows binaries: r-devel: jmcm_0.2.4.zip, r-release: jmcm_0.2.4.zip, r-oldrel: jmcm_0.2.4.zip
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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=jmcm to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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