jmcm: Joint Mean-Covariance Models in R.

Features

• Efficient for large data sets, using algorithms from the Armadillo linear algebra package via the RcppArmadillo interface layer.
• Fits joint mean-covariance models based on three Cholesky decomposition-type covariance structure modelling methods, namely modified Cholesky decomposition (MCD), alternative Cholesky decomposition (ACD) and hyperpherical parameterization of Cholesky factor (HPC).

Citation

To cite jmcm in publications use:

Pan J and Pan Y (2017). “jmcm: An R Package for Joint Mean-Covariance Modeling of Longitudinal Data.” Journal of Statistical Software, 82(9), pp. 1–29. doi: 10.18637/jss.v082.i09.

Corresponding BibTeX entry:

@Article{,
  title = {{jmcm}: An {R} Package for Joint Mean-Covariance Modeling
    of Longitudinal Data},
  author = {Jianxin Pan and Yi Pan},
  journal = {Journal of Statistical Software},
  year = {2017},
  volume = {82},
  number = {9},
  pages = {1--29},
  doi = {10.18637/jss.v082.i09},
}

Installation

Get the development version from github:

install.packages("devtools")
library(devtools)
devtools::install_github("ypan1988/jmcm", dependencies=TRUE)

Or the released version from CRAN:

install.packages("jmcm")