Package: jmcm 0.2.5

Jianxin Pan

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.

Authors:Jianxin Pan [aut, cre], Yi Pan [aut]

jmcm_0.2.5.tar.gz
jmcm_0.2.5.zip(r-4.7)jmcm_0.2.5.zip(r-4.6)jmcm_0.2.5.zip(r-4.5)
jmcm_0.2.5.tgz(r-4.6-x86_64)jmcm_0.2.5.tgz(r-4.6-arm64)jmcm_0.2.5.tgz(r-4.5-x86_64)jmcm_0.2.5.tgz(r-4.5-arm64)
jmcm_0.2.5.tar.gz(r-4.7-arm64)jmcm_0.2.5.tar.gz(r-4.7-x86_64)jmcm_0.2.5.tar.gz(r-4.6-arm64)jmcm_0.2.5.tar.gz(r-4.6-x86_64)
jmcm_0.2.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
jmcm/json (API)
NEWS

# Install 'jmcm' in R:

install.packages('jmcm', repos = c('https://ypan1988.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/ypan1988/jmcm/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

aids - Aids Data
cattle - Cattle Data

On CRAN:

cholesky-decomposition covariance-models openblas cpp openmp

5.18 score 5 stars 1 packages 10 scripts 227 downloads 13 exports 4 dependencies

Last updated from:9a983360c9. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	152
linux-devel-x86_64	OK	154
source / vignettes	OK	184
linux-release-arm64	OK	145
linux-release-x86_64	OK	138
macos-release-arm64	OK	104
macos-release-x86_64	OK	192
macos-oldrel-arm64	OK	97
macos-oldrel-x86_64	OK	169
windows-devel	OK	185
windows-release	OK	127
windows-oldrel	OK	118
wasm-release	OK	110

Exports:acd_estimation bootcurve getJMCM hpc_estimation jmcm jmcmControl ldFormula mcd_estimation meanplot mkJmcmMod optimizeJmcm regressogram show

Dependencies:Formula Rcpp RcppArmadillo roptim

jmcm: An R Package for Joint Mean-Covariance Modelling of Longitudinal Data

Rendered fromjss2542.pdf.asisusingR.rsp::asison May 09 2026.

Last update: 2018-11-09
Started: 2018-11-09

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Fit Joint Mean-Covariance Models based on ACD	acd_estimation
Aids Data	aids
Plot Fitted Curves and Corresponding Confidence Interval using bootstrapping method	bootcurve
Cattle Data	cattle
Extract or Get Generalized Components from a Fitted Joint Mean Covariance Model	getJMCM getJMCM.jmcmMod
Fit Joint Mean-Covariance Models based on HPC	hpc_estimation
Fit Joint Mean-Covariance Models	jmcm
Control of Joint Mean Covariance Model Fitting	jmcmControl
Class "jmcmMod" of Fitted Joint Mean-Covariance Models.	jmcmMod-class
Fit Joint Mean-Covariance Models based on MCD	mcd_estimation
Plot Fitted Mean Curves	meanplot
Modular Functions for Joint Mean Covariance Model Fits	ldFormula mkJmcmMod modular optimizeJmcm
Plot Sample Regressograms and Fitted Curves	regressogram
Print information for jmcmMod-class	show,jmcmMod-method