Learn R Programming

jmcm (version 0.2.5)

Joint Mean-Covariance Models using 'Armadillo' and S4

Description

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.

Copy Link

Version

Install

install.packages('jmcm')

Monthly Downloads

250

Version

0.2.5

License

GPL (>= 2)

Issues

0

Pull Requests

0

Stars

5

Forks

3

Maintainer

Jianxin Pan

Last Published

October 13th, 2025

Functions in jmcm (0.2.5)

acd_estimation

Fit Joint Mean-Covariance Models based on ACD
getJMCM

Extract or Get Generalized Components from a Fitted Joint Mean Covariance Model
jmcm

Fit Joint Mean-Covariance Models
bootcurve

Plot Fitted Curves and Corresponding Confidence Interval using bootstrapping method
mcd_estimation

Fit Joint Mean-Covariance Models based on MCD
jmcmMod-class

Class "jmcmMod" of Fitted Joint Mean-Covariance Models.
hpc_estimation

Fit Joint Mean-Covariance Models based on HPC
jmcmControl

Control of Joint Mean Covariance Model Fitting
aids

Aids Data
modular

Modular Functions for Joint Mean Covariance Model Fits
regressogram

Plot Sample Regressograms and Fitted Curves
meanplot

Plot Fitted Mean Curves
show,jmcmMod-method

Print information for jmcmMod-class
cattle

Cattle Data