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jmcm (version 0.1.3.0)

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.

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Version

Install

install.packages('jmcm')

Monthly Downloads

250

Version

0.1.3.0

License

GPL (>= 2)

Maintainer

Jianxin Pan

Last Published

May 13th, 2016

Functions in jmcm (0.1.3.0)

ACD-class

Class ACD
acd_estimation

Fit Joint Mean-Covariance Models based on ACD
hpc_estimation

Fit Joint Mean-Covariance Models based on HPC
meanplot

Plot Fitted Mean Curves
cattle

Cattle Data
$,MCD-method

Extract parts of MCD.
show,jmcmMod-method

Print information for jmcmMod-class
jmcmMod-class

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

Fit Joint Mean-Covariance Models
bootcurve

Plot Fitted Curves and Corresponding Confidence Interval using bootstrapping method
modular

Modular Functions for Joint Mean Covariance Model Fits
mcd_estimation

Fit Joint Mean-Covariance Models based on MCD
$,ACD-method

Extract parts of ACD.
HPC-class

Class HPC
$,HPC-method

Extract parts of HPC.
MCD-class

Class MCD
jmcmControl

Control of Joint Mean Covariance Model Fitting
getJMCM

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

Aids Data
regressogram

Plot Sample Regressograms and Fitted Curves