CRAN

jmcm 0.2.1

Joint Mean-Covariance Models using 'Armadillo' and S4

Released Nov 10, 2018 by Jianxin Pan

This package can be loaded by Renjin but 4 out 6 tests failed.

Dependencies

roptim 0.1.1 Rcpp Formula 1.2-3 lattice 0.20-38 RcppArmadillo 0.9.200.4.0

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.

Installation

Maven

This package can be included as a dependency from a Java or Scala project by including the following your project's pom.xml file. Read more about embedding Renjin in JVM-based projects.

<dependencies>
  <dependency>
    <groupId>org.renjin.cran</groupId>
    <artifactId>jmcm</artifactId>
    <version>0.2.1-b1</version>
  </dependency>
</dependencies>
<repositories>
  <repository>
    <id>bedatadriven</id>
    <name>bedatadriven public repo</name>
    <url>https://nexus.bedatadriven.com/content/groups/public/</url>
  </repository>
</repositories>

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Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:

library('org.renjin.cran:jmcm')

Test Results

This package was last tested against Renjin 0.9.2709 on Nov 12, 2018.

Source

R
C
C++

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Release History