In wbonat/mcglm: Multivariate Covariance Generalized Linear Models

## Get VERSION and create file names
ver <- sub(x=grep(x=readLines("DESCRIPTION"), pattern="^Version: ",
                  value=TRUE),
           pattern="^Version: ", replacement="")
pkg.name <- "mcglm_"
pkg.source <- paste0(pkg.name, ver, ".tar.gz")
pkg.win <- paste0(pkg.name, ver, ".zip")

mcglm r ver

Build status for the stable version (master branch)

Build status for the development version (devel branch)

The mcglm package fits multivariate covariance generalized linear models (Bonat and Jorgensen, 2016).

Introduction

mcglm fits multivariate covariance generalized linear models. It allows use a different linear predictor for each response variable of a multivariate response. The response variable can be continous or dicrete, like counts and binary and also limited continuos ou discrete/continuous inflated responses. The most important and relevant feature is that many covariance structures can be used to model the relations among variables.

This package is part of the Thesis of the first author.

Download and install

Linux/Mac

Use the devtools package (available from CRAN) to install automatically from this GitHub repository:

library(devtools)
install_github("wbonat/mcglm")

Alternatively, download the package tarball: [r pkg.source][] and run from a UNIX terminal (make sure you are on the container file directory):

cmd <- paste("R CMD INSTALL -l /path/to/your/R/library", pkg.source)
cat(cmd, sep = "\n")

Or, inside an R session:

inst <- paste0("install.packages(", "\"", pkg.source, "\"", ", repos = NULL,\n",
               "                 lib.loc = \"/path/to/your/R/library\",\n",
               "                 dependencies = TRUE)")
cat(inst, sep = "\n")

Note that -l /path/to/your/R/library in the former and lib.loc = "/path/to/your/R/library" in the latter are optional. Only use it if you want to install in a personal library, other than the standard R library.

Windows

Download Windows binary version: [r pkg.win][] (do not unzip it under Windows), put the file in your working directory, and from inside R:

instw <- paste0("install.packages(", "\"", pkg.win, "\"", ", repos = NULL,\n",
                "                 dependencies = TRUE)")
cat(instw, sep = "\n")

Development version

By default, if you use devtools::install_github(), or download any of the package tarball or Windows binary version, it will install the stable version of the package (from the master branch of this repository).

If you want to install the development version, you can use

library(devtools)
install_github("wbonat/mcglm", ref = "devel")

Note that the development version can contain bugs and other unknown features, so use it at your own risk!

Authors

• Wagner Hugo Bonat (author and main developer)
• Walmes Marques Zeviani (contributor)
• Fernando de Pol Mayer (contributor)

Documentation

The reference manual in PDF can be found here: mcglm-manual.pdf

Contributing

This R package is develop using [roxygen2][] for documentation and [devtools] to check and build. Also, we adopt the Gitflow worflow in this repository. Please, see the instructions for contributing to collaborate.

License

This package is released under the GNU General Public License (GPL) v3.0.

See LICENSE

pkg.source.link <- paste0(
    "https://github.com/wbonat/mcglm/raw/master/downloads/",
    pkg.source)
pkg.win.link <- paste0(
    "https://github.com/wbonat/mcglm/raw/master/downloads/",
    pkg.win)

[r pkg.source]: r pkg.source.link [r pkg.win]: r pkg.win.link

wbonat/mcglm documentation built on June 23, 2020, 11:06 a.m.