```{r, echo=FALSE, include=FALSE} ## 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` [](http://git.leg.ufpr.br/ci/projects/3?ref=master) Build status for the stable version (`master` branch) [](http://git.leg.ufpr.br/ci/projects/3?ref=devel) Build status for the development version (`devel` branch) The `mcglm` package fit multivariate covariance generalized linear models (Bonat and Jorgensen, 2015). ## Introduction `mcglm` fit 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](http://cran-r.c3sl.ufpr.br/web/packages/devtools/index.html)) to install automatically from this GitLab repository: ```{r, eval=FALSE} library(devtools) install_git("http://git.leg.ufpr.br/wbonat/mcglm.git") ``` Alternatively, download the package tarball: [`r pkg.source`][] and run from a UNIX terminal (make sure you are on the container file directory): ```{r, echo=FALSE, comment=NA} cmd <- paste("R CMD INSTALL -l /path/to/your/R/library", pkg.source) cat(cmd, sep = "\n") ``` Or, inside an `R` session: ```{r, echo=FALSE, comment=NA} 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`: ```{r, echo=FALSE, comment=NA} instw <- paste0("install.packages(", "\"", pkg.win, "\"", ", repos = NULL,\n", " dependencies = TRUE)") cat(instw, sep = "\n") ``` ### Development version By default, if you use `devtools::install_git()`, 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 ```r library(devtools) install_git("http://git.leg.ufpr.br/wbonat/mcglm.git", branch = "devel") ``` Note that the development version can contain bugs and other unknown features, so use it at your own risk! ## 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](./contributing.md) to collaborate. ## License This package is released under the [GNU General Public License (GPL) v3.0][]. See [LICENSE](./LICENSE) <!-- links --> ```{r, echo=FALSE, include=FALSE} pkg.source.link <- paste0("http://www.leg.ufpr.br/~leg/mcglm/source/", pkg.source) pkg.win.link <- paste0("http://www.leg.ufpr.br/~leg/mcglm/source/", pkg.win) ``` [GNU General Public License (GPL) v3.0]: http://www.gnu.org/licenses/gpl-3.0.html [`roxygen2`]: https://github.com/klutometis/roxygen [`devtools`]: https://github.com/hadley/devtools [`r pkg.source`]: `r pkg.source.link` [`r pkg.win`]: `r pkg.win.link` [mcglm-manual.pdf]: http://www.leg.ufpr.br/~leg/mcglm/source/mcglm-manual.pdf [Gitflow worflow]: http://nvie.com/posts/a-successful-git-branching-model/