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 (McGLMs).
Introduction
McGLM is a general framework for non-normal multivariate data analysis, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link function combined with a matrix linear predictor involving known matrices. The models take non-normality into account in the conventional way by means of a variance function, and the mean structure is modelled by means of a link function and a linear predictor. The models are fitted using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of different types of response variables and covariance structures, including multivariate extensions of repeated measures, time series, longitudinal, spatial and spatio-temporal structures. The package offers a user-friendly interface for fitting McGLMs similar to the glm() R function. See Bonat (2018), for more information and examples.
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: mcglm_0.6.0.tar.gz and run from a UNIX terminal (make sure you are on the container file directory):
R CMD INSTALL -l /path/to/your/R/library mcglm_0.6.0.tar.gzOr, inside an R session:
install.packages("mcglm_0.6.0.tar.gz", repos = NULL,
lib.loc = "/path/to/your/R/library",
dependencies = TRUE)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: mcglm_0.6.0.zip (do not unzip it under Windows), put the file in your working directory, and from inside R:
install.packages("mcglm_0.6.0.zip", repos = NULL,
dependencies = TRUE)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!
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.