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The mcglm package fits multivariate covariance
generalized linear models (Bonat and Jorgensen, 2016).
mcglm is an R package designed to fit Multivariate
Covariance Generalized Linear Models. It allows you to specify a
distinct linear predictor for each response variable, offering
exceptional flexibility for analyses involving multiple outcomes.
With mcglm, you can model a wide range of response types
— continuous, discrete (such as counts and binary), limited, and even
zero inflated responses, whether continuous or mixed.
Its main strength lies in the ability to capture complex relationships between variables through multiple covariance structures, enabling more realistic and robust multivariate modeling.
This package was developed as part of the Wagner’s Ph.D. thesis, combining academic rigor with practical value for the statistical modeling community.
Use the devtools package (available from CRAN)
to install automatically from this GitHub repository:
library(devtools)
install_github("bonatwagner/mcglm")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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.