# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "mcglm" in publications use:' type: software license: GPL-3.0-only title: 'mcglm: Multivariate Covariance Generalized Linear Models' version: 0.9.0 doi: 10.32614/CRAN.package.mcglm abstract: Fitting multivariate covariance generalized linear models (McGLMs) to data. 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. authors: - family-names: Bonat given-names: Wagner Hugo email: wbonat@ufpr.br repository: https://bonatwagner.r-universe.dev repository-code: https://github.com/bonatwagner/mcglm commit: 6bc460bb25168f4ddd8b1f25abac2a2db818cb88 url: https://github.com/bonatwagner/mcglm date-released: '2025-12-14' contact: - family-names: Bonat given-names: Wagner Hugo email: wbonat@ufpr.br