https://bonatwagner.r-universe.devRecent package updates in bonatwagnerR-universehttps://github.com/bonatwagner.pnghttps://bonatwagner.r-universe.devSun, 14 Dec 2025 20:57:50 GMTwbonat@ufpr.br (Wagner Hugo Bonat)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) <doi:10.18637/jss.v084.i04>, for more information and examples.https://github.com/r-universe/bonatwagner/actions/runs/39590407767Sun, 14 Dec 2025 20:57:50 GMTmcglm0.9.0successhttps://bonatwagner.r-universe.devhttps://github.com/bonatwagner/mcglmUniModels.RmdUniModels.htmlChoosing link, variance and covariance functions2025-11-27 23:48:002025-11-30 20:54:52GLMExamples.RmdGLMExamples.htmlFitting generalized linear models using the mcglm package2025-11-27 23:48:002025-11-30 20:54:52