mcglm: Multivariate Covariance Generalized Linear Models
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.
| Version: |
0.7.0 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
stats, Matrix, assertthat, graphics, Rcpp (≥ 0.12.16) |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
testthat, knitr, rmarkdown, MASS, mvtnorm, tweedie, devtools |
| Published: |
2021-07-11 |
| Author: |
Wagner Hugo Bonat [aut, cre],
Walmes Marques Zeviani [ctb],
Fernando de Pol Mayer [ctb] |
| Maintainer: |
Wagner Hugo Bonat <wbonat at ufpr.br> |
| BugReports: |
https://github.com/wbonat/mcglm/issues |
| License: |
GPL-3 | file LICENSE |
| URL: |
http://mcglm.leg.ufpr.br/ |
| NeedsCompilation: |
yes |
| Citation: |
mcglm citation info |
| CRAN checks: |
mcglm results |
Documentation:
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