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GHRmodel: Bayesian Hierarchical Modelling of Spatio-Temporal Health Data (original) (raw)

Supports modeling health outcomes using Bayesian hierarchical spatio-temporal models with complex covariate effects (e.g., linear, non-linear, interactions, distributed lag linear and non-linear models) in the 'INLA' framework. It is designed to help users identify key drivers and predictors of disease risk by enabling streamlined model exploration, comparison, and visualization of complex covariate effects. See an application of the modelling framework in Lowe, Lee, O'Reilly et al. (2021) <doi:10.1016/S2542-5196(20)30292-8>.

Version: 0.1.1
Depends: R (≥ 4.1.0)
Imports: cowplot, dlnm, dplyr, ggplot2 (≥ 3.5.0), GHRexplore, rlang, scales, tidyr, tidyselect
Suggests: INLA, sf, sn, RColorBrewer, colorspace, testthat (≥ 3.0.0), spdep, knitr, rmarkdown
Published: 2025-11-07
DOI: 10.32614/CRAN.package.GHRmodel
Author: Carles Milà ORCID iD [aut, cre], Giovenale Moirano ORCID iD [aut], Anna B. Kawiecki ORCID iD [aut], Rachel Lowe ORCID iD [aut]
Maintainer: Carles Milà <carles.milagarcia at bsc.es>
BugReports: https://gitlab.earth.bsc.es/ghr/ghrmodel/-/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://gitlab.earth.bsc.es/ghr/ghrmodel,https://bsc-es.github.io/GHRtools/docs/GHRmodel/GHRmodel
NeedsCompilation: no
Additional_repositories: https://inla.r-inla-download.org/R/stable
Materials: README, NEWS
CRAN checks: GHRmodel results

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