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GHRmodel

0.1.1Package record

Bayesian Hierarchical Modelling of Spatio-Temporal Health Data

0packages depend
2.7Kdownloads / year
63.0%test coverage
13/13flavors OK

Overview

About

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.

Changes in 0.1.1
  • Fixed bug in the colour scale in the function plot_coef_crosspred().
  • Minor updates in the documentation.

From NEWS.md in the release

Install

Health

CRAN checks
13OK
Slowest check: 10.9 min · r-release-macos-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK12 OK2026-04-25
Show 1 earlier changeHide 1 earlier change
  • NOTE11 OK, 3 NOTE2026-03-10
Advisories

none known

Documentation

In release 0.1.1
READMEYes · 516 wordsVignettesYes · 3 · dynamicNEWSYes · 100% structured · mentions 0.1.1Citation fileNoWebsiteYes
Help pages
31 (1 internal)includes a package overview page
Examples that run
56%15 run in a plain check · 12 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples
100%
Documented parameters
96%
Return-value docs
100%
Help pages citing references
0%

Downloads

2.7K
CRAN downloads in the past year
Rank #15,313 · ~8/day · ~228/mo
Daily download trend is not available in this view yet.
31430 days
79690 days
2.7K1 year
Compare downloads with other packages →
Also on134 r2u6 autocran

Repository

0Stars
0Forks
0Open issues
1Open PRs
0Releases
479Commits
3Commit identities
License file reads as GPL-2.0 · 479 commits · Last activity 2026-05-22
Responsiveness
How these are sampled
PRs merged (all time)
90%
Median days to close, 50 most recently updated closed issues
GitHub only
Median days to close, 50 most recently updated closed PRs
GitHub only
PracticesBeta

Repository gitlab.earth.bsc.es/ghr/ghrmodel is linked, but repository-practices checks have not run for it yet. Checks are GitHub-only for now.

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
18 external dependencies (excludes base and recommended)

Installing GHRmodel adds 36 packages (18 with compiled code, 37 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, GHRexplore 3.8 MB.

Depends (1)
R >= 4.1.0
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (4)
Author, Maintainer since 0.1.0 (2025)
Releases (2)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.1Latest
    record
    2025-11-07 · current release · diff ↗
  • 0.1.0
    record
    2025-10-21
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-10-21
Total releases
2 / 1 yrs
License
GPL (>= 2) OSI
Additional repositories
inla.r-inla-download.org
Minimum R
≥ 4.1.0
Bundled data
87 KB / 3 files
Download size
6.2 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("GHRmodel")
Milà, C., Kawiecki, A. B., Lowe, R., & Moirano, G. (2025). GHRmodel: Bayesian Hierarchical Modelling of Spatio-Temporal Health Data (Version 0.1.1) [Computer software]. https://doi.org/10.32614/CRAN.package.GHRmodel

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for GHRmodel version 0.1.1 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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