R Observatory: Metrics for RBaM version 1.1.2

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

RBaM

1.1.2

Bayesian Modeling: Estimate a Computer Model and Make Uncertain Predictions

1packages depend

4.4Kdownloads / year

–test coverage

13/13checks pass

Overview

About

Maintained by Benjamin RenardFirst published 2025-07-103 releasesCRAN page ↗GitHub ↗

An interface to the 'BaM' (Bayesian Modeling) engine, a 'Fortran'-based executable aimed at estimating a model with a Bayesian approach and using it for prediction, with a particular focus on uncertainty quantification. Classes are defined for the various building blocks of 'BaM' inference (model, data, error models, Markov Chain Monte Carlo (MCMC) samplers, predictions). The typical usage is as follows: (1) specify the model to be estimated; (2) specify the inference setting (dataset, parameters, error models...); (3) perform Bayesian-MCMC inference; (4) read, analyse and use MCMC samples; (5) perform prediction experiments. Technical details are available (in French) in Renard (2017) https://hal.science/hal-02606929v1. Examples of applications include Mansanarez et al. (2019) doi:10.1029/2018WR023389, Le Coz et al. (2021) doi:10.1002/hyp.14169, Perret et al. (2021) doi:10.1029/2020WR027745, Darienzo et al. (2021) doi:10.1029/2020WR028607 and Perret et al. (2023) doi:10.1061/JHEND8.HYENG-13101.

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("RBaM", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("BaM-tools/RBaM")

Development version from BaM-tools/RBaM. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-rbam

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-RBaM

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-RBaM

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

13OK

Slowest check: 2.5 min · r-oldrel-windows-x86_64

Code health

None

Tests · ratio 0.00

not tracked

Coverage

100%

Documentation · exports

12

Dependencies · direct

Check history

OK2026-08-05
13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
NOTE2026-08-01
12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
OK2026-03-10
14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMEYes · 784 wordsVignettesNopkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 92%
Return-value docs: 100%
References docs: 0%

Downloads

4.4K

CRAN downloads in the past year

Rank #9,677 · ~12/day · ~367/mo

Releases R versions

Daily download trend is not available in this view yet.

14530 days

97990 days

4.4K1 year

Compare downloads with other packages →

Also on106 r2u15 autocran

Repository

GitHub ↗ bam-tools/rbam

1Stars

2Forks

5Open issues

0Open PRs

2Releases

90Commits

3Contributors

bayesian-inferenceuncertaintymodelingstatisticsr

License GPL-3.0 · 90 commits · Last activity 2026-04-09

Stars over time

2022-11-08 · 12026-07-07 · 1

Repository practices

Upstream repositoryBeta

5 development-tooling and community-health practices detected across 5 families in the upstream repository

Checks run against github.com/bam-tools/rbam on 2026-08-16.

Continuous integration (1)

GitHub Actions

Reproducibility and dev environment (1)

data-raw/

CRAN release process (1)

cran-comments.md

Docs source (1)

README.Rmd

Show all practices

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies

9 external dependencies (excludes base and recommended)

Depends (1)

R >= 4.0.0

Imports (12)

ggplot2 gridExtra R.utilsutilsgrDevicesstatsrjson rlangtoolstidyr mvtnorm progress

LinkingTo (0)

none

Suggests (1)

rmarkdown

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

1direct

0indirect

ShiftHappens

Code & Tests

Datasets

People & History

People (3)

Maintainer (1)

Benjamin Renard

Author, Maintainer, Copyright holder

Authors (1)

Benjamin Renard

Author, Maintainer, Copyright holder

Copyright holders (1)

Benjamin Renard

Author, Maintainer, Copyright holder

Funders (2)

INRAE

Funder

Ministère de la Transition Ecologique - SCHAPI

Funder

Package Timeline

3 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
1.1.2Latest
2026-01-08 · current release · diff ↗
1.1.1
2025-09-30 · diff ↗
1.0.1
2025-07-10
R
R 4.5.0 released · 2025-04-11

Package metadata

First published: 2025-07-10
Total releases: 3 / 1 yrs
License: GPL-3 OSI
Minimum R: ≥ 4.0.0
Bundled data: 2.7 KB / 3 files
Download size: 381 KB
Installed size: not tracked yet
With dependencies: not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("RBaM")

Format

Renard, B., INRAE, & Ministère de la Transition Ecologique - SCHAPI. (2026). RBaM: Bayesian Modeling: Estimate a Computer Model and Make Uncertain Predictions (Version 1.1.2) [Computer software]. https://doi.org/10.32614/CRAN.package.RBaM

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

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

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for RBaM version 1.1.2 [Data set]. HJJB, LLC. Data release v2026-08-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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