# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "RBaM" in publications use:' type: software license: GPL-3.0-only title: 'RBaM: Bayesian Modeling: Estimate a Computer Model and Make Uncertain Predictions' version: 1.1.2 doi: 10.32614/CRAN.package.RBaM abstract: '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) . Examples of applications include Mansanarez et al. (2019) , Le Coz et al. (2021) , Perret et al. (2021) , Darienzo et al. (2021) and Perret et al. (2023) .' authors: - family-names: Renard given-names: Benjamin email: benjamin.renard@inrae.fr orcid: https://orcid.org/0000-0001-8447-5430 repository: https://bam-tools.r-universe.dev repository-code: https://github.com/BaM-tools/RBaM commit: 5108898da7d63636322c3ff45b1b8adafd716a74 url: https://github.com/BaM-tools/RBaM date-released: '2026-04-09' contact: - family-names: Renard given-names: Benjamin email: benjamin.renard@inrae.fr orcid: https://orcid.org/0000-0001-8447-5430