Prior-Fraction Diagnostics for Hierarchical Models R package fibr version 0.1.1 Computes the prior fraction, the per-group pooling or shrinkage factor, for hierarchical models, including directly from 'brms' fits. For each group-level coefficient the prior fraction is the share of the posterior precision contributed by the shrinkage prior relative to the likelihood; values near one indicate a coefficient that is prior-dominated (the centring/non-centring funnel regime), values near zero indicate a likelihood-dominated coefficient that is well identified from the data. These quantities are invisible to standard convergence diagnostics such as R-hat and effective sample size, and they indicate where a non-centred reparameterisation is likely to help. A companion advisor reports the same decomposition for changepoint random effects fitted with 'smoothbp'. The underlying geometry (the Fisher-metric connection on the base-fiber split, for which this connection is flat so the obstruction is statistical rather than geometric) is described in Bindoff (2026) <doi:10.5281/zenodo.20724550>; code reproducing the paper is in the package's source repository. Software Depends: R (>= 4.1.0) Imports: posterior (>= 1.4.0), ggplot2 Suggests: brms, smoothbp, cmdstanr, testthat (>= 3.0.0) Aidan D Bindoff <aidan.bindoff@utas.edu.au> Comprehensive R Archive Network (CRAN) Aidan D Bindoff [aut, cre] (ORCID: <https://orcid.org/0000-0002-0943-2702>) MIT + file LICENSE (https://CRAN.R-project.org/package=fibr/LICENSE) 2026-06-29 application/tgz https://CRAN.R-project.org/package=fibr doi:10.32614/CRAN.package.fibr