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fibr  

Prior-Fraction Diagnostics for Hierarchical Models
View on CRAN: Click here


Download and install fibr package within the R console
Install from CRAN:
install.packages("fibr")

Install from Github:
library("remotes")
install_github("cran/fibr")

Install by package version:
library("remotes")
install_version("fibr", "0.1.1")



Attach the package and use:
library("fibr")
Maintained by
Aidan D Bindoff
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-29
Latest Update: 2026-06-29
Description:
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.
How to cite:
Aidan D Bindoff (2026). fibr: Prior-Fraction Diagnostics for Hierarchical Models. R package version 0.1.1, https://cran.r-project.org/web/packages/fibr. Accessed 05 Aug. 2026.
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