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  "Title": "Prior-Fraction Diagnostics for Hierarchical Models",
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  "Authors@R": "person(\"Aidan D\", \"Bindoff\",\nemail   = \"aidan.bindoff@utas.edu.au\",\nrole    = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-0943-2702\"))",
  "Description": "Computes the prior fraction, the per-group pooling or\nshrinkage factor, for hierarchical models, including directly\nfrom 'brms' fits. For each group-level coefficient the prior\nfraction is the share of the posterior precision contributed by\nthe shrinkage prior relative to the likelihood; values near one\nindicate a coefficient that is prior-dominated (the\ncentring/non-centring funnel regime), values near zero indicate\na likelihood-dominated coefficient that is well identified from\nthe data. These quantities are invisible to standard\nconvergence diagnostics such as R-hat and effective sample\nsize, and they indicate where a non-centred reparameterisation\nis likely to help. A companion advisor reports the same\ndecomposition for changepoint random effects fitted with\n'smoothbp'. The underlying geometry (the Fisher-metric\nconnection on the base-fiber split, for which this connection\nis flat so the obstruction is statistical rather than\ngeometric) is described in Bindoff (2026)\n<doi:10.5281/zenodo.20724550>; code reproducing the paper is in\nthe package's source repository.",
  "License": "MIT + file LICENSE",
  "URL": "https://github.com/ABindoff/fibr,\nhttps://doi.org/10.5281/zenodo.20724550",
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  "Author": "Aidan D Bindoff [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-0943-2702>)",
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