_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-rbest 1.8-1
Dependencies: pngquant@2.12.6 pandoc@2.19.2
Propagated dependencies: r-stanheaders@2.32.10 r-rstantools@2.4.0 r-rstan@2.32.6 r-rlang@1.1.4 r-rcppparallel@5.1.9 r-rcppeigen@0.3.4.0.2 r-rcpp@1.0.13-1 r-mvtnorm@1.3-2 r-matrixstats@1.4.1 r-ggplot2@3.5.1 r-formula@1.2-5 r-dplyr@1.1.4 r-checkmate@2.3.2 r-bh@1.84.0-0 r-bayesplot@1.11.1 r-assertthat@0.2.1 r-abind@1.4-8
Channel: guix-cran
Location: guix-cran/packages/r.scm (guix-cran packages r)
Home page: https://opensource.nibr.com/RBesT/
Licenses: GPL 3+
Synopsis: R Bayesian Evidence Synthesis Tools
Description:

Tool-set to support Bayesian evidence synthesis. This includes meta-analysis, (robust) prior derivation from historical data, operating characteristics and analysis (1 and 2 sample cases). Please refer to Weber et al. (2021) <doi:10.18637/jss.v100.i19> for details on applying this package while Neuenschwander et al. (2010) <doi:10.1177/1740774509356002> and Schmidli et al. (2014) <doi:10.1111/biom.12242> explain details on the methodology.

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