CRAN/E | RBesT

RBesT

R Bayesian Evidence Synthesis Tools

Installation

About

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.

Citation RBesT citation info
opensource.nibr.com/RBesT/
System requirements GNU make, pandoc (>= 1.12.3), pngquant, C++17
Bug report File report

Key Metrics

Version 1.7-3
R ≥ 3.5.0
Published 2024-01-08 112 days ago
Needs compilation? yes
License GPL (≥ 3)
CRAN checks RBesT results

Downloads

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Last 7 days 164 -16%
Last 30 days 643 -15%
Last 90 days 2.142 -10%
Last 365 days 9.175 +6%

Maintainer

Maintainer

Sebastian Weber

sebastian.weber@novartis.com

Authors

Novartis Pharma AG

cph

Sebastian Weber

aut / cre

Beat Neuenschwander

ctb

Heinz Schmidli

ctb

Baldur Magnusson

ctb

Yue Li

ctb

Satrajit Roychoudhury

ctb

Trustees of Columbia University

cph

(R/stanmodels.R, configure, configure.win)

Material

NEWS
Reference manual
Package source

In Views

MetaAnalysis

Vignettes

Getting started with RBesT (binary)

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

RBesT archive

Depends

R ≥ 3.5.0

Imports

methods
Rcpp ≥ 0.12.0
RcppParallel ≥ 5.0.1
rstan ≥2.26.0
rstantools ≥ 2.3.1
assertthat
mvtnorm
Formula
checkmate
bayesplot ≥ 1.4.0
ggplot2
dplyr
stats
utils
matrixStats
abind
rlang

Suggests

rmarkdown
knitr
testthat ≥ 2.0.0
foreach
purrr
rstanarm ≥ 2.17.2
scales
tools
broom
tidyr
parallel
brms
glue
ragg

LinkingTo

BH ≥ 1.72.0
Rcpp ≥ 0.12.0
RcppEigen ≥ 0.3.3.3.0
RcppParallel ≥ 5.0.1
rstan ≥ 2.26.0
StanHeaders ≥2.26.0

Reverse Depends

SAMprior

Reverse Imports

BayesianMCPMod
NCC
tipmap

Reverse Suggests

DoseFinding