Package: shinybrms 1.8.0

shinybrms: Graphical User Interface ('shiny' App) for 'brms'

A graphical user interface (GUI) for fitting Bayesian regression models using the package 'brms' which in turn relies on 'Stan' (<https://mc-stan.org/>). The 'shinybrms' GUI is a 'shiny' app.

Authors:Frank Weber [aut, cre], Katja Ickstadt [ctb], Änne Glass [ctb], Thomas Park [ctb, cph], Twitter, Inc. [ctb, cph], Google, LLC [ctb, cph]

shinybrms_1.8.0.tar.gz
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shinybrms_1.8.0.tgz(r-4.4-any)shinybrms_1.8.0.tgz(r-4.3-any)
shinybrms_1.8.0.tar.gz(r-4.5-noble)shinybrms_1.8.0.tar.gz(r-4.4-noble)
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shinybrms.pdf |shinybrms.html
shinybrms/json (API)
NEWS

# Install 'shinybrms' in R:
install.packages('shinybrms', repos = c('https://fweber144.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/fweber144/shinybrms/issues

On CRAN:

bayesbayesianbayesian-data-analysisbayesian-inferencebayesian-statisticsbrmscmdstanrguimcmcrstanshinyshiny-appstanstatistical-analysisstatistical-inferencestatistical-modelsstatistics

3.70 score 10 stars 3 scripts 291 downloads 1 exports 95 dependencies

Last updated 7 months agofrom:01adb2d93f. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 02 2024
R-4.5-winNOTENov 02 2024
R-4.5-linuxNOTENov 02 2024
R-4.4-winNOTENov 02 2024
R-4.4-macNOTENov 02 2024
R-4.3-winNOTENov 02 2024
R-4.3-macNOTENov 02 2024

Exports:launch_shinybrms

Dependencies:abindbackportsbase64encbayesplotBHbridgesamplingbrmsBrobdingnagbslibcachemcallrcheckmateclicodacodetoolscolorspacecommonmarkcrayondescdigestdistributionaldplyrfansifarverfastmapfontawesomefsfuturefuture.applygenericsggplot2ggridgesglobalsgluegridExtragtablehtmltoolshttpuvinlineisobandjquerylibjsonlitelabelinglaterlatticelifecyclelistenvloomagrittrMASSMatrixmatrixStatsmemoisemgcvmimemunsellmvtnormnleqslvnlmenumDerivparallellypillarpkgbuildpkgconfigplyrposteriorprocessxpromisespsQuickJSRR6rappdirsRColorBrewerRcppRcppEigenRcppParallelreshape2rlangrstanrstantoolssassscalesshinysourcetoolsStanHeadersstringistringrtensorAtibbletidyselectutf8vctrsviridisLitewithrxtable