Package: bartMan 0.1.1

Alan Inglis

bartMan: Create Visualisations for BART Models

Investigating and visualising Bayesian Additive Regression Tree (BART) (Chipman, H. A., George, E. I., & McCulloch, R. E. 2010) <doi:10.1214/09-AOAS285> model fits. We construct conventional plots to analyze a model’s performance and stability as well as create new tree-based plots to analyze variable importance, interaction, and tree structure. We employ Value Suppressing Uncertainty Palettes (VSUP) to construct heatmaps that display variable importance and interactions jointly using colour scale to represent posterior uncertainty. Our visualisations are designed to work with the most popular BART R packages available, namely 'BART' Rodney Sparapani and Charles Spanbauer and Robert McCulloch 2021 <doi:10.18637/jss.v097.i01>, 'dbarts' (Vincent Dorie 2023) <https://CRAN.R-project.org/package=dbarts>, and 'bartMachine' (Adam Kapelner and Justin Bleich 2016) <doi:10.18637/jss.v070.i04>.

Authors:Alan Inglis [aut, cre], Andrew Parnell [aut], Catherine Hurley [aut], Claus Wilke [ctb]

bartMan_0.1.1.tar.gz
bartMan_0.1.1.tar.gz(r-4.5-noble)bartMan_0.1.1.tar.gz(r-4.4-noble)
bartMan_0.1.1.tgz(r-4.4-emscripten)bartMan_0.1.1.tgz(r-4.3-emscripten)
bartMan.pdf |bartMan.html✨
bartMan/json (API)

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

Peer review:

Uses libs:
  • openjdk– OpenJDK Java runtime, using Hotspot JIT
Datasets:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.20 score 16 scripts 287 downloads 40 exports 127 dependencies

Last updated 4 months agofrom:e5c750c705. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-linuxOKNov 22 2024

Exports:acceptRatebartClassifDiagbartDiagbartRegrDiagbivariate_rangebivariate_scaleclusterTreescombineDummyextractTreeDatagetChildrengetObservationsguide_colorfanguide_colourfanlocalProceduremdsBartnode_depthpal_vsuppermVimppermVintplotProximityplotSingleTreeplotTreesproximityMatrixRangeBivariateScaleBivariatesort_trees_by_depthMaxsplitDensityterminalFunctiontrain_bivariatetree_dataframetreeBarPlottreeDepthtreeListtreeNodesvimpBartvimpPlotvintPlotviviBartviviBartMatrixviviBartPlot

Dependencies:abindarrayhelpersbackportsBARTbartMachinebartMachineJARsbase64encbitbit64bslibcacachemcheckmateclicliprclustercodacodetoolscolorspacecowplotcpp11crayondbartsDendSerdigestdistributionaldoRNGdplyrevaluatefansifarverfastmapfontawesomeforeachfsgclusgenericsggdistggforceggiraphggnewscaleggplot2ggraphggrepelgluegraphlayoutsgridExtragtablehighrhmshtmltoolshtmlwidgetsigraphisobanditeratorsitertoolsjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmemoisemgcvmimemissForestmunsellnlmenumDerivpatchworkpermutepillarpkgconfigpolyclipposteriorprettyunitsprogresspurrrqapquadprogR6randomForestrappdirsRColorBrewerRcppRcppArmadilloRcppEigenreadrregistryrJavarlangrmarkdownrngtoolsrrapplysassscalesseriationstringistringrsurvivalsvUnitsystemfontstensorAtibbletidybayestidygraphtidyrtidyselecttidytreatmenttinytexTSPtweenrtzdbutf8uuidvctrsveganviridisviridisLitevroomwithrxfunyaml