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:
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')) |
- input_data - Input_data
- tree_data_example - Tree_data_example
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 months agofrom:e5c750c705. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 22 2024 |
R-4.5-linux | OK | Nov 22 2024 |
Exports:acceptRatebartClassifDiagbartDiagbartRegrDiagbivariate_rangebivariate_scaleclusterTreescombineDummyextractTreeDatagetChildrengetObservationsguide_colorfanguide_colourfanlocalProceduremdsBartnode_depthpal_vsuppermVimppermVintplotProximityplotSingleTreeplotTreesproximityMatrixRangeBivariateScaleBivariatesort_trees_by_depthMaxsplitDensityterminalFunctiontrain_bivariatetree_dataframetreeBarPlottreeDepthtreeListtreeNodesvimpBartvimpPlotvintPlotviviBartviviBartMatrixviviBartPlot
Dependencies:abindarrayhelpersbackportsBARTbartMachinebartMachineJARsbase64encbitbit64bslibcacachemcheckmateclicliprclustercodacodetoolscolorspacecowplotcpp11crayondbartsDendSerdigestdistributionaldoRNGdplyrevaluatefansifarverfastmapfontawesomeforeachfsgclusgenericsggdistggforceggiraphggnewscaleggplot2ggraphggrepelgluegraphlayoutsgridExtragtablehighrhmshtmltoolshtmlwidgetsigraphisobanditeratorsitertoolsjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmemoisemgcvmimemissForestmunsellnlmenumDerivpatchworkpermutepillarpkgconfigpolyclipposteriorprettyunitsprogresspurrrqapquadprogR6randomForestrappdirsRColorBrewerRcppRcppArmadilloRcppEigenreadrregistryrJavarlangrmarkdownrngtoolsrrapplysassscalesseriationstringistringrsurvivalsvUnitsystemfontstensorAtibbletidybayestidygraphtidyrtidyselecttidytreatmenttinytexTSPtweenrtzdbutf8uuidvctrsveganviridisviridisLitevroomwithrxfunyaml