Package: RFpredInterval 1.0.6

RFpredInterval: Prediction Intervals with Random Forests and Boosted Forests

Implements various prediction interval methods with random forests and boosted forests. The package has two main functions: pibf() produces prediction intervals with boosted forests (PIBF) as described in Alakus et al. (2021) <arxiv:2106.08217> and rfpi() builds 15 distinct variations of prediction intervals with random forests (RFPI) proposed by Roy and Larocque (2020) <doi:10.1177/0962280219829885>.

Authors:Cansu Alakus [aut, cre], Denis Larocque [aut], Aurelie Labbe [aut], Hemant Ishwaran [ctb], Udaya B. Kogalur [ctb]

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RFpredInterval.pdf |RFpredInterval.html✨
RFpredInterval/json (API)
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Peer review:

Bug tracker:https://github.com/calakus/rfpredinterval/issues

On CRAN:

5 exports 5 stars 1.11 score 88 dependencies 3 scripts 305 downloads

Last updated 2 years agofrom:6170733a40. Checks:OK: 3 WARNING: 5 NOTE: 1. Indexed: yes.

Exports:piallpibfplot.rfpredintervalprint.rfpredintervalrfpi

Dependencies:ashbase64encbitbit64bslibcachemclicliprcolorspacecpp11crayondata.tabledata.treeDiagrammeRdigestdplyrevaluatefansifarverfastmapFNNfontawesomefsgenericsggplot2gluegtablehdrcdehighrhmshtmltoolshtmlwidgetsigraphisobandjquerylibjsonlitekernlabKernSmoothknitrkslabelinglatticelifecyclelocfitmagrittrMASSMatrixmclustmemoisemgcvmimemulticoolmunsellmvtnormnlmepillarpkgconfigpracmaprettyunitsprogresspurrrR6rangerrappdirsRColorBrewerRcppRcppEigenreadrrlangrmarkdownrstudioapisassscalesstringistringrtibbletidyrtidyselecttinytextzdbutf8vctrsviridisLitevisNetworkvroomwithrxfunyaml