Package: ScottKnottESD 3.0.0

ScottKnottESD: The Non-Parametric Scott-Knott Effect Size Difference (ESD) Test

The Non-Parametric Scott-Knott Effect Size Difference (ESD) test is a mean comparison approach that leverages a hierarchical clustering to partition the set of treatment means (e.g., means of variable importance scores, means of model performance) into statistically distinct groups with non-negligible difference [Tantithamthavorn et al., (2018) <doi:10.1109/TSE.2018.2794977>].

Authors:Chakkrit Tantithamthavorn

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ScottKnottESD/json (API)

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

Bug tracker:https://github.com/klainfo/scottknottesd/issues

Datasets:
  • example - An example dataset of Breiman's variable importance scores
  • maven - An example dataset of Breiman's variable importance scores

On CRAN:

Conda:

defect-prediction-modelseffect-sizemultiple-comparisonsranking-algorithmscott-knottstatistical-tests

5.77 score 43 stars 68 scripts 261 downloads 5 exports 80 dependencies

Last updated 2 years agofrom:401664099a. Checks:1 OK, 7 WARNING. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 17 2025
R-4.5-winWARNINGFeb 17 2025
R-4.5-macWARNINGFeb 17 2025
R-4.5-linuxWARNINGFeb 17 2025
R-4.4-winWARNINGFeb 17 2025
R-4.4-macWARNINGFeb 17 2025
R-4.3-winWARNINGFeb 17 2025
R-4.3-macWARNINGFeb 17 2025

Exports:check.ANOVA.assumptionscheckDifferencelong2widenormalizesk_esd

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11curlDerivdoBydplyreffsizefansifarverforecastFormulafracdiffgenericsggplot2gluegtableisobandjsonlitelabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplyrpurrrquadprogquantmodquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasreshape2rlangscalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDatetseriesTTRurcautf8vctrsviridisLitewithrxtszoo