Package: influenceAUC
Type: Package
Title: Identify Influential Observations in Binary Classification
Version: 0.1.3
Authors@R: c( 
    person("Bo-Shiang", "Ke", email = "naivete0907@gmail.com", role = c("cre", "aut", "cph")), 
    person("Yuan-chin Ivan", "Chang", email = "ycchang@sinica.edu.tw", role = "aut"), 
    person("Wen-Ting", "Wang", email = "egpivo@gmail.com", role = "aut")
    )
Maintainer: Bo-Shiang Ke <naivete0907@gmail.com>
Description: Ke, B. S., Chiang, A. J., & Chang, Y. C. I. (2018)
        <doi:10.1080/10543406.2017.1377728> provide two theoretical
        methods (influence function and local influence) based on the
        area under the receiver operating characteristic curve (AUC) to
        quantify the numerical impact of each observation to the
        overall AUC. Alternative graphical tools, cumulative lift
        charts, are proposed to reveal the existences and approximate
        locations of those influential observations through data
        visualization.
License: GPL-3
BugReports: https://github.com/BoShiangKe/InfluenceAUC/issues
URL: https://boshiangke.github.io/InfluenceAUC/
Encoding: UTF-8
RoxygenNote: 7.1.0
Depends: R (>= 3.6)
Imports: dplyr, geigen, ggplot2, ggrepel, methods, ROCR
Repository: https://boshiangke.r-universe.dev
Date/Publication: 2026-02-07 02:17:11 UTC
RemoteUrl: https://github.com/boshiangke/influenceauc
RemoteRef: HEAD
RemoteSha: b78ace93dc4f887cf5d6afca5fa5d6e0be317286
NeedsCompilation: no
Packaged: 2026-10-05 10:39:48 UTC; root
Author: Bo-Shiang Ke [cre, aut, cph],
  Yuan-chin Ivan Chang [aut],
  Wen-Ting Wang [aut]