Package: cvAUC 1.1.4

cvAUC: Cross-Validated Area Under the ROC Curve Confidence Intervals

Tools for working with and evaluating cross-validated area under the ROC curve (AUC) estimators. The primary functions of the package are ci.cvAUC and ci.pooled.cvAUC, which report cross-validated AUC and compute confidence intervals for cross-validated AUC estimates based on influence curves for i.i.d. and pooled repeated measures data, respectively. One benefit to using influence curve based confidence intervals is that they require much less computation time than bootstrapping methods. The utility functions, AUC and cvAUC, are simple wrappers for functions from the ROCR package.

Authors:Erin LeDell, Maya Petersen, Mark van der Laan

cvAUC_1.1.4.tar.gz
cvAUC_1.1.4.zip(r-4.7-any)cvAUC_1.1.4.zip(r-4.6-any)cvAUC_1.1.4.zip(r-4.5-any)
cvAUC_1.1.4.tgz(r-4.6-any)cvAUC_1.1.4.tgz(r-4.5-any)
cvAUC_1.1.4.tar.gz(r-4.7-any)cvAUC_1.1.4.tar.gz(r-4.6-any)
cvAUC_1.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
cvAUC/json (API)

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

Bug tracker:https://github.com/ledell/cvauc/issues

Datasets:
  • adherence - Data set: Simulated Pooled Repeated Measures Data
  • admissions - Data set: Simulated Admissions Data with Binary Outcome

On CRAN:

Conda:

aucconfidence-intervalscross-validationmachine-learningstatisticsvariance

10.10 score 25 stars 48 packages 317 scripts 22k downloads 20 mentions 4 exports 7 dependencies

Last updated from:4c7feae3a4. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK107
source / vignettesOK172
linux-releaseOK100
macos-releaseOK104
macos-oldrelOK82
windows-develOK73
windows-releaseOK79
windows-oldrelOK60
wasm-releaseOK80

Exports:AUCci.cvAUCci.pooled.cvAUCcvAUC

Dependencies:bitopscaToolsdata.tablegplotsgtoolsKernSmoothROCR