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-4.5)cvAUC_1.1.4.zip(r-4.4)cvAUC_1.1.4.zip(r-4.3)
cvAUC_1.1.4.tgz(r-4.4-any)cvAUC_1.1.4.tgz(r-4.3-any)
cvAUC_1.1.4.tar.gz(r-4.5-noble)cvAUC_1.1.4.tar.gz(r-4.4-noble)
cvAUC_1.1.4.tgz(r-4.4-emscripten)cvAUC_1.1.4.tgz(r-4.3-emscripten)
cvAUC.pdf |cvAUC.html
cvAUC/json (API)
NEWS

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

Peer review:

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:

aucconfidence-intervalscross-validationmachine-learningstatisticsvariance

9.11 score 23 stars 40 packages 319 scripts 3.0k downloads 20 mentions 4 exports 7 dependencies

Last updated 3 years agofrom:4c7feae3a4. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 12 2024
R-4.5-winOKOct 12 2024
R-4.5-linuxOKOct 12 2024
R-4.4-winOKOct 12 2024
R-4.4-macOKOct 12 2024
R-4.3-winOKOct 12 2024
R-4.3-macOKOct 12 2024

Exports:AUCci.cvAUCci.pooled.cvAUCcvAUC

Dependencies:bitopscaToolsdata.tablegplotsgtoolsKernSmoothROCR