of the package see Thiele and Hirschfeld (2020) <arXiv:2002.09209>.

of the package see Thiele and Hirschfeld (2021) <doi:10.18637/jss.v098.i11>.

Title: An R package to perform LPUE standardization and stock
assessment of the English Channel cuttlefish stock using a
Author: Michael Gras and Jean-Paul Robin
Description: This package can be used to standardize abundance indices using the delta-GLM method and to model the English Channel cuttlefish stock using a two-stage biomass model

Package: cvAUC
Type: Package
Title: Cross-Validated Area Under the ROC Curve Confidence Intervals
Version: 1.0-0
Date: 2012-12-06
Author: Erin LeDell, Maya Petersen, Mark van der Laan
Maintainer: Erin LeDell <ledell@berkeley.edu>
Description: This package contains various 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
function, cvAUC, which computes cross-validated AUC, is a
wrapper for functions from the ROCR package.
License: GPL (>= 2)
Depends: ROCR
Suggests: MASS, parallel
LazyLoad: yes
Packaged: 2013-01-15 00:53:04 UTC; maru
Repository: CRAN
Date/Publication: 2013-01-15 07:39:19

Description: This package contains various 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.