Package: ROCket 1.0.1.9000

ROCket: Simple and Fast ROC Curves

A set of functions for receiver operating characteristic (ROC) curve estimation and area under the curve (AUC) calculation. All functions are designed to work with aggregated data; nevertheless, they can also handle raw samples. In 'ROCket', we distinguish two types of ROC curve representations: 1) parametric curves - the true positive rate (TPR) and the false positive rate (FPR) are functions of a parameter (the score), 2) functions - TPR is a function of FPR. There are several ROC curve estimation methods available. An introduction to the mathematical background of the implemented methods (and much more) can be found in de Zea Bermudez, Gonçalves, Oliveira & Subtil (2014) <https://www.ine.pt/revstat/pdf/rs140101.pdf> and Cai & Pepe (2004) <doi:10.1111/j.0006-341X.2004.00200.x>.

Authors:Daniel Lazar [aut, cre]

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ROCket.pdf |ROCket.html✨
ROCket/json (API)

Peer review:

Bug tracker:https://github.com/da-zar/rocket/issues

On CRAN:

7 exports 1 stars 0.62 score 1 dependencies 6 scripts 169 downloads

Last updated 4 years agofrom:3f53a32379. Checks:OK: 5 NOTE: 2. Indexed: yes.

Exports:aucmwu.testrkt_ecdfrkt_preprkt_rocshow_methodsvariance

Dependencies:data.table