Package: svyROC 1.1.0
svyROC: Estimation of the ROC Curve and the AUC for Complex Survey Data
Estimate the receiver operating characteristic (ROC) curve, area under the curve (AUC) and optimal cut-off points for individual classification taking into account complex sampling designs when working with complex survey data. Methods implemented in this package are described in: A. Iparragirre, I. Barrio, I. Arostegui (2024) <doi:10.1002/sta4.635>; A. Iparragirre, I. Barrio, J. Aramendi, I. Arostegui (2022) <doi:10.2436/20.8080.02.121>; A. Iparragirre, I. Barrio (2024) <doi:10.1007/978-3-031-65723-8_7>.
Authors:
svyROC_1.1.0.tar.gz
svyROC_1.1.0.zip(r-4.7)svyROC_1.1.0.zip(r-4.6)svyROC_1.1.0.zip(r-4.5)
svyROC_1.1.0.tgz(r-4.6-any)svyROC_1.1.0.tgz(r-4.5-any)
svyROC_1.1.0.tar.gz(r-4.7-any)svyROC_1.1.0.tar.gz(r-4.6-any)
svyROC_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
svyROC/json (API)
NEWS
| # Install 'svyROC' in R: |
| install.packages('svyROC', repos = c('https://aiparragirre.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/aiparragirre/svyroc/issues
- example_data_wroc - Simulated data
- example_variables_wroc - Simulated data
- example_variables_wroc_2 - Simulated data
aucauc-optimism-correctioncomplex-survey-dataoptimal-cut-off-pointsroc-curvesampling-weights
Last updated from:0a60ccf777. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 142 | ||
| source / vignettes | OK | 201 | ||
| linux-release-x86_64 | OK | 135 | ||
| macos-release-arm64 | OK | 132 | ||
| macos-oldrel-arm64 | OK | 123 | ||
| windows-devel | OK | 98 | ||
| windows-release | OK | 103 | ||
| windows-oldrel | OK | 94 | ||
| wasm-release | OK | 112 |
Exports:ci.wauccorrected.waucht.indepht.pairedwaucwocpwrocwroc.plotwsewsp
Dependencies:codetoolsDBIforeachglmnetiteratorslatticeMatrixminqamitoolsnumDerivRcppRcppArmadilloRcppEigenshapesurveysurvivalsvyVarSel
