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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>.

Versions across snapshots

VersionRepositoryFileSize
1.1.0 rolling linux/jammy R-4.5 svyROC_1.1.0.tar.gz 415.5 KiB
1.1.0 rolling linux/noble R-4.5 svyROC_1.1.0.tar.gz 415.4 KiB
1.1.0 rolling source/ R- svyROC_1.1.0.tar.gz 323.3 KiB
1.1.0 latest linux/jammy R-4.5 svyROC_1.1.0.tar.gz 415.5 KiB
1.1.0 latest linux/noble R-4.5 svyROC_1.1.0.tar.gz 415.4 KiB
1.1.0 latest source/ R- svyROC_1.1.0.tar.gz 323.3 KiB
1.1.0 2026-04-26 source/ R- svyROC_1.1.0.tar.gz 323.3 KiB
1.1.0 2026-04-23 source/ R- svyROC_1.1.0.tar.gz 323.3 KiB
1.0.0 2026-04-09 windows/windows R-4.5 svyROC_1.0.0.zip 214.5 KiB
1.0.0 2025-04-20 source/ R- svyROC_1.0.0.tar.gz 149.0 KiB

Dependencies (latest)

Imports