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>.
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aucauc-optimism-correctioncomplex-survey-dataoptimal-cut-off-pointsroc-curvesampling-weights
3.30 score 2 stars 1 scripts 632 downloadssvyVarSel - Variable Selection for Complex Survey Data
Fit design-based linear and logistic elastic nets with complex survey data considering the sampling design when defining training and test sets using replicate weights. Methods implemented in this package are described in: A. Iparragirre, T. Lumley, I. Barrio, I. Arostegui (2024) <doi:10.1002/sta4.578>.
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complex-survey-dataelastic-netslassoreplicate-weightsvariable-selection
3.18 score 1 stars 1 dependents 2 scripts 226 downloads