R package pROC: display and analyze ROC curves. Tools for visualizing, smoothing and comparing receiver operating characteristic (ROC curves). (Partial) area under the curve (AUC) can be compared with statistical tests based on U-statistics or bootstrap. Confidence intervals can be computed for (p)AUC or ROC curves.

References in zbMATH (referenced in 28 articles )

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  1. Christian Thiele; Gerrit Hirschfeld: cutpointr: Improved Estimation and Validation of Optimal Cutpoints in R (2021) not zbMATH
  2. Vishwakarma, Gajendra K.; Thomas, Abin; Bhattacharjee, Atanu: A weight function method for selection of proteins to predict an outcome using protein expression data (2021)
  3. Wollschläger, Daniel: R compact. The fast introduction into data analysis (2021)
  4. Díaz-Coto, Susana; Martínez-Camblor, Pablo; Pérez-Fernández, Sonia: SmoothROCtime: an (\mathsfR) package for time-dependent ROC curve estimation (2020)
  5. Gero Szepannek: An Overview on the Landscape of R Packages for Credit Scoring (2020) arXiv
  6. Jokiel-Rokita, Alicja; Topolnicki, Rafał: Estimation of the ROC curve from the Lehmann family (2020)
  7. Kandanaarachchi, Sevvandi; Muñoz, Mario A.; Hyndman, Rob J.; Smith-Miles, Kate: On normalization and algorithm selection for unsupervised outlier detection (2020)
  8. Maria Xose Rodriguez-Alvarez, Vanda Inacio: ROCnReg: An R Package for Receiver Operating Characteristic Curve Inference with and without Covariate Information (2020) arXiv
  9. Muschelli, John III: ROC and AUC with a binary predictor: a potentially misleading metric (2020)
  10. Julien Chiquet, Pierre Barbillon, Timothée Tabouy: missSBM: An R Package for Handling Missing Values in the Stochastic Block Model (2019) arXiv
  11. Wang, Wan-Lun: Mixture of multivariate (t) nonlinear mixed models for multiple longitudinal data with heterogeneity and missing values (2019)
  12. Fanjul-Hevia, Arís; González-Manteiga, Wenceslao: A comparative study of methods for testing the equality of two or more ROC curves (2018)
  13. Lombarte, Mercedes; Lupo, Maela; Fina Brenda, L.; Campetelli, German; Buzalaf Marilia, A. R.; Basualdo, Marta; Rigalli, Alfredo: \textitInvivo measurement of the rate constant of liver handling of glucose and glucose uptake by insulin-dependent tissues, using a mathematical model for glucose homeostasis in diabetic rats (2018)
  14. Vivo, Juana-María; Franco, Manuel; Vicari, Donatella: Rethinking an ROC partial area index for evaluating the classification performance at a high specificity range (2018)
  15. Krautenbacher, Norbert; Theis, Fabian J.; Fuchs, Christiane: Correcting classifiers for sample selection bias in two-phase case-control studies (2017)
  16. Matthew Dixon, Diego Klabjan, Lan Wei: OSTSC: Over Sampling for Time Series Classification in R (2017) arXiv
  17. Michael C. Sachs: plotROC: A Tool for Plotting ROC Curves (2017) not zbMATH
  18. Sara Perez-Jaume; Konstantina Skaltsa; Natàlia Pallarès; Josep Carrasco: ThresholdROC: Optimum Threshold Estimation Tools for Continuous Diagnostic Tests in R (2017) not zbMATH
  19. Unal, Ilker: Defining an optimal cut-point value in ROC analysis: an alternative approach (2017)
  20. Waldemar W. Koczkodaj, Alicja Wolny-Dominiak: RatingScaleReduction package: stepwise rating scale item reduction without predictability loss (2017) arXiv

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