Minimum distance estimation of the binormal ROC curve

Alicja Jokiel-Rokita () and Rafał Topolnicki
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Alicja Jokiel-Rokita: Wroclaw University of Science and Technology
Rafał Topolnicki: Wroclaw University of Science and Technology

Statistical Papers, 2019, vol. 60, issue 6, No 16, 2183 pages

Abstract: Abstract The receiver operating characteristic (ROC) curve describes the performance of a diagnostic test, which classifies individuals into one of two categories. Many parametric, semiparametric and nonparametric estimation methods have been proposed for estimating the ROC curve and its functionals. In this paper the minimum distance estimation of the binormal ROC curve is considered. A modification of the estimator considered in the paper of Davidov and Nov (J Stat Plan Inference 142(4):872–877, 2012) and some new estimators are proposed. We compare the accuracy of the new estimators with known minimum distance estimators of the binormal ROC curve and we conclude that our estimators generally perform better than their competitors.

Keywords: Receiver operating characteristic (ROC) curve; Binormal model; Semiparametric estimation; Minimum distance estimation (MDE); Bayesian bootstrap (BB) (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s00362-017-0915-7

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