Nonparametric estimation of the ROC curve based on smoothed empirical distribution functions

DOI10.1007/S11222-012-9340-XzbMath1322.62122OpenAlexW1967997344MaRDI QIDQ746342

Alicja Jokiel-Rokita, Michał Pulit

Publication date: 16 October 2015

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-012-9340-x

zbMATH Keywords

empirical distribution functionnonparametric estimationreceiver operating characteristic (ROC) curve

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05)

Related Items (11)

REVIEW AND LIMITATIONS OF METHODS FOR CONSTRUCTING A RECEIVER OPERATING CHARACTERISTIC CURVE IN A CASE-CONTROL DESIGN ⋮ A new method of kernel-smoothing estimation of the ROC curve ⋮ Modelling receiver operating characteristic curves using Gaussian mixtures ⋮ A comparative study of methods for testing the equality of two or more ROC curves ⋮ Nonparametric estimation of quantile versions of the Lorenz curve ⋮ Minimum distance estimation of the Lehmann receiver operating characteristic curve ⋮ Estimation of the ROC curve from the Lehmann family ⋮ A note on estimating cumulative distribution functions by the use of convolution power kernels ⋮ Nonparametric estimation of the ROC curve based on the Bernstein polynomial ⋮ Quantile estimation via distribution fitting ⋮ Minimum distance estimation of the binormal ROC curve

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