A new method of kernel-smoothing estimation of the ROC curve

DOI10.1007/S00184-015-0569-1zbMath1342.62050OpenAlexW2212505474WikidataQ59472160 ScholiaQ59472160MaRDI QIDQ300525

Michał Pulit

Publication date: 28 June 2016

Published in: Metrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00184-015-0569-1

zbMATH Keywords

kernel smoothingbandwidth selectionROC curvenonparametric estimation

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Related Items (3)

Estimators for ROC curves with missing biomarkers values and informative covariates ⋮ Empirical likelihood of quantile difference with missing response when high-dimensional covariates are present ⋮ Nonparametric estimation of the ROC curve based on the Bernstein polynomial

Cites Work

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• Kernel estimators of the ROC curve are better than empirical.
• Smoothing parameter selection for smooth distribution functions
• Measuring the Accuracy of Diagnostic Systems
• Asymptotic Expansion for Inverse Moments of Binomial and Poisson Distributions
• ROC Curves for Continuous Data
• Bandwith selection for the smoothing of distribution functions
• Multistage plug—in bandwidth selection for kernel distribution function estimates

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