Rank-based kernel estimation of the area under the ROC curve
From MaRDI portal
Publication:670129
DOI10.1016/j.stamet.2016.04.001zbMath1487.62141OpenAlexW2343725866MaRDI QIDQ670129
Jingjing Yin, Yi Hao, Hani M. Samawi, Haresh D. Rochani
Publication date: 18 March 2019
Published in: Statistical Methodology (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.stamet.2016.04.001
Density estimation (62G07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Sampling theory, sample surveys (62D05) Order statistics; empirical distribution functions (62G30)
Related Items (3)
Smooth estimation of a reliability function in ranked set sampling ⋮ Interval estimation of \(P(X<Y)\) in ranked set sampling ⋮ Symmetric smoothed bootstrap methods for ranked set samples
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The \(L_1\) convergence of kernel density estimates
- The area above the ordinal dominance graph and the area below the receiver operating characteristic graph
- Ranked set sampling. Theory and applications
- Ranked set sampling: its relevance and impact on statistical inference
- Kernel estimators of the ROC curve are better than empirical.
- Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach
- Ranked Set Sampling Theory with Order Statistics Background
- Characterization of a Ranked-Set Sample with Application to Estimating Distribution Functions
- Estimation of Variance Using Judgment Ordered Ranked Set Samples
- The Effect of Imperfect Judgment Rankings on Properties of Procedures Based on the Ranked-Set Samples Analog of the Mann-Whitney-Wilcoxon Statistic
- Estimation of Ratio Using Rank Set Sampling
- Estimating the Population Mean Using Extreme Ranked Set Sampling
- Estimation of the Youden Index and its Associated Cutoff Point
- Modern Applied U‐Statistics
- A Class of Statistics with Asymptotically Normal Distribution
This page was built for publication: Rank-based kernel estimation of the area under the ROC curve