Nonparametric and semiparametric optimal transformations of markers

DOI10.1016/j.jmva.2011.06.014zbMath1231.62051OpenAlexW1997780071MaRDI QIDQ642230

Chih-Heng Chiu, Chin-Tsang Chiang

Publication date: 25 October 2011

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2011.06.014

zbMATH Keywords

\(U\)-statisticsreceiver operating characteristic curvesingle-index modelnonparametric estimatorarea under curveoptimal marker

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Monte Carlo methods (65C05)

Related Items (1)

Estimating robot strengths with application to selection of alliance members in FIRST robotics competitions

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Large and moderate deviations principles for kernel estimators of the multivariate regression
• Some asymptotic theory for the bootstrap
• Bootstrap methods: another look at the jackknife
• Semiparametric least squares (SLS) and weighted SLS estimation of single-index models
• Optimal smoothing in single-index models
• Combining Several Screening Tests: Optimality of the Risk Score
• Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach
• Some uniform large deviation results in nonparametric function estimation
• A modified sign test for comparing paired ROC curves
• Model checking in regression via dimension reduction
• Fitting regression models to case-control data by maximum likelihood
• A distribution-free procedure for comparing receiver operating characteristic curves for a paired experiment
• Dimension Reduction in Binary Response Regression
• Time‐Dependent ROC Curves for Censored Survival Data and a Diagnostic Marker
• A Permutation Test to Compare Receiver Operating Characteristic Curves
• An Efficient Semiparametric Estimator for Binary Response Models
• Combining Multiple Markers for Classification Using ROC
• Combining Predictors for Classification Using the Area under the Receiver Operating Characteristic Curve
• Kernel Estimators for Univariate Binary Regression
• Empirical Likelihood Inference for the Area under the ROC Curve
• A Class of Statistics with Asymptotically Normal Distribution

This page was built for publication: Nonparametric and semiparametric optimal transformations of markers