Estimation of a convex ROC curve

Statistics and Probability Letters

Volumn 59, Issue 1, 2002, Pages 99-111

  Lloyd, Chris J ^a  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

Binary classification; Isotonic regression; Misclassification rates; Weighted distribution

Indexed keywords

EID: 0036722917     PISSN: 01677152     EISSN: None     Source Type: Journal    
DOI: 10.1016/s0167-7152(02)00212-2     Document Type: Article

References (21)

1. A non-parametric measure of signal discriminability
2. An empirical distribution functions for sampling with incomplete information
3. Statistical Inference Under Order Restrictions: The Theory and Application of Isotonic Regression
4. An application of Lomax distributions in receiver operating characteristic (ROC) curve analysis
5. Proper receiving operating characteristic analysis: The bigamma model
6. Receiver operating characteristic (ROC) curves and non-normal data: An empirical study
7. Generalised Additive Models
8. A goodness-of-fit test statistic for the multiple logistic regression model
9. The empirical process approach for semiparametric two-sample models with heterogeneous treatment effect
10. Non-parametric and semi-parametric estimation of the receiver operating characteristic curve
11. The use of smoothed ROC curves to summaries and compare diagnostic systems
12. Kernel estimators of the ROC curve are better than empirical
13. Maximum likelihood estimation of receiver operating characteristic (ROC) curves from continuously distributed data
14. Proper binormal ROC curves: Theory and maximum-likelihood estimation
15. A recursive algorithm for nonparametric analysis with missing data
16. The proper binormal model: Parametric receiver operating characteristic curve estimation with degenerate data
17. Implications of latency data for threshold and non-threshold models of signal detection
18. Non-parametric estimation in the presence of length bias
19. The use of deviance to test the goodness of fit of a logistic linear model to binary data