Comparing the estimates of ROC curves by modeling methods

We investigate parameter estimation problems using the ROC curve approach. We compare several parametric, semiparametric, and nonparametric estimates of ROC curves on the assumption that the model is binormal. Our comparison is based on the analysis of numerical examples: we use generalized least sq...

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Published in:Cybernetics and systems analysis 2010-11, Vol.46 (6), p.960-966
Main Authors: Michalek, Ja, Vesely, V.
Format: Article
Language:English
Subjects:
Artificial Intelligence
Control
Cybernetics
Estimates
Estimating techniques
Least squares method
Mathematical models
Mathematics
Mathematics and Statistics
Parameter estimation
Processor Architectures
Random variables
Software Engineering/Programming and Operating Systems
Studies
Systems analysis
Systems Theory
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Vesely, V.
description We investigate parameter estimation problems using the ROC curve approach. We compare several parametric, semiparametric, and nonparametric estimates of ROC curves on the assumption that the model is binormal. Our comparison is based on the analysis of numerical examples: we use generalized least square method for parametric estimation, functional modeling for semiparametric, and sdf for nonparametric estimation.
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subjects Artificial Intelligence
Control
Cybernetics
Estimates
Estimating techniques
Least squares method
Mathematical models
Mathematics
Mathematics and Statistics
Parameter estimation
Processor Architectures
Random variables
Software Engineering/Programming and Operating Systems
Studies
Systems analysis
Systems Theory
title Comparing the estimates of ROC curves by modeling methods
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