An extension of parametric ROC analysis for calculating diagnostic accuracy when underlying distributions are mixture of Gaussian

DOI10.1080/02664763.2010.545109OpenAlexW2143620510MaRDI QIDQ5124887

Vahid Nassiri, James A. Hanley, Karimollah Hajian-Tilaki

Publication date: 30 September 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2010.545109

zbMATH Keywords

extensionarea under the curvemixture of Gaussianbinormal modeltrue positive fractionparametric ROC analysis

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach
• Mixture Densities, Maximum Likelihood and the EM Algorithm
• A family of nonparametric statistics for comparing diagnostic markers with paired or unpaired data
• Convergence properties of a general algorithm for calculating variational Bayesian estimates for a normal mixture model
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