A decision-theoretic parametric ROC framework under scale mixtures of skew-normal distributions defines optimal cutoffs by minimizing weighted misclassification risk, establishes their existence and uniqueness under monotone likelihood ratio, and supplies asymptotic normality with a plug-in variance
and Alf, Edward , title =
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Parametric ROC Analysis and Optimal Cutoff Selection under Scale Mixtures of Skew-Normal Distributions: A Decision-Theoretic Framework with Asymptotic Inference
A decision-theoretic parametric ROC framework under scale mixtures of skew-normal distributions defines optimal cutoffs by minimizing weighted misclassification risk, establishes their existence and uniqueness under monotone likelihood ratio, and supplies asymptotic normality with a plug-in variance