基于测量证据的ROC分析
ROC Analyses Based on Measuring Evidence
摘要：
ROC分析是在关于测量值$X$在两个人群中的分布的各种假设下考虑的。这些模型包括副正态模型和非参数模型，其中对分布的形式几乎没有假设。该方法基于统计证据的表征，其取决于未知总体分布以及给定人群中疾病的相关患病率$w$的先验分布的规格。在所有情况下，启发式算法提供指导先验的选择。推导AUC以及用于分类的截止值$c$和相关误差特征的推断。
英文摘要：
ROC analyses are considered under a variety of assumptions concerning the distributions of a measurement $X$ in two populations. These include the binormal model as well as nonparametric models where little is assumed about the form of distributions. The methodology is based on a characterization of statistical evidence which is dependent on the specification of prior distributions for the unknown population distributions as well as for the relevant prevalence $w$ of the disease in a given population. In all cases, elicitation algorithms are provided to guide the selection of the priors. Inferences are derived for the AUC as well as the cutoff $c$ used for classification and the associated error characteristics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
