基于九分量混合高斯Copula模型的诊断检验

International journal of statistics and probability Pub Date : 2021-05-16 DOI:10.5539/IJSP.V10N4P1

A. Nanthakumar

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引用次数: 0

摘要

本文研究了一个包含马尔可夫链的混合高斯Copula诊断测试的性能。假设在传染病的情况下，有三种状态;易感(S)，感染(I)或恢复(R)。我们将这种方法的性能与通常用于诊断研究的ROC(受试者工作特征)曲线进行比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Diagnostic Test Based on a 9-Component Mixture Gaussian Copula Model

Here in this paper, we investigate the performance of a diagnostic test based on a mixture Gaussian Copula which incorporates a Markov Chain. Suppose that in the context of an infectious disease, there are three states; Susceptible (S), Infected (I), or Recovered (R). We compare the performance of this approach with the ROC (Receiver Operating Characteristic) Curve which is usually used in diagnostic studies.

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International journal of statistics and probability

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