Confidence intervals are an established means of portraying uncertainty about an inferred parameter and can be generated through the use of confidence distributions. For a confidence distribution to be ideal, it must maintain frequentist coverage of the true parameter. This can be represented for a precise distribution by adherence to a cumulative unit uniform distribution, referred to here as a Singh plot. This manuscript extends this to imprecise confidence structures with bounds around the uniform distribution, and describes how deviations convey information regarding the characteristics of confidence structures designed for inference and prediction. This quick visual representation, in a manner similar to ROC curves, aids the development of robust structures and methods that make use of confidence. A demonstration of the utility of Singh plots is provided with an assessment of the coverage of the ProUCL Chebyshev upper confidence limit estimator for the mean of an unknown distribution.

翻译：信任间隔是描述推断参数不确定性的固定手段,可以通过使用信任分布产生。为了理想地进行信任分布,必须保持真实参数的常住性覆盖。这可以通过坚持累计单位统一分布(此处称为Singh的图案)来表示准确分布。这一手稿将它扩展至不精确的、有统一分布界限的信任结构,并描述偏离如何传递关于为推断和预测而设计的信任结构特征的信息。这种快速直观表达方式与ROC曲线类似,有助于发展稳健的结构和利用信任的方法。Singh地块的效用表现是对ProUCL Chebyshev最高信任限值值的覆盖范围进行评估,以说明不明分布的平均值。