论文标题
逆设置估计和同时置信区间的反转
Inverse set estimation and inversion of simultaneous confidence intervals
论文作者
论文摘要
由气候学评估问题（北美温度变化）和医学（他汀类药物使用的影响和Covid-19对住院患者的影响）的动机，我们解决了估计图像等于预定义子集的功能域中集合的问题。构建置信集的现有方法需要严格的假设。我们通过证明可以通过倒置的同时置信频段可以同时构建多个级别的置信度，从而通过证明多个级别的置信度可以同时构建多个级别的置信度，从而将这种集合的估计概括为密集和非密集的域，并保护“数据窥视”。提供了非参数引导算法和代码。
Motivated by the questions of risk assessment in climatology (temperature change in North America) and medicine (impact of statin usage and COVID-19 on hospitalized patients), we address the problem of estimating the set in the domain of a function whose image equals a predefined subset. Existing methods that construct confidence sets require strict assumptions. We generalize the estimation of such sets to dense and non-dense domains with protection against "data peeking" by proving that confidence sets of multiple levels can be simultaneously constructed with the desired confidence non-asymptotically through inverting simultaneous confidence bands. A non-parametric bootstrap algorithm and code are provided.
