Functional Ordinary Kriging is the most widely used method to predict a curve at a given spatial point. However, uncertainty remains an open issue. In this article a distribution-free prediction method based on two different modulation functions and two conformity scores is proposed. Through simulations and benchmark data analyses, we demonstrate the advantages of our approach when compared to standard methods.

翻译：函数普通克里金法是在给定空间点预测曲线时最广泛使用的方法。然而，其不确定性仍是一个悬而未决的问题。本文提出了一种基于两种不同调制函数和两种适应性评分的无分布预测方法。通过模拟和基准数据分析，我们证明了该方法相较于标准方法的优势。