Visualization for Large‐scale Gaussian Updates
针对地质统计学等应用中大规模高斯过程模型更新的可视化难题，提出了一种名为“奖章图”的工具，展示观测位置的不确定性变化及信息共享情况，并以南极冰盖质量趋势评估为例说明其应用。
Abstract In geostatistics and also in other applications in science and engineering, it is now common to perform updates on Gaussian process models with many thousands or even millions of components. These large‐scale inferences involve modelling, representational and computational challenges. We describe a visualization tool for large‐scale Gaussian updates, the ‘medal plot’. The medal plot shows the updated uncertainty at each observation location and also summarizes the sharing of information across observations, as a proxy for the sharing of information across the state vector (or latent process). As such, it reflects characteristics of both the observations and the statistical model. We illustrate with an application to assess mass trends in the Antarctic Ice Sheet, for which there are strong constraints from the observations and the physics.