论文标题
由空间数据引起的高维高斯累积分布函数的vecchia近似
A Vecchia Approximation for High-Dimensional Gaussian Cumulative Distribution Functions Arising from Spatial Data
论文作者
论文摘要
我们引入了一种方法，以快速，准确地近似于空间高斯过程引起的多元高斯分布的累积分布函数。这种近似在使用标准软件上可以平行，易于实现。我们在一系列仿真实验中证明了它的准确性和计算效率，并将其应用于使用最近提供的空间极端尺度混合模型来分析大沉淀数据集的关节尾部。该数据集比以前认为使用首选推论技术合适的数据集大。
We introduce an approach to quickly and accurately approximate the cumulative distribution function of multivariate Gaussian distributions arising from spatial Gaussian processes. This approximation is trivially parallelizable and simple to implement using standard software. We demonstrate its accuracy and computational efficiency in a series of simulation experiments and apply it to analyzing the joint tail of a large precipitation dataset using a recently-proposed scale mixture model for spatial extremes. This dataset is many times larger than what was previously considered possible to fit using preferred inferential techniques.
