A Resampling-Based Stochastic Approximation Method for Analysis of Large Geostatistical Data
大型地统计数据分析的重抽样随机逼近方法
The Gaussian geostatistical model has been widely used in modeling of spatial data. However, it is challenging to computationally implement this method because it requires the inversion of a large covariance matrix, particularly when there is a large number of observations. This article proposes a resampling-based stochastic approximation method to address this challenge. At each iteration of the proposed method, a small subsample is drawn from the full dataset, and then the…