Discussion on Competition for Spatial Statistics for Large Datasets

Discussion on Competition for Spatial Statistics for Large Datasets
复制标题

大数据集空间统计竞争探讨

DOI:
10.1007/s13253-021-00463-1
复制
发表时间:
2021
期刊:
Journal of Agricultural, Biological and Environmental Statistics
影响因子:
--
通讯作者:
Matsuda
Matsuda
中科院分区:
--
文献类型:
--
作者:
Yasumasa;Matsuda

文献摘要

参考文献

被引文献

相似文献

东北大学的团队参加了大型数据集空间统计竞赛的子竞赛2b,其中以90万个训练点为条件构建10万个测试点的预测。我们选择了一种简化的协方差锥形方法来管理一百万个空间数据点。通过对Matérn类协方差的拟合,将扩展后的子区域的长度扩大,将其划分为等面积的子区域,在每个子区域分别构造基于训练数据的预测器。
The team of Tohoku University attended sub-competition 2b in the competition on spatial statistics for large datasets, where prediction on 100,000 testing points were to be constructed conditional on 900,000 training points. We chose a covariance tapering approach in a simplified way to manage one million spatial data points. Dividingintosub-regions with equal area, we construct predictors separately in each sub-region conditional on training data over the extended sub-region with length enlarged byby fitting Matérn class covariances.
DOI: 10.1198/016214508000000959
发表时间: 2008-12-01
影响因子: 3.7
作者:
Kaufman, Cari G.;Schervish, Mark J.;Nychka, Douglas W.
通讯作者: Nychka, Douglas W.
DOI: 10.32614/rj-2019-030
发表时间: 2019-06-01
期刊: R JOURNAL
影响因子: 2.1
作者:
Gerber, Florian;Furrer, Reinhard
通讯作者: Furrer, Reinhard