spNNGP R Package for Nearest Neighbor Gaussian Process Models
spNNGP R Package for Nearest Neighbor Gaussian Process Models
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DOI：
10.18637/jss.v103.i05
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发表时间：
2022-07-01
影响因子：
5.8
通讯作者：
Banerjee, Sudipto
中科院分区：
文献类型：
--
作者：
Finley, Andrew O.;Datta, Abhirup;Banerjee, Sudipto
本文描述并说明了 spNNGP R 包的功能。该软件包提供了一套空间回归模型，用于空间索引的高斯和非高斯点参考结果。该包实现了多个马尔可夫链蒙特卡罗 (MCMC) 和无 MCMC 最近邻高斯过程 (NNGP) 模型，用于推理大型空间数据。非高斯结果使用 NNGP Polya-Gamma 潜变量进行建模。提供 OpenMP 并行化选项以利用多处理器系统。使用模拟和真实数据集说明封装特性。
This paper describes and illustrates functionality of the spNNGP R package. The package provides a suite of spatial regression models for Gaussian and non-Gaussian point-referenced outcomes that are spatially indexed. The package implements several Markov chain Monte Carlo (MCMC) and MCMC-free nearest neighbor Gaussian process (NNGP) models for inference about large spatial data. Non-Gaussian outcomes are modeled using a NNGP Polya-Gamma latent variable. OpenMP parallelization options are provided to take advantage of multiprocessor systems. Package features are illustrated using simulated and real data sets.