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.
翻译:本文描述和说明SPNNGP R 包件的功能。 包件为Gaussian 和非Gausian 点参照结果提供了一套空间索引的空间回归模型。 包件执行了若干Markov链Monte Carlo(MCMC )和MC-MMC无近邻Gaussian进程(NNGP)模型,用以推断大型空间数据。 非Gausian 结果使用NNGP Polya- Gamma 潜伏变量进行模型模型模型。 提供了 OpenMP 平行选项,以利用多处理器系统。 包件功能用模拟和真实数据集演示。