This paper describes and illustrates functionality of the spNNGP R (R Core Team 2018) 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 Pólya-Gamma latent variable. OpenMP parallelization options are provided to take advantage of multiprocessor systems. Package features are illustrated using simulated and real data sets.
|Original language||English (US)|
|State||Published - Jan 24 2020|
- Nearest Neighbor Gaussian Process
ASJC Scopus subject areas