<b>spNNGP</b> <i>R</i> Package for Nearest Neighbor Gaussian Process Models
Andrew O. Finley, Abhirup Datta, Sudipto Banerjee
Abstract
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 pointreferenced 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.
Topics & Concepts
Markov chain Monte CarloComputer scienceGaussian processGaussianR packageInferencek-nearest neighbors algorithmAlgorithmArtificial intelligenceComputational scienceBayesian probabilityPhysicsQuantum mechanicsSoil Geostatistics and MappingEconomic and Environmental ValuationSpatial and Panel Data Analysis