spNNGP R package for Nearest Neighbor Gaussian Process models
Computation
2021-04-16 v2
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 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.
Cite
@article{arxiv.2001.09111,
title = {spNNGP R package for Nearest Neighbor Gaussian Process models},
author = {Andrew O. Finley and Abhirup Datta and Sudipto Banerjee},
journal= {arXiv preprint arXiv:2001.09111},
year = {2021}
}