@article{JSSv103i05, title={spNNGP R Package for Nearest Neighbor Gaussian Process Models}, volume={103}, url={https://www.jstatsoft.org/index.php/jss/article/view/v103i05}, doi={10.18637/jss.v103.i05}, abstract={<p>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.</p>}, number={5}, journal={Journal of Statistical Software}, author={Finley, Andrew O. and Datta, Abhirup and Banerjee, Sudipto}, year={2022}, pages={1–40} }