spNNGP R package for Nearest Neighbor Gaussian Process models

Andrew O. Finley, Abhirup Datta, Sudipto Banerjee

Research output: Contribution to journalArticlepeer-review

Abstract

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 languageEnglish (US)
JournalUnknown Journal
StatePublished - Jan 24 2020

Keywords

  • Kriging
  • MCMC
  • Nearest Neighbor Gaussian Process
  • R

ASJC Scopus subject areas

  • General

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