spNNGP: Spatial Regression Models for Large Datasets using Nearest Neighbor Gaussian Processes

Fits univariate Bayesian spatial regression models for large datasets using Nearest Neighbor Gaussian Processes (NNGP) detailed in Finley, Datta, Banerjee (2022) <doi:10.18637/jss.v103.i05>, Finley, Datta, Cook, Morton, Andersen, and Banerjee (2019) <doi:10.1080/10618600.2018.1537924>, and Datta, Banerjee, Finley, and Gelfand (2016) <doi:10.1080/01621459.2015.1044091>.

Version: 1.0.0
Depends: R (≥ 3.5.0), coda, Formula, RANN
Imports: methods
Published: 2022-06-27
Author: Andrew Finley [aut, cre], Abhirup Datta [aut], Sudipto Banerjee [aut]
Maintainer: Andrew Finley <finleya at msu.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://www.finley-lab.com/
NeedsCompilation: yes
Citation: spNNGP citation info
CRAN checks: spNNGP results

Documentation:

Reference manual: spNNGP.pdf

Downloads:

Package source: spNNGP_1.0.0.tar.gz
Windows binaries: r-devel: spNNGP_1.0.0.zip, r-release: spNNGP_1.0.0.zip, r-oldrel: spNNGP_1.0.0.zip
macOS binaries: r-release (arm64): spNNGP_1.0.0.tgz, r-oldrel (arm64): spNNGP_1.0.0.tgz, r-release (x86_64): spNNGP_1.0.0.tgz, r-oldrel (x86_64): spNNGP_1.0.0.tgz
Old sources: spNNGP archive

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