spmodel: Spatial Statistical Modeling and Prediction

Fit, summarize, and predict for a variety of spatial statistical models applied to point-referenced and areal (lattice) data. Parameters are estimated using various methods. Additional modeling features include anisotropy, non-spatial random effects, partition factors, big data approaches, and more. Model-fit statistics are used to summarize, visualize, and compare models. Predictions at unobserved locations are readily obtainable. For additional details, see Dumelle et al. (2023) <doi:10.1371/journal.pone.0282524>.

Version:	0.6.0
Depends:	R (≥ 3.5.0)
Imports:	graphics, generics, Matrix, sf, stats, tibble, parallel
Suggests:	rmarkdown, knitr, testthat (≥ 3.0.0), ggplot2, ranger, statmod
Published:	2024-04-16
Author:	Michael Dumelle [aut, cre], Matt Higham [aut], Jay M. Ver Hoef [aut]
Maintainer:	Michael Dumelle <Dumelle.Michael at epa.gov>
BugReports:	https://github.com/USEPA/spmodel/issues
License:	GPL-3
URL:	https://usepa.github.io/spmodel/
NeedsCompilation:	no
Citation:	spmodel citation info
Materials:	README NEWS
In views:	Spatial
CRAN checks:	spmodel results

Documentation:

Reference manual:	spmodel.pdf
Vignettes:	An Introduction to spmodel

Downloads:

Package source:	spmodel_0.6.0.tar.gz
Windows binaries:	r-devel: spmodel_0.6.0.zip, r-release: spmodel_0.6.0.zip, r-oldrel: spmodel_0.6.0.zip
macOS binaries:	r-release (arm64): spmodel_0.6.0.tgz, r-oldrel (arm64): spmodel_0.6.0.tgz, r-release (x86_64): spmodel_0.6.0.tgz, r-oldrel (x86_64): spmodel_0.6.0.tgz
Old sources:	spmodel archive

Reverse dependencies:

Reverse imports:

SSN2

Linking:

Please use the canonical form https://CRAN.R-project.org/package=spmodel to link to this page.