Fit, summarize, and predict for a variety of spatial statistical models. Parameters are estimated using various methods. Additional modeling features include anisotropy, 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.
Version: | 0.1.0 |
Depends: | R (≥ 3.5.0) |
Imports: | graphics, generics, Matrix, sf, stats, tibble, parallel |
Suggests: | rmarkdown, knitr, testthat (≥ 3.0.0), ggplot2 |
Published: | 2022-08-12 |
Author: | Michael Dumelle |
Maintainer: | Michael Dumelle <Dumelle.Michael at epa.gov> |
License: | GPL-3 |
NeedsCompilation: | no |
Citation: | spmodel citation info |
Materials: | README NEWS |
CRAN checks: | spmodel results |
Reference manual: | spmodel.pdf |
Vignettes: |
An Overview of Basic Features in spmodel A Detailed Guide to spmodel Technical Details |
Package source: | spmodel_0.1.0.tar.gz |
Windows binaries: | r-devel: spmodel_0.1.0.zip, r-release: spmodel_0.1.0.zip, r-oldrel: spmodel_0.1.0.zip |
macOS binaries: | r-release (arm64): spmodel_0.1.0.tgz, r-oldrel (arm64): spmodel_0.1.0.tgz, r-release (x86_64): spmodel_0.1.0.tgz, r-oldrel (x86_64): spmodel_0.1.0.tgz |
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