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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>.
Getting started
Browse package contents
Package details |
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| Author | Michael Dumelle [aut, cre] (<https://orcid.org/0000-0002-3393-5529>), Matt Higham [aut] (<https://orcid.org/0009-0006-4217-625X>), Ryan A. Hill [ctb] (<https://orcid.org/0000-0001-9583-0426>), Michael Mahon [ctb] (<https://orcid.org/0000-0002-9436-2998>), Jay M. Ver Hoef [aut] (<https://orcid.org/0000-0003-4302-6895>) |
| Maintainer | Michael Dumelle <Dumelle.Michael@epa.gov> |
| License | GPL-3 |
| Version | 0.10.0 |
| URL | https://usepa.github.io/spmodel/ |
| Package repository | View on CRAN |
| Installation |
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