Spatial Statistical Modeling and Prediction R package spmodel version 0.13.0 CRAN Task View: MixedModels (https://CRAN.R-project.org/view=MixedModels) CRAN Task View: Spatial (https://CRAN.R-project.org/view=Spatial) 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>. Software Depends: R (>= 3.5.0) Imports: graphics, generics, Matrix, sf, stats, tibble, parallel Suggests: rmarkdown, knitr, testthat (>= 3.0.0), ggplot2, ranger, statmod, pROC, emmeans (>= 1.4), estimability Michael Dumelle <Dumelle.Michael@epa.gov> Comprehensive R Archive Network (CRAN) Michael Dumelle [aut, cre] (ORCID: <https://orcid.org/0000-0002-3393-5529>), Matt Higham [aut] (ORCID: <https://orcid.org/0009-0006-4217-625X>), Ryan A. Hill [ctb] (ORCID: <https://orcid.org/0000-0001-9583-0426>), Michael Mahon [ctb] (ORCID: <https://orcid.org/0000-0002-9436-2998>), Jay M. Ver Hoef [aut] (ORCID: <https://orcid.org/0000-0003-4302-6895>) GPL-3 2026-06-10 application/tgz https://CRAN.R-project.org/package=spmodel doi:10.32614/CRAN.package.spmodel