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mbg: Model-Based Geostatistics

Modern model-based geostatistics for point-referenced data. This package provides a simple interface to run spatial machine learning models and geostatistical models that estimate a continuous (raster) surface from point-referenced outcomes and, optionally, a set of raster covariates. The package also includes functions to summarize raster outcomes by (polygon) region while preserving uncertainty.

Version: 1.0.0
Depends: R (≥ 4.1.0)
Imports: assertthat, caret, data.table, glue, Matrix, matrixStats, purrr, R6, sf, terra, tictoc
Suggests: INLA, knitr, rmarkdown, ggplot2, scales
Published: 2025-04-02
DOI: 10.32614/CRAN.package.mbg
Author: Nathaniel Henry ORCID iD [aut, cre], Benjamin Mayala [aut]
Maintainer: Nathaniel Henry <nat at henryspatialanalysis.com>
BugReports: https://github.com/henryspatialanalysis/mbg/issues
License: MIT + file LICENSE
URL: https://henryspatialanalysis.github.io/mbg/
NeedsCompilation: no
Additional_repositories: https://inla.r-inla-download.org/R/stable/
Materials: README
CRAN checks: mbg results

Documentation:

Reference manual: mbg.pdf
Vignettes: All model runner options (source)
Getting started with MBG (source)
Model validation and comparison (source)
Running spatial machine learning models (source)

Downloads:

Package source: mbg_1.0.0.tar.gz
Windows binaries: r-devel: mbg_1.0.0.zip, r-release: not available, r-oldrel: not available
macOS binaries: r-devel (arm64): not available, r-release (arm64): not available, r-oldrel (arm64): not available, r-devel (x86_64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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