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RiskMap: Geo-Statistical Modeling of Spatially Referenced Data

Provides functions for geo-statistical analysis of both continuous and count data using maximum likelihood methods. The models implemented in the package use stationary Gaussian processes with Matern correlation function to carry out spatial prediction in a geographical area of interest. The underpinning theory of the methods implemented in the package are found in Diggle and Giorgi (2019, ISBN: 978-1-138-06102-7).

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: sf, stats, methods, ggplot2, Matrix, maxLik, terra, xtable
Published: 2024-06-25
DOI: 10.32614/CRAN.package.RiskMap
Author: Emanuele Giorgi ORCID iD [aut, cre], Claudio Fronterre ORCID iD [ctb]
Maintainer: Emanuele Giorgi <e.giorgi at lancaster.ac.uk>
License: MIT + file LICENSE
URL: https://claudiofronterre.github.io/RiskMap/
NeedsCompilation: no
Materials: README
CRAN checks: RiskMap results

Documentation:

Reference manual: RiskMap.pdf

Downloads:

Package source: RiskMap_0.1.0.tar.gz
Windows binaries: r-devel: RiskMap_0.1.0.zip, r-release: RiskMap_0.1.0.zip, r-oldrel: RiskMap_0.1.0.zip
macOS binaries: r-release (arm64): RiskMap_0.1.0.tgz, r-oldrel (arm64): RiskMap_0.1.0.tgz, r-release (x86_64): RiskMap_0.1.0.tgz, r-oldrel (x86_64): RiskMap_0.1.0.tgz

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.