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SSNbayes: Bayesian Spatio-Temporal Analysis in Stream Networks

Fits Bayesian spatio-temporal models and makes predictions on stream networks using the approach by Santos-Fernandez, Edgar, et al. (2022)."Bayesian spatio-temporal models for stream networks". <doi:10.48550/arXiv.2103.03538>. In these models, spatial dependence is captured using stream distance and flow connectivity, while temporal autocorrelation is modelled using vector autoregression methods.

Version: 0.0.3
Depends: R (≥ 4.0.0)
Imports: plyr, dplyr, rstan, sf, methods, SSN2
Suggests: rmarkdown, knitr, testthat (≥ 3.0.0)
Published: 2023-12-03
DOI: 10.32614/CRAN.package.SSNbayes
Author: Edgar Santos-Fernandez [aut, cre, cph]
Maintainer: Edgar Santos-Fernandez <santosfe at qut.edu.au>
BugReports: https://github.com/EdgarSantos-Fernandez/SSNbayes/issues
License: GPL-2
URL: https://github.com/EdgarSantos-Fernandez/SSNbayes
NeedsCompilation: no
Citation: SSNbayes citation info
Materials: README NEWS
CRAN checks: SSNbayes results

Documentation:

Reference manual: SSNbayes.pdf
Vignettes: SSNbayes

Downloads:

Package source: SSNbayes_0.0.3.tar.gz
Windows binaries: r-devel: SSNbayes_0.0.3.zip, r-release: SSNbayes_0.0.3.zip, r-oldrel: SSNbayes_0.0.3.zip
macOS binaries: r-release (arm64): SSNbayes_0.0.3.tgz, r-oldrel (arm64): SSNbayes_0.0.3.tgz, r-release (x86_64): SSNbayes_0.0.3.tgz, r-oldrel (x86_64): SSNbayes_0.0.3.tgz
Old sources: SSNbayes archive

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.