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spTimer: Spatio-Temporal Bayesian Modelling

Fits, spatially predicts and temporally forecasts large amounts of space-time data using [1] Bayesian Gaussian Process (GP) Models, [2] Bayesian Auto-Regressive (AR) Models, and [3] Bayesian Gaussian Predictive Processes (GPP) based AR Models for spatio-temporal big-n problems. Bakar and Sahu (2015) <doi:10.18637/jss.v063.i15>.

Version: 3.3.3
Depends: R (≥ 4.4.0)
Imports: coda, sp, spacetime, extraDistr, grDevices, graphics, stats, utils
Published: 2024-09-08
DOI: 10.32614/CRAN.package.spTimer
Author: K. Shuvo Bakar ORCID iD [aut, cre], Sujit K. Sahu ORCID iD [ctb]
Maintainer: K. Shuvo Bakar <shuvo.bakar at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: spTimer citation info
Materials: ChangeLog
In views: Bayesian, Spatial, SpatioTemporal, TimeSeries
CRAN checks: spTimer results

Documentation:

Reference manual: spTimer.pdf

Downloads:

Package source: spTimer_3.3.3.tar.gz
Windows binaries: r-devel: spTimer_3.3.3.zip, r-release: spTimer_3.3.3.zip, r-oldrel: spTimer_3.3.2.zip
macOS binaries: r-release (arm64): spTimer_3.3.3.tgz, r-oldrel (arm64): spTimer_3.3.2.tgz, r-release (x86_64): spTimer_3.3.3.tgz, r-oldrel (x86_64): spTimer_3.3.2.tgz
Old sources: spTimer archive

Reverse dependencies:

Reverse depends: spTDyn
Reverse imports: bmstdr
Reverse suggests: SpatMCA

Linking:

Please use the canonical form https://CRAN.R-project.org/package=spTimer to link to this page.

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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