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: 3.3.2
Depends: R (≥ 3.4.0)
Imports: coda, sp, spacetime, extraDistr, grDevices, graphics, stats, utils
Published: 2022-10-26
DOI: 10.32614/CRAN.package.spTimer
Author: K. Shuvo Bakar & Sujit K. Sahu
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


Reference manual: spTimer.pdf


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


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