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 [aut, cre], Sujit K. Sahu [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 [issues need fixing before 2026-03-25]

Documentation:

Reference manual:

spTimer.html , 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_3.3.3.zip
macOS binaries:	r-release (arm64): spTimer_3.3.3.tgz, r-oldrel (arm64): spTimer_3.3.3.tgz, r-release (x86_64): spTimer_3.3.3.tgz, r-oldrel (x86_64): spTimer_3.3.3.tgz
Old sources:	spTimer archive

Reverse dependencies:

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

Linking:

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