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: | 3.0-1 |
| Depends: | R (≥ 3.4.1) |
| Imports: | coda, sp, spacetime, grDevices, graphics, stats, utils |
| Published: | 2017-10-19 |
| Author: | K. Shuvo Bakar & Sujit K. Sahu |
| Maintainer: | 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_3.0-1.tar.gz |
| Windows binaries: | r-devel: spTimer_3.0-1.zip, r-release: spTimer_3.0-1.zip, r-oldrel: spTimer_2.0-1.zip |
| OS X El Capitan binaries: | r-release: spTimer_3.0-1.tgz |
| OS X Mavericks binaries: | r-oldrel: spTimer_2.0-1.tgz |
| Old sources: | spTimer archive |
| Reverse depends: | spTDyn |
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