The package is able to fit, spatially predict and temporally forecast 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.
| Version: | 0.7 |
| Depends: | R (≥ 2.14.0), coda, lattice, forecast |
| Published: | 2013-05-23 |
| Author: | K. Shuvo Bakar & Sujit K. Sahu |
| Maintainer: | Khandoker Shuvo Bakar <Shuvo.Bakar at csiro.au> |
| License: | GPL (≥ 2) |
| URL: | http://www.southampton.ac.uk/~sks/research http://www.southampton.ac.uk/~sks/research/papers/spTimeRpaper.pdf |
| NeedsCompilation: | yes |
| In views: | Bayesian, SpatioTemporal |
| CRAN checks: | spTimer results |
| Package source: | spTimer_0.7.tar.gz |
| MacOS X binary: | spTimer_0.7.tgz |
| Windows binary: | spTimer_0.7.zip |
| Reference manual: | spTimer.pdf |
| Old sources: | spTimer archive |