Mixture model is used to achieve the clustering goal. Each component is itself a mixture model of polynomial autoregressive regressions whose the logistic weights consider the spatial and temporal information.
Version: | 1.0 |
Depends: | R (≥ 3.0.2) |
Imports: | methods, Rcpp (≥ 0.11.1), parallel |
LinkingTo: | Rcpp, RcppArmadillo |
Published: | 2016-12-21 |
Author: | Cheam A., Marbac M., and McNicholas P. |
Maintainer: | Matthieu Marbac <matthieu.marbac at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
In views: | SpatioTemporal |
CRAN checks: | SpaTimeClus results |
Reference manual: | SpaTimeClus.pdf |
Package source: | SpaTimeClus_1.0.tar.gz |
Windows binaries: | r-devel: SpaTimeClus_1.0.zip, r-release: SpaTimeClus_1.0.zip, r-oldrel: SpaTimeClus_1.0.zip |
macOS binaries: | r-release: SpaTimeClus_1.0.tgz, r-oldrel: SpaTimeClus_1.0.tgz |
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