Allow to identify motifs in spatial-time series. A motif is a previously unknown subsequence of a (spatial) time series with relevant number of occurrences. For this purpose, the Combined Series Approach (CSA) is used.
| Version: | 1.0.2 |
| Depends: | R (≥ 2.10) |
| Imports: | stats, ggplot2, reshape2, scales, grDevices, RColorBrewer, shiny |
| Suggests: | knitr, rmarkdown, testthat |
| Published: | 2019-02-11 |
| Author: | Amin Bazaz [aut] (Polytech'Montpellier), Heraldo Borges [aut, cre] (CEFET/RJ), Eduardo Ogasawara [aut] (CEFET/RJ) |
| Maintainer: | Heraldo Borges <stmotif at eic.cefet-rj.br> |
| License: | GPL-2 | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | STMotif results |
| Reference manual: | STMotif.pdf |
| Vignettes: |
Motifs discovery in spatial-time series Example with a sample dataset Generation of candidates from a dataset Search for Spatial-time Motifs |
| Package source: | STMotif_1.0.2.tar.gz |
| Windows binaries: | r-devel: STMotif_1.0.2.zip, r-release: STMotif_1.0.2.zip, r-oldrel: STMotif_1.0.2.zip |
| OS X binaries: | r-release: STMotif_1.0.2.tgz, r-oldrel: STMotif_1.0.2.tgz |
| Old sources: | STMotif archive |
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