STMotif: Discovery of Motifs in Spatial-Time Series
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: | 2.0.2 |
| Imports: | stats,ggplot2,reshape2,scales, grDevices,RColorBrewer |
| Suggests: | knitr,rmarkdown,testthat |
| Published: | 2024-02-23 |
| DOI: | 10.32614/CRAN.package.STMotif |
| Author: | Heraldo Borges [aut, cre] (CEFET/RJ), Amin Bazaz [aut] (Polytech'Montpellier), Esther Pacciti [aut] (INRIA/Polytech'Montpellier), Eduardo Ogasawara [aut] (CEFET/RJ) |
| Maintainer: | Heraldo Borges <stmotif at eic.cefet-rj.br> |
| BugReports: | https://github.com/heraldoborges/STMotif/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/heraldoborges/STMotif/wiki |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | STMotif results |
Documentation:
Downloads:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=STMotifto link to this page.