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: |
2.0.3 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
ggplot2 (≥ 3.4.0), scales, RColorBrewer, rlang, stats, grDevices |
| Suggests: |
testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: |
2026-03-29 |
| 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: |
GPL-3 |
| URL: |
https://github.com/heraldoborges/STMotif |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
STMotif results |