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: |
2.0.1 |
Imports: |
stats, ggplot2, reshape2, scales, grDevices, RColorBrewer, shiny |
Suggests: |
knitr, rmarkdown, testthat |
Published: |
2020-11-14 |
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-2 | GPL-3 |
URL: |
https://github.com/heraldoborges/STMotif/wiki |
NeedsCompilation: |
no |
Citation: |
STMotif citation info |
Materials: |
NEWS |
CRAN checks: |
STMotif results |