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: 2.0.1
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

Documentation:

Reference manual: STMotif.pdf
Vignettes: STMotif R Package

Downloads:

Package source: STMotif_2.0.1.tar.gz
Windows binaries: r-devel: STMotif_2.0.1.zip, r-release: STMotif_2.0.1.zip, r-oldrel: STMotif_2.0.1.zip
macOS binaries: r-release (arm64): STMotif_2.0.1.tgz, r-release (x86_64): STMotif_2.0.1.tgz, r-oldrel: STMotif_2.0.1.tgz
Old sources: STMotif archive

Linking:

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