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: 1.0.4
Depends: R (≥ 2.10)
Imports: stats, ggplot2, reshape2, scales, grDevices, RColorBrewer, shiny
Suggests: knitr, rmarkdown, testthat
Published: 2019-08-22
Author: Heraldo Borges [aut, cre] (CEFET/RJ), Amin Bazaz [aut] (Polytech'Montpellier), Luciana Escobar [aut] (CEFET/RJ), Esther Pacitti [aut] (University of Montpellier), 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

Downloads:

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_1.0.4.tar.gz
Windows binaries: r-devel: STMotif_1.0.2.zip, r-release: STMotif_1.0.2.zip, r-oldrel: STMotif_1.0.3.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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