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.


This package allows 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.

Author

  • Amin Bazaz
  • Heraldo Borges
  • Eduardo Ogasawara

Licence

This project is licensed under the GPL License.

News

STMotif 1.0.1

  • Fix some functions.
  • Improvements of the documentation.

STMotif 1.0.0

  • Redefining the functions names.
  • Improvements of the documentation.

STMotif 0.1.1

  • Improvements of the documentation.
  • Fix the plot function

STMotif 0.1.0

  • Fist version of the STMotif package.

Reference manual

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install.packages("STMotif")

1.0.4 by Heraldo Borges, a month ago


Browse source code at https://github.com/cran/STMotif


Authors: 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)


Documentation:   PDF Manual  


GPL-2 | GPL-3 license


Imports stats, ggplot2, reshape2, scales, grDevices, RColorBrewer, shiny

Suggests knitr, rmarkdown, testthat


See at CRAN