SOMEnv: SOM Algorithm for the Analysis of Multivariate Environmental Data

Analysis of multivariate environmental high frequency data by Self-Organizing Map and k-means clustering algorithms. By means of the graphical user interface it provides a comfortable way to elaborate by self-organizing map algorithm rather big datasets (txt files up to 100 MB ) obtained by environmental high-frequency monitoring by sensors/instruments. The functions present in the package are based on 'kohonen' and 'openair' packages implemented by functions embedding Vesanto et al. (2001) <http://www.cis.hut.fi/projects/somtoolbox/package/papers/techrep.pdf> heuristic rules for map initialization parameters, k-means clustering algorithm and map features visualization. Cluster profiles visualization as well as graphs dedicated to the visualization of time-dependent variables Licen et al. (2020) <doi:10.4209/aaqr.2019.08.0414> are provided.

Version: 0.1.1
Imports: rlist, kohonen, shiny, dplyr, plyr, openair, colourpicker, shinycssloaders, shinycustomloader
Published: 2021-01-25
Author: Sabina Licen [aut, cre], Marco Franzon [aut], Tommaso Rodani [aut], Pierluigi Barbieri [aut]
Maintainer: Sabina Licen <slicen at units.it>
BugReports: https://github.com/SomEnv/somenv/issues
License: GPL-2
URL: https://github.com/SomEnv/somenv
NeedsCompilation: no
Citation: SOMEnv citation info
CRAN checks: SOMEnv results

Downloads:

Reference manual: SOMEnv.pdf
Package source: SOMEnv_0.1.1.tar.gz
Windows binaries: r-devel: SOMEnv_0.1.1.zip, r-release: SOMEnv_0.1.1.zip, r-oldrel: SOMEnv_0.1.1.zip
macOS binaries: r-release: SOMEnv_0.1.1.tgz, r-oldrel: SOMEnv_0.1.1.tgz

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