somspace: Spatial Analysis with Self-Organizing Maps

Application of the Self-Organizing Maps technique for spatial classification of time series. The package uses spatial data, point or gridded, to create clusters with similar characteristics. The clusters can be further refined to a smaller number of regions by hierarchical clustering and their spatial dependencies can be presented as complex networks. Thus, meaningful maps can be created, representing the regional heterogeneity of a single variable. More information and an example of implementation can be found in Markonis and Strnad (2019).

Version: 1.0.0
Depends: R (≥ 3.4.0), ggplot2, data.table, kohonen, maps
Suggests: knitr, rmarkdown, testthat
Published: 2019-05-13
Author: Yannis Markonis [aut, cre], Filip Strnad [aut], Simon Michael Papalexiou [aut]
Maintainer: Yannis Markonis <imarkonis at gmail.com>
License: GPL-3
NeedsCompilation: no
Materials: README
In views: Cluster, Hydrology
CRAN checks: somspace results

Downloads:

Reference manual: somspace.pdf
Vignettes: Vignette Title
Package source: somspace_1.0.0.tar.gz
Windows binaries: r-devel: somspace_1.0.0.zip, r-release: somspace_1.0.0.zip, r-oldrel: somspace_1.0.0.zip
OS X binaries: r-release: somspace_1.0.0.tgz, r-oldrel: somspace_1.0.0.tgz

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