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 (2020, <doi:10.1177/0959683620913924>).
Version: 1.2.4 Depends: R (≥ 3.5.0), ggplot2, data.table, kohonen Imports: maps, reshape2 Suggests: knitr, rmarkdown, testthat Published: 2023-04-28 DOI: 10.32614/CRAN.package.somspace Author: Yannis Markonis [aut, cre], Filip Strnad [aut], Simon Michael Papalexiou [aut], Mijael Rodrigo Vargas Godoy [ctb] Maintainer: Yannis Markonis <imarkonis at gmail.com> License: GPL-3 NeedsCompilation: no Materials: README CRAN checks: somspace results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=somspace to link to this page.
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