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 (2020, doi:10.1177/0959683620913924).
- Version1.2.4
- R version≥ 3.5.0
- LicenseGPL-3
- Needs compilation?No
- Last release04/28/2023
Documentation
Team
Yannis Markonis
Mijael Rodrigo Vargas Godoy
Show author detailsRolesContributorSimon Michael Papalexiou
Show author detailsRolesAuthorFilip Strnad
Show author detailsRolesAuthor
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- Depends3 packages
- Imports2 packages
- Suggests3 packages