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Allows distance based spatial clustering of georeferenced data by implementing the City Clustering Algorithm - CCA. Multiple versions allow clustering for a matrix, raster and single coordinates on a plain (Euclidean distance) or on a sphere (great-circle or orthodromic distance).
| Version: | 1.0.5 |
| Depends: | methods, raster, R (≥ 2.14) |
| Suggests: | testthat, maps |
| Published: | 2019-12-19 |
| DOI: | 10.32614/CRAN.package.osc |
| Author: | Steffen Kriewald, Till Fluschnik, Dominik Reusser, Diego Rybski |
| Maintainer: | Steffen Kriewald <kriewald at pik-potsdam.de> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| URL: | https://www.pik-potsdam.de/~kriewald/osc/ |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | osc results |
| Reference manual: | osc.pdf |
| Vignettes: |
Using the City Clustering Algorithm |
| Package source: | osc_1.0.5.tar.gz |
| Windows binaries: | r-devel: osc_1.0.5.zip, r-release: osc_1.0.5.zip, r-oldrel: osc_1.0.5.zip |
| macOS binaries: | r-release (arm64): osc_1.0.5.tgz, r-oldrel (arm64): osc_1.0.5.tgz, r-release (x86_64): osc_1.0.5.tgz, r-oldrel (x86_64): osc_1.0.5.tgz |
| Old sources: | osc archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.